#334 by GitHub stars
foryourhealth111-pixel/Vibe-Skills
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
History
Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.
View weekly changes
SKILL.md
Week of Nov 2, 2026 · +2 / −2 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
- 242 - Version: 4.1.1
- 243 - Updated: 2026-10-18
+ 242 - Version: 4.1.2
+ 243 - Updated: 2026-11-04
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/.system/skill-creator/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/.system/skill-installer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/LQF_Machine_Learning_Expert_Guide/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/adaptyv/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/aeon/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/algorithmic-art/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/alpha-vantage/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/architecture-patterns/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/astropy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/autonomous-builder/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/bio-database-evidence/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/biopython/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/brainstorming/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/cancel-ralph/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/chembl-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/citation-management/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/claude-skills/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/clinical-decision-support/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/clinical-reports/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/clinicaltrials-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/clinpgx-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/code-reviewer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/coding-tutor/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/commit-with-reflection/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/comprehensive-research-agent/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/content-research-writer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/context-fundamentals/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/context-hunter/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/create-plan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/creating-data-visualizations/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/cs-foundations/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/dask/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/data-artist/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/data-quality-frameworks/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/data-storytelling/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/datacommons-client/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/datavis/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/denario/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/designing-experiments/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/deslop/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/detecting-data-anomalies/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/detecting-performance-regressions/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/dialectic/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/digital-brain/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/dnanexus-integration/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/doc/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/docs-review/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/docs-write/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/document-skills/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/document-skills/docx/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/document-skills/pdf/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/document-skills/pptx/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/documentation-lookup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/docx/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/docx-comment-reply/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/edgartools/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/embedding-strategies/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/ena-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/error-resolver/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/etetoolkit/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/evals-context/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/evaluating-code-models/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/evaluating-llms-harness/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/evaluating-machine-learning-models/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/explaining-machine-learning-models/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/exploratory-data-analysis/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/fda-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/figma-implement-design/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/file-organizer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/flashrag-evidence/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/fluidsim/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/fred-economic-data/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/g2-legend-expert/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/generate-image/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/generating-test-reports/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/geo-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/geomaster/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/geopandas/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/get-available-resources/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/gh-address-comments/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/gh-fix-ci/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/gradient-methods/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/gtars/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/hedgefundmonitor/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/histolab/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/hive-mind-advanced/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/hypothesis-generation/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/hypothesis-testing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/imagegen/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/imaging-data-commons/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/infographics/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/iso-13485-certification/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/jupyter-notebook/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/knowledge-steward/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/lamindb/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/latchbio-integration/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/latex-posters/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/latex-submission-pipeline/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/literature-review/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/local-vco-roles/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/manuscript-as-code/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/markdown-mermaid-writing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/market-research-reports/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/markitdown/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/matchms/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/math/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/math-model-selector/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/math-tools/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/mathematical-logic-expert/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/matlab/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/matplotlib/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/mcp-integration/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/medchem/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/metabolomics-workbench-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/metric-calculator/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/ml-data-leakage-guard/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/ml-pipeline-workflow/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/netlify-deploy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/networkx/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/neurokit2/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/neuropixels-analysis/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/node-zombie-guardian/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/nowait-reasoning-optimizer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/omero-integration/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/openai-docs/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/openai-knowledge/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/openalex-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/paper-2-web/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pathml/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pdf/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/peer-review/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/performance-testing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/performing-causal-analysis/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/perplexity-search/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/planning-with-files/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/playwright/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/plotly/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/polars/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pptx-posters/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/preprocessing-data-with-automated-pipelines/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/prompt-lookup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/property-based-testing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/propositional-logic/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/providing-performance-optimization-advice/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/prowler-docs/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pubmed-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pufferlib/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pydeseq2/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pydicom/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pyhealth/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pymatgen/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pymc/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pymc-bayesian-modeling/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pymoo/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pyopenms/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pytorch-lightning/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/pyzotero/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/ralph-loop/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/rdkit/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/receiving-code-review/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/report-generator/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/requesting-code-review/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/research-grants/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/research-lookup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/rowan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scanpy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scholar-evaluation/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scholarly-publishing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-brainstorming/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-critical-thinking/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-data-preprocessing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-reporting/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-schematics/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-slides/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-visualization/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scientific-writing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scikit-bio/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scikit-learn/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scikit-survival/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/scrapling/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/screenshot/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/seaborn/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/security-best-practices/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/security-ownership-map/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/security-reviewer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/security-threat-model/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/senior-computer-vision/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/senior-data-scientist/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/senior-ml-engineer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/senior-prompt-engineer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/sentry/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/shap/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/similarity-search-patterns/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/simpy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/skill-creator/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/skill-lookup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/skypilot-multi-cloud-orchestration/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/slides-as-code/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/smart-file-writer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/sparse-autoencoder-training/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/spec-kit-vibe-compat/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-analyze/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-checklist/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-clarify/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-constitution/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-implement/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-plan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-specify/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-tasks/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speckit-taskstoissues/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/speech/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/splitting-datasets/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/spreadsheet/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/stable-baselines3/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/statistical-analysis/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/statistics-math/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/statsmodels/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/structured-content-storage/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/subagent-driven-development/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/submission-checklist/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/sympy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/systematic-debugging/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/tdd-guide/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/tensorboard/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/theme-factory/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/think-harder/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/tiledbvcf/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/timesfm-forecasting/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/torch-geometric/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/torchdrug/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/transcribe/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/transformer-lens-interpretability/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/transformers/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/treatment-plans/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/umap-learn/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/uniprot-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/unsloth/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/usfiscaldata/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/uspto-database/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/ux-researcher-designer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Local scripts
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/vaex/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/venue-templates/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/vercel-deploy/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/verification-before-completion/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/verification-quality-assurance/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/video-studio/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/visualization-best-practices/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/vscode-release-notes-writer/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Network or broad shell → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Network or broad shell
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/webthinker-deep-research/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/weights-and-biases/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/windows-hook-debugging/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/writing-docs/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/writing-plans/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/xan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/xlsx/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Local scripts → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Local scripts
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/yeet/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Instructions only
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
bundled/skills/zarr-python/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
Before Instructions only → After Network or broad shell
5200420c1992 → bd10381417cb
Week of Oct 26, 2026 · Line counts unavailable
Before Not checked yet → After Instructions only
First observation → 5200420c1992
No earlier version was observed for comparison.
View on GitHubAdd to my skills
Verified commit bd10381417cbd890ed6f08a18bb18fb5aaf0f741
git clone --filter=blob:none --no-checkout https://github.com/foryourhealth111-pixel/Vibe-Skills.git .hotskills/foryourhealth111-pixel-vibe-skills && git -C .hotskills/foryourhealth111-pixel-vibe-skills checkout --detach bd10381417cbd890ed6f08a18bb18fb5aaf0f741
# Copy each selected skill directory from .hotskills/foryourhealth111-pixel-vibe-skills into .agents/skills/<skill-name>/3.8kGitHub stars
17stars in 7 days
258skills in this repository
67commits in 30 days
Heat
5.9- Star growth, last 7 daysAhead of 70% of tracked repositories
- Star growth, last 24 hoursAhead of 73% of tracked repositories
- Rank movement, last 7 daysAhead of 42% of tracked repositories
- Commits, last 30 daysAhead of 92% of tracked repositories
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekAhead of 0% of tracked repositories
Heat never changes the order by stars, and sponsorship never touches it. How heat works
Stars over time
Individual skills in this repository
- vibe
/ - skill-creator
bundled/skills/.system/skill-creator - skill-installer
bundled/skills/.system/skill-installer - LQF_Machine_Learning_Expert_Guide
bundled/skills/LQF_Machine_Learning_Expert_Guide - adaptyv
bundled/skills/adaptyv - aeon
bundled/skills/aeon - algorithmic-art
bundled/skills/algorithmic-art - alpha-vantage
bundled/skills/alpha-vantage - architecture-patterns
bundled/skills/architecture-patterns - astropy
bundled/skills/astropy - autonomous-builder
bundled/skills/autonomous-builder - bio-database-evidence
bundled/skills/bio-database-evidence - biopython
bundled/skills/biopython - brainstorming
bundled/skills/brainstorming - cancel-ralph
bundled/skills/cancel-ralph - chembl-database
bundled/skills/chembl-database - citation-management
bundled/skills/citation-management - claude-skills
bundled/skills/claude-skills - clinical-decision-support
bundled/skills/clinical-decision-support - clinical-reports
bundled/skills/clinical-reports - clinicaltrials-database
bundled/skills/clinicaltrials-database - clinpgx-database
bundled/skills/clinpgx-database - code-reviewer
bundled/skills/code-reviewer - coding-tutor
bundled/skills/coding-tutor - commit-with-reflection
bundled/skills/commit-with-reflection - comprehensive-research-agent
bundled/skills/comprehensive-research-agent - content-research-writer
bundled/skills/content-research-writer - context-fundamentals
bundled/skills/context-fundamentals - context-hunter
bundled/skills/context-hunter - create-plan
bundled/skills/create-plan - creating-data-visualizations
bundled/skills/creating-data-visualizations - cs-foundations
bundled/skills/cs-foundations - dask
bundled/skills/dask - data-artist
bundled/skills/data-artist - data-quality-frameworks
bundled/skills/data-quality-frameworks - data-storytelling
bundled/skills/data-storytelling - datacommons-client
bundled/skills/datacommons-client - datavis
bundled/skills/datavis - denario
bundled/skills/denario - designing-experiments
bundled/skills/designing-experiments - deslop
bundled/skills/deslop - detecting-data-anomalies
bundled/skills/detecting-data-anomalies - detecting-performance-regressions
bundled/skills/detecting-performance-regressions - dialectic
bundled/skills/dialectic - digital-brain
bundled/skills/digital-brain - dnanexus-integration
bundled/skills/dnanexus-integration - doc
bundled/skills/doc - docs-review
bundled/skills/docs-review - docs-write
bundled/skills/docs-write - document-skills
bundled/skills/document-skills - docx
bundled/skills/document-skills/docx - pdf
bundled/skills/document-skills/pdf - pptx
bundled/skills/document-skills/pptx - documentation-lookup
bundled/skills/documentation-lookup - docx
bundled/skills/docx - docx-comment-reply
bundled/skills/docx-comment-reply - edgartools
bundled/skills/edgartools - embedding-strategies
bundled/skills/embedding-strategies - ena-database
bundled/skills/ena-database - Error Resolver
bundled/skills/error-resolver - etetoolkit
bundled/skills/etetoolkit - evals-context
bundled/skills/evals-context - evaluating-code-models
bundled/skills/evaluating-code-models - evaluating-llms-harness
bundled/skills/evaluating-llms-harness - evaluating-machine-learning-models
bundled/skills/evaluating-machine-learning-models - explaining-machine-learning-models
bundled/skills/explaining-machine-learning-models - exploratory-data-analysis
bundled/skills/exploratory-data-analysis - fda-database
bundled/skills/fda-database - figma-implement-design
bundled/skills/figma-implement-design - file-organizer
bundled/skills/file-organizer - flashrag-evidence
bundled/skills/flashrag-evidence - fluidsim
bundled/skills/fluidsim - fred-economic-data
bundled/skills/fred-economic-data - G2 Legend Expert
bundled/skills/g2-legend-expert - generate-image
bundled/skills/generate-image - generating-test-reports
bundled/skills/generating-test-reports - geo-database
bundled/skills/geo-database - geomaster
bundled/skills/geomaster - geopandas
bundled/skills/geopandas - get-available-resources
bundled/skills/get-available-resources - gh-address-comments
bundled/skills/gh-address-comments - gh-fix-ci
bundled/skills/gh-fix-ci - gradient-methods
bundled/skills/gradient-methods - gtars
bundled/skills/gtars - hedgefundmonitor
bundled/skills/hedgefundmonitor - histolab
bundled/skills/histolab - hive-mind-advanced
bundled/skills/hive-mind-advanced - hypothesis-generation
bundled/skills/hypothesis-generation - hypothesis-testing
bundled/skills/hypothesis-testing - imagegen
bundled/skills/imagegen - imaging-data-commons
bundled/skills/imaging-data-commons - infographics
bundled/skills/infographics - iso-13485-certification
bundled/skills/iso-13485-certification - jupyter-notebook
bundled/skills/jupyter-notebook - knowledge-steward
bundled/skills/knowledge-steward - lamindb
bundled/skills/lamindb - latchbio-integration
bundled/skills/latchbio-integration - latex-posters
bundled/skills/latex-posters - latex-submission-pipeline
bundled/skills/latex-submission-pipeline - literature-review
bundled/skills/literature-review - local-vco-roles
bundled/skills/local-vco-roles - manuscript-as-code
bundled/skills/manuscript-as-code - markdown-mermaid-writing
bundled/skills/markdown-mermaid-writing - market-research-reports
bundled/skills/market-research-reports - markitdown
bundled/skills/markitdown - matchms
bundled/skills/matchms - math
bundled/skills/math - math-model-selector
bundled/skills/math-model-selector - math-tools
bundled/skills/math-tools - mathematical-logic-expert
bundled/skills/mathematical-logic-expert - matlab
bundled/skills/matlab - matplotlib
bundled/skills/matplotlib - MCP Integration
bundled/skills/mcp-integration - medchem
bundled/skills/medchem - metabolomics-workbench-database
bundled/skills/metabolomics-workbench-database - metric-calculator
bundled/skills/metric-calculator - ml-data-leakage-guard
bundled/skills/ml-data-leakage-guard - ml-pipeline-workflow
bundled/skills/ml-pipeline-workflow - netlify-deploy
bundled/skills/netlify-deploy - networkx
bundled/skills/networkx - neurokit2
bundled/skills/neurokit2 - neuropixels-analysis
bundled/skills/neuropixels-analysis - node-zombie-guardian
bundled/skills/node-zombie-guardian - nowait-reasoning-optimizer
bundled/skills/nowait-reasoning-optimizer - omero-integration
bundled/skills/omero-integration - openai-docs
bundled/skills/openai-docs - openai-knowledge
bundled/skills/openai-knowledge - openalex-database
bundled/skills/openalex-database - paper-2-web
bundled/skills/paper-2-web - pathml
bundled/skills/pathml - pdf
bundled/skills/pdf - peer-review
bundled/skills/peer-review - performance-testing
bundled/skills/performance-testing - performing-causal-analysis
bundled/skills/performing-causal-analysis - perplexity-search
bundled/skills/perplexity-search - planning-with-files
bundled/skills/planning-with-files - playwright
bundled/skills/playwright - plotly
bundled/skills/plotly - polars
bundled/skills/polars - pptx-posters
bundled/skills/pptx-posters - preprocessing-data-with-automated-pipelines
bundled/skills/preprocessing-data-with-automated-pipelines - prompt-lookup
bundled/skills/prompt-lookup - property-based-testing
bundled/skills/property-based-testing - propositional-logic
bundled/skills/propositional-logic - providing-performance-optimization-advice
bundled/skills/providing-performance-optimization-advice - prowler-docs
bundled/skills/prowler-docs - pubmed-database
bundled/skills/pubmed-database - pufferlib
bundled/skills/pufferlib - pydeseq2
bundled/skills/pydeseq2 - pydicom
bundled/skills/pydicom - pyhealth
bundled/skills/pyhealth - pymatgen
bundled/skills/pymatgen - pymc-bayesian-modeling
bundled/skills/pymc - pymc-bayesian-modeling
bundled/skills/pymc-bayesian-modeling - pymoo
bundled/skills/pymoo - pyopenms
bundled/skills/pyopenms - pytorch-lightning
bundled/skills/pytorch-lightning - pyzotero
bundled/skills/pyzotero - ralph-loop
bundled/skills/ralph-loop - rdkit
bundled/skills/rdkit - receiving-code-review
bundled/skills/receiving-code-review - report-generator
bundled/skills/report-generator - requesting-code-review
bundled/skills/requesting-code-review - research-grants
bundled/skills/research-grants - research-lookup
bundled/skills/research-lookup - rowan
bundled/skills/rowan - scanpy
bundled/skills/scanpy - scholar-evaluation
bundled/skills/scholar-evaluation - scholarly-publishing
bundled/skills/scholarly-publishing - scientific-brainstorming
bundled/skills/scientific-brainstorming - scientific-critical-thinking
bundled/skills/scientific-critical-thinking - scientific-data-preprocessing
bundled/skills/scientific-data-preprocessing - scientific-reporting
bundled/skills/scientific-reporting - scientific-schematics
bundled/skills/scientific-schematics - scientific-slides
bundled/skills/scientific-slides - scientific-visualization
bundled/skills/scientific-visualization - scientific-writing
bundled/skills/scientific-writing - scikit-bio
bundled/skills/scikit-bio - scikit-learn
bundled/skills/scikit-learn - scikit-survival
bundled/skills/scikit-survival - scrapling
bundled/skills/scrapling - screenshot
bundled/skills/screenshot - seaborn
bundled/skills/seaborn - security-best-practices
bundled/skills/security-best-practices - security-ownership-map
bundled/skills/security-ownership-map - security-reviewer
bundled/skills/security-reviewer - security-threat-model
bundled/skills/security-threat-model - senior-computer-vision
bundled/skills/senior-computer-vision - senior-data-scientist
bundled/skills/senior-data-scientist - senior-ml-engineer
bundled/skills/senior-ml-engineer - senior-prompt-engineer
bundled/skills/senior-prompt-engineer - sentry
bundled/skills/sentry - shap
bundled/skills/shap - similarity-search-patterns
bundled/skills/similarity-search-patterns - simpy
bundled/skills/simpy - skill-creator
bundled/skills/skill-creator - skill-lookup
bundled/skills/skill-lookup - skypilot-multi-cloud-orchestration
bundled/skills/skypilot-multi-cloud-orchestration - slides-as-code
bundled/skills/slides-as-code - smart-file-writer
bundled/skills/smart-file-writer - sparse-autoencoder-training
bundled/skills/sparse-autoencoder-training - spec-kit-vibe-compat
bundled/skills/spec-kit-vibe-compat - speckit-analyze
bundled/skills/speckit-analyze - speckit-checklist
bundled/skills/speckit-checklist - speckit-clarify
bundled/skills/speckit-clarify - speckit-constitution
bundled/skills/speckit-constitution - speckit-implement
bundled/skills/speckit-implement - speckit-plan
bundled/skills/speckit-plan - speckit-specify
bundled/skills/speckit-specify - speckit-tasks
bundled/skills/speckit-tasks - speckit-taskstoissues
bundled/skills/speckit-taskstoissues - speech
bundled/skills/speech - splitting-datasets
bundled/skills/splitting-datasets - spreadsheet
bundled/skills/spreadsheet - stable-baselines3
bundled/skills/stable-baselines3 - statistical-analysis
bundled/skills/statistical-analysis - statistics-math
bundled/skills/statistics-math - statsmodels
bundled/skills/statsmodels - structured-content-storage
bundled/skills/structured-content-storage - subagent-driven-development
bundled/skills/subagent-driven-development - submission-checklist
bundled/skills/submission-checklist - sympy
bundled/skills/sympy - systematic-debugging
bundled/skills/systematic-debugging - tdd-guide
bundled/skills/tdd-guide - tensorboard
bundled/skills/tensorboard - theme-factory
bundled/skills/theme-factory - think-harder
bundled/skills/think-harder - tiledbvcf
bundled/skills/tiledbvcf - timesfm-forecasting
bundled/skills/timesfm-forecasting - torch-geometric
bundled/skills/torch-geometric - torchdrug
bundled/skills/torchdrug - transcribe
bundled/skills/transcribe - transformer-lens-interpretability
bundled/skills/transformer-lens-interpretability - transformers
bundled/skills/transformers - treatment-plans
bundled/skills/treatment-plans - umap-learn
bundled/skills/umap-learn - uniprot-database
bundled/skills/uniprot-database - unsloth
bundled/skills/unsloth - usfiscaldata
bundled/skills/usfiscaldata - uspto-database
bundled/skills/uspto-database - ux-researcher-designer
bundled/skills/ux-researcher-designer - vaex
bundled/skills/vaex - venue-templates
bundled/skills/venue-templates - vercel-deploy
bundled/skills/vercel-deploy - verification-before-completion
bundled/skills/verification-before-completion - Verification & Quality Assurance
bundled/skills/verification-quality-assurance - video-studio
bundled/skills/video-studio - visualization-best-practices
bundled/skills/visualization-best-practices - vscode-release-notes-writer
bundled/skills/vscode-release-notes-writer - webthinker-deep-research
bundled/skills/webthinker-deep-research - weights-and-biases
bundled/skills/weights-and-biases - windows-hook-debugging
bundled/skills/windows-hook-debugging - writing-docs
bundled/skills/writing-docs - writing-plans
bundled/skills/writing-plans - xan
bundled/skills/xan - xlsx
bundled/skills/xlsx - yeet
bundled/skills/yeet - zarr-python
bundled/skills/zarr-python
How it works
vibe
When your agent uses it
Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, bounds execution, and enforces verification and phase cleanup.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
3,698 tokensWhen the skill is activated
Reference documents
76,501 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Trigger Contract
- Canonical Bootstrap
- Consensus And Task Evolution
- Hard Stop And Re-entry
- Unified Runtime Contract
- Skill Execution
- Quality Rules
- User Delivery
- Protocol Map
- Maintenance
Scripts executed separately
_python_source_roots.pyapps/vgo-cli/src/vgo_cli/__init__.pyapps/vgo-cli/src/vgo_cli/commands.pyapps/vgo-cli/src/vgo_cli/core_bridge.pyapps/vgo-cli/src/vgo_cli/errors.pyapps/vgo-cli/src/vgo_cli/external.pyapps/vgo-cli/src/vgo_cli/hosts.pyapps/vgo-cli/src/vgo_cli/install_gates.pyapps/vgo-cli/src/vgo_cli/install_support.pyapps/vgo-cli/src/vgo_cli/installer_bridge.pyapps/vgo-cli/src/vgo_cli/main.pyapps/vgo-cli/src/vgo_cli/output.pyapps/vgo-cli/src/vgo_cli/process.pyapps/vgo-cli/src/vgo_cli/repo.pyapps/vgo-cli/src/vgo_cli/skill_surface.pyapps/vgo-cli/src/vgo_cli/upgrade_service.pyapps/vgo-cli/src/vgo_cli/upgrade_state.pyapps/vgo-cli/src/vgo_cli/version_reminder.pyapps/vgo-cli/src/vgo_cli/workspace.pycheck.ps1check.shdocs/cases/ml-experiment/reproduce/compute_uncertainty.pydocs/cases/ml-experiment/reproduce/create_data_audit.pydocs/cases/ml-experiment/reproduce/make_figures.pydocs/cases/ml-experiment/reproduce/reproduce.ps1docs/cases/ml-experiment/reproduce/run_experiment.pyinstall.ps1install.shpackages/adapter-sdk/src/vgo_adapters/__init__.pypackages/adapter-sdk/src/vgo_adapters/descriptor_loader.pypackages/adapter-sdk/src/vgo_adapters/target_root_resolver.pypackages/contracts/src/vgo_contracts/__init__.pypackages/contracts/src/vgo_contracts/adapter_descriptor.pypackages/contracts/src/vgo_contracts/adapter_registry_support.pypackages/contracts/src/vgo_contracts/canonical_vibe_contract.pypackages/contracts/src/vgo_contracts/catalog_descriptor.pypackages/contracts/src/vgo_contracts/discoverable_entry_surface.pypackages/contracts/src/vgo_contracts/entry_root_guard.pypackages/contracts/src/vgo_contracts/git_provenance.pypackages/contracts/src/vgo_contracts/governance_runtime_roles.pypackages/contracts/src/vgo_contracts/host_launch_receipt.pypackages/contracts/src/vgo_contracts/host_runtime_readiness.pypackages/contracts/src/vgo_contracts/install_ledger.pypackages/contracts/src/vgo_contracts/installed_runtime_contract.pypackages/contracts/src/vgo_contracts/live_governance_contract.pypackages/contracts/src/vgo_contracts/mirror_topology_contract.pypackages/contracts/src/vgo_contracts/module_execution_contract.pypackages/contracts/src/vgo_contracts/runtime_packet.pypackages/contracts/src/vgo_contracts/runtime_surface_contract.pypackages/contracts/src/vgo_contracts/target_root_contract.pypackages/contracts/src/vgo_contracts/tdd_evidence_contract.pypackages/contracts/src/vgo_contracts/verification_scenario.pypackages/contracts/src/vgo_contracts/workspace_memory_identity.pypackages/installer-core/src/vgo_installer/__init__.pypackages/installer-core/src/vgo_installer/_bootstrap.pypackages/installer-core/src/vgo_installer/_io.pypackages/installer-core/src/vgo_installer/_path_safety.pypackages/installer-core/src/vgo_installer/adapter_registry.pypackages/installer-core/src/vgo_installer/discoverable_wrappers.pypackages/installer-core/src/vgo_installer/global_instruction_contract.pypackages/installer-core/src/vgo_installer/global_instruction_merge.pypackages/installer-core/src/vgo_installer/global_instruction_service.pypackages/installer-core/src/vgo_installer/host_closure.pypackages/installer-core/src/vgo_installer/install_plan.pypackages/installer-core/src/vgo_installer/install_runtime.pypackages/installer-core/src/vgo_installer/ledger_service.pypackages/installer-core/src/vgo_installer/materializer.pypackages/installer-core/src/vgo_installer/profile_inventory.pypackages/installer-core/src/vgo_installer/repair.pypackages/installer-core/src/vgo_installer/runtime_packaging.pypackages/installer-core/src/vgo_installer/simple_skill_installer.pypackages/installer-core/src/vgo_installer/uninstall_plan.pypackages/installer-core/src/vgo_installer/uninstall_runtime.pypackages/installer-core/src/vgo_installer/uninstall_service.pypackages/runtime-core/src/vgo_runtime/__init__.pypackages/runtime-core/src/vgo_runtime/artifact_contract.pypackages/runtime-core/src/vgo_runtime/canonical_entry.pypackages/runtime-core/src/vgo_runtime/compatibility_exit.pypackages/runtime-core/src/vgo_runtime/custom_admission.pypackages/runtime-core/src/vgo_runtime/entry_locator.pypackages/runtime-core/src/vgo_runtime/entry_policy.pypackages/runtime-core/src/vgo_runtime/governance.pypackages/runtime-core/src/vgo_runtime/grade_intent.pypackages/runtime-core/src/vgo_runtime/kernel/__init__.pypackages/runtime-core/src/vgo_runtime/kernel/_io.pypackages/runtime-core/src/vgo_runtime/kernel/capability_bridge.pypackages/runtime-core/src/vgo_runtime/kernel/codex_plugins.pypackages/runtime-core/src/vgo_runtime/kernel/codex_skill_policy.pypackages/runtime-core/src/vgo_runtime/kernel/executor.pypackages/runtime-core/src/vgo_runtime/kernel/finder.pypackages/runtime-core/src/vgo_runtime/kernel/host_skill_roots.pypackages/runtime-core/src/vgo_runtime/kernel/loop.pypackages/runtime-core/src/vgo_runtime/kernel/module_assignments.pypackages/runtime-core/src/vgo_runtime/kernel/planner.pypackages/runtime-core/src/vgo_runtime/kernel/run_state.pypackages/runtime-core/src/vgo_runtime/kernel/skill_index.pypackages/runtime-core/src/vgo_runtime/kernel/skill_manifest.pypackages/runtime-core/src/vgo_runtime/kernel/skill_resources.pypackages/runtime-core/src/vgo_runtime/kernel/task_card.pypackages/runtime-core/src/vgo_runtime/kernel/text_tokens.pypackages/runtime-core/src/vgo_runtime/kernel/verifier.pypackages/runtime-core/src/vgo_runtime/kernel/work_plan.pypackages/runtime-core/src/vgo_runtime/memory.pypackages/runtime-core/src/vgo_runtime/planning.pypackages/runtime-core/src/vgo_runtime/powershell_bridge.pypackages/runtime-core/src/vgo_runtime/process_tree.pypackages/runtime-core/src/vgo_runtime/route_index.pypackages/runtime-core/src/vgo_runtime/router_contract_runtime.pypackages/runtime-core/src/vgo_runtime/runtime_bridge.pypackages/runtime-core/src/vgo_runtime/runtime_summary.pypackages/runtime-core/src/vgo_runtime/runtime_support.pypackages/runtime-core/src/vgo_runtime/runtime_truth.pypackages/runtime-core/src/vgo_runtime/skill_authority.pypackages/runtime-core/src/vgo_runtime/stage_machine.pypackages/runtime-core/src/vgo_runtime/stage_stop.pypackages/runtime-core/src/vgo_runtime/task_intent.pypackages/runtime-core/src/vgo_runtime/workspace_memory.pypackages/runtime-core/src/vgo_runtime/workspace_memory_schema.pypackages/skill-catalog/src/vgo_catalog/__init__.pypackages/skill-catalog/src/vgo_catalog/_bootstrap.pypackages/skill-catalog/src/vgo_catalog/exporter.pypackages/verification-core/src/vgo_verify/__init__.pypackages/verification-core/src/vgo_verify/_bootstrap.pypackages/verification-core/src/vgo_verify/_io.pypackages/verification-core/src/vgo_verify/_repo.pypackages/verification-core/src/vgo_verify/bio_science_pack_consolidation_audit.pypackages/verification-core/src/vgo_verify/bootstrap_doctor.pypackages/verification-core/src/vgo_verify/bootstrap_doctor_runtime.pypackages/verification-core/src/vgo_verify/bootstrap_doctor_support.pypackages/verification-core/src/vgo_verify/code_quality_pack_consolidation_audit.pypackages/verification-core/src/vgo_verify/gate_engine.pypackages/verification-core/src/vgo_verify/global_pack_consolidation_audit.pypackages/verification-core/src/vgo_verify/ml_skills_pruning_audit.pypackages/verification-core/src/vgo_verify/opencode_preview_smoke.pypackages/verification-core/src/vgo_verify/opencode_preview_smoke_runtime.pypackages/verification-core/src/vgo_verify/opencode_preview_smoke_support.pypackages/verification-core/src/vgo_verify/policies.pypackages/verification-core/src/vgo_verify/proof_publication.pypackages/verification-core/src/vgo_verify/release_notes_quality.pypackages/verification-core/src/vgo_verify/release_notes_quality_runtime.pypackages/verification-core/src/vgo_verify/release_notes_quality_support.pypackages/verification-core/src/vgo_verify/release_truth.pypackages/verification-core/src/vgo_verify/router_ai_connectivity_probe.pypackages/verification-core/src/vgo_verify/router_ai_probe_advice.pypackages/verification-core/src/vgo_verify/router_ai_probe_support.pypackages/verification-core/src/vgo_verify/router_ai_probe_vector.pypackages/verification-core/src/vgo_verify/router_bridge_gate.pypackages/verification-core/src/vgo_verify/router_bridge_gate_runtime.pypackages/verification-core/src/vgo_verify/router_bridge_gate_support.pypackages/verification-core/src/vgo_verify/runtime_coherence.pypackages/verification-core/src/vgo_verify/runtime_coherence_runtime.pypackages/verification-core/src/vgo_verify/runtime_coherence_support.pypackages/verification-core/src/vgo_verify/runtime_delivery_acceptance.pypackages/verification-core/src/vgo_verify/runtime_delivery_acceptance_runtime.pypackages/verification-core/src/vgo_verify/runtime_delivery_acceptance_support.pypackages/verification-core/src/vgo_verify/runtime_freshness.pypackages/verification-core/src/vgo_verify/scenario_runner.pypackages/verification-core/src/vgo_verify/test_baseline_audit.pypackages/verification-core/src/vgo_verify/workflow_acceptance.pypackages/verification-core/src/vgo_verify/workflow_acceptance_runtime.pypackages/verification-core/src/vgo_verify/workflow_acceptance_support.pyscripts.check.upstream.shscripts/bootstrap/one-shot-setup.ps1scripts/bootstrap/one-shot-setup.shscripts/bootstrap/scaffold-claude-preview.ps1scripts/bootstrap/scaffold-claude-preview.shscripts/bootstrap/sync-local-compat.ps1scripts/build/assemble_distribution.pyscripts/build/sync_adapter_registry.pyscripts/build/sync_dist_release_manifests.pyscripts/build/sync_runtime_core_packaging_profiles.pyscripts/build/sync_version_governance_runtime_roles.pyscripts/common/AntiProxyGoalDrift.ps1scripts/common/NodeLaunchWrapper.ps1scripts/common/ProcessLedger.ps1scripts/common/ProtectedDocumentCleanup.ps1scripts/common/Resolve-VgoAdapter.ps1scripts/common/adapter_registry_query.pyscripts/common/python_helpers.shscripts/common/resolve_vgo_adapter.pyscripts/common/runtime_contracts.pyscripts/common/vibe-governance-helpers.ps1scripts/common/vibe-wave-gate-runner.ps1scripts/governance/Invoke-NodeProcessAudit.ps1scripts/governance/Invoke-NodeZombieCleanup.ps1scripts/governance/audit-upstream.ps1scripts/governance/export-repo-cleanliness-inventory.ps1scripts/governance/install-local-worktree-excludes.ps1scripts/governance/invoke-mem0-policy.ps1scripts/governance/invoke-openspec-governance.ps1scripts/governance/new-origin-record.ps1scripts/governance/phase-end-cleanup.ps1scripts/governance/publish-absorption-soft-rollout.ps1scripts/governance/publish-openspec-soft-rollout.ps1scripts/governance/release-cut.ps1scripts/governance/set-gsd-overlay-rollout.ps1scripts/governance/set-openspec-rollout.ps1scripts/governance/sync-bundled-vibe.ps1scripts/install/Install-VgoAdapter.ps1scripts/install/install_vgo_adapter.pyscripts/overlay/suggest-browserops-provider.ps1scripts/overlay/suggest-overlays.ps1scripts/release/build_release_bundle.pyscripts/research/build-eval-slicing-catalog.ps1scripts/research/build-watch-portfolio-review.ps1scripts/research/build-xl-operator-checklist.ps1scripts/research/extract-prompt-signals.ps1scripts/research/generate-vco-suggestions.ps1scripts/research/sync-mcp-catalog.ps1scripts/research/vibe-adaptive-train.ps1scripts/router/invoke-pack-route.pyscripts/router/modules/00-core-utils.ps1scripts/router/modules/01-openai-responses.ps1scripts/router/modules/10-observability.ps1scripts/router/modules/11-route-probe.ps1scripts/router/modules/12-heartbeat.ps1scripts/router/modules/19-custom-admission.ps1scripts/router/modules/20-routing-rules.ps1scripts/router/modules/21-capability-interview.ps1scripts/router/modules/22-intent-contract.ps1scripts/router/modules/30-openspec.ps1scripts/router/modules/31-gsd-overlay.ps1scripts/router/modules/32-prompt-overlay.ps1scripts/router/modules/33-memory-governance.ps1scripts/router/modules/34-data-scale-overlay.ps1scripts/router/modules/35-quality-debt-overlay.ps1scripts/router/modules/36-framework-interop-overlay.ps1scripts/router/modules/37-ml-lifecycle-overlay.ps1scripts/router/modules/38-python-clean-code-overlay.ps1scripts/router/modules/39-system-design-overlay.ps1scripts/router/modules/40-cuda-kernel-overlay.ps1scripts/router/modules/42-ai-rerank-overlay.ps1scripts/router/modules/43-retrieval-overlay.ps1scripts/router/modules/44-dialectic-team-gate.ps1scripts/router/modules/44-exploration-overlay.ps1scripts/router/modules/45-daily-dialectic-guard.ps1scripts/router/modules/47-closure-overlay.ps1scripts/router/modules/48-llm-acceleration-overlay.ps1scripts/router/modules/49-prompt-asset-boost.ps1scripts/router/resolve-pack-route.ps1scripts/router/runtime_neutral/custom_admission.pyscripts/router/runtime_neutral/router_contract.pyscripts/ruc-nlpir/preflight.ps1scripts/runtime/Freeze-RuntimeInputPacket.ps1scripts/runtime/Invoke-AntiProxyGoalDriftCompaction.ps1scripts/runtime/Invoke-DeepInterview.ps1scripts/runtime/Invoke-PhaseCleanup.ps1scripts/runtime/Invoke-PlanExecute.ps1scripts/runtime/Invoke-SkeletonCheck.ps1scripts/runtime/Invoke-VibeCanonicalEntry.ps1scripts/runtime/VibeMemoryActivation.Common.ps1scripts/runtime/VibeMemoryBackends.Common.ps1scripts/runtime/VibeRuntime.Common.ps1scripts/runtime/VibeSkillRouting.Common.ps1scripts/runtime/VibeWorkspaceMemory.Common.ps1scripts/runtime/Write-RequirementDoc.ps1scripts/runtime/Write-XlPlan.ps1scripts/runtime/invoke-vibe-runtime.ps1scripts/runtime/memory_backend_driver.pyscripts/runtime/skill_authority_driver.pyscripts/runtime/workspace_memory_driver.pyscripts/setup/check-kvm-host-readiness.shscripts/setup/check-windows-eval-iso-readiness.shscripts/setup/check-windows-proof-vm-state.shscripts/setup/export-codex-settings-sanitized.ps1scripts/setup/fetch-windows11-eval-iso.shscripts/setup/install-local-vm-host.shscripts/setup/persist-codex-openai-env.ps1scripts/setup/run-windows-proof-vm.shscripts/setup/send-qmp-boot-keys.pyscripts/setup/send-qmp-text.pyscripts/setup/show-windows-proof-media-options.shscripts/setup/stop-windows-proof-vm.shscripts/setup/sync-codex-settings-to-user-env.ps1scripts/uninstall/Uninstall-VgoAdapter.ps1scripts/uninstall/uninstall_vgo_adapter.pyscripts/verify/cer-compare.ps1scripts/verify/lib/VibeOfflineSkillsAudit.Suites.ps1scripts/verify/lib/VibeOfflineSkillsAudit.ps1scripts/verify/lib/VibeRouteAudit.Suites.ps1scripts/verify/lib/VibeRouteAudit.ps1scripts/verify/live-document-gate.pyscripts/verify/probe-scientific-packs.ps1scripts/verify/publish-proof.pyscripts/verify/runtime_neutral/_bootstrap.pyscripts/verify/runtime_neutral/bio_science_pack_consolidation_audit.pyscripts/verify/runtime_neutral/bootstrap_doctor.pyscripts/verify/runtime_neutral/code_quality_pack_consolidation_audit.pyscripts/verify/runtime_neutral/coherence_gate.pyscripts/verify/runtime_neutral/freshness_gate.pyscripts/verify/runtime_neutral/global_pack_consolidation_audit.pyscripts/verify/runtime_neutral/ml_skills_pruning_audit.pyscripts/verify/runtime_neutral/opencode_preview_smoke.pyscripts/verify/runtime_neutral/release_notes_quality.pyscripts/verify/runtime_neutral/release_truth_gate.pyscripts/verify/runtime_neutral/router_ai_connectivity_probe.pyscripts/verify/runtime_neutral/router_bridge_gate.pyscripts/verify/runtime_neutral/runtime_delivery_acceptance.pyscripts/verify/runtime_neutral/workflow_acceptance_runner.pyscripts/verify/skill-metadata-gate.ps1scripts/verify/test-baseline-audit.pyscripts/verify/tool-governance-gate.ps1scripts/verify/vgo-adapter-closure-gate.ps1scripts/verify/vgo-adapter-target-root-guard-gate.ps1scripts/verify/vibe-adaptive-routing-readiness-gate.ps1scripts/verify/vibe-ai-rerank-gate.ps1scripts/verify/vibe-bio-science-pack-consolidation-audit-gate.ps1scripts/verify/vibe-bom-frontmatter-gate.ps1scripts/verify/vibe-bootstrap-doctor-gate.ps1scripts/verify/vibe-browserops-gate.ps1scripts/verify/vibe-browserops-scorecard-gate.ps1scripts/verify/vibe-browserops-softrollout-gate.ps1scripts/verify/vibe-built-in-skill-governance-gate.ps1scripts/verify/vibe-candidate-quality-board-gate.ps1scripts/verify/vibe-canonical-entry-truth-gate.ps1scripts/verify/vibe-capability-catalog-gate.ps1scripts/verify/vibe-capability-dedup-gate.ps1scripts/verify/vibe-capability-lifecycle-gate.ps1scripts/verify/vibe-child-specialist-escalation-gate.ps1scripts/verify/vibe-code-quality-pack-consolidation-audit-gate.ps1scripts/verify/vibe-config-parity-gate.ps1scripts/verify/vibe-connector-action-ledger-gate.ps1scripts/verify/vibe-connector-admission-gate.ps1scripts/verify/vibe-connector-sandbox-simulation-gate.ps1scripts/verify/vibe-connector-scorecard-gate.ps1scripts/verify/vibe-context-retro-smoke.ps1scripts/verify/vibe-cross-host-degrade-contract-gate.ps1scripts/verify/vibe-cross-host-install-isolation-gate.ps1scripts/verify/vibe-cross-host-route-parity-gate.ps1scripts/verify/vibe-cross-plane-conflict-gate.ps1scripts/verify/vibe-cross-plane-replay-gate.ps1scripts/verify/vibe-cross-plane-task-contract-gate.ps1scripts/verify/vibe-cuda-kernel-overlay-gate.ps1scripts/verify/vibe-current-routing-contract-scan.ps1scripts/verify/vibe-current-routing-debt-gate.ps1scripts/verify/vibe-data-scale-overlay-gate.ps1scripts/verify/vibe-deep-discovery-gate.ps1scripts/verify/vibe-deep-discovery-scenarios.ps1scripts/verify/vibe-deep-extraction-pilot-gate.ps1scripts/verify/vibe-desktopops-replay-gate.ps1scripts/verify/vibe-desktopops-shadow-gate.ps1scripts/verify/vibe-desktopops-softrollout-gate.ps1scripts/verify/vibe-developer-entry-gate.ps1scripts/verify/vibe-discovery-intake-scorecard-gate.ps1scripts/verify/vibe-dist-manifest-gate.ps1scripts/verify/vibe-docling-contract-gate.ps1scripts/verify/vibe-docling-contract-v2-gate.ps1scripts/verify/vibe-document-asset-safety-gate.ps1scripts/verify/vibe-document-failure-taxonomy-gate.ps1scripts/verify/vibe-ecosystem-absorption-contract-gate.ps1scripts/verify/vibe-exploration-overlay-gate.ps1scripts/verify/vibe-external-corpus-gate.ps1scripts/verify/vibe-framework-interop-gate.ps1scripts/verify/vibe-gate-reliability-gate.ps1scripts/verify/vibe-generate-skills-lock.ps1scripts/verify/vibe-global-pack-consolidation-audit-gate.ps1scripts/verify/vibe-governance-entry-compression-gate.ps1scripts/verify/vibe-governed-runtime-contract-gate.ps1scripts/verify/vibe-gsd-overlay-gate.ps1scripts/verify/vibe-heartbeat-gate.ps1scripts/verify/vibe-host-adapter-contract-gate.ps1scripts/verify/vibe-host-capability-schema-gate.ps1scripts/verify/vibe-installed-runtime-freshness-gate.ps1scripts/verify/vibe-keyword-precision-audit.ps1scripts/verify/vibe-letta-contract-gate.ps1scripts/verify/vibe-letta-policy-conformance-gate.ps1scripts/verify/vibe-linux-pwsh-proof-gate.ps1scripts/verify/vibe-linux-router-no-pwsh-gate.ps1scripts/verify/vibe-llm-acceleration-overlay-gate.ps1scripts/verify/vibe-manual-apply-policy-gate.ps1scripts/verify/vibe-mem0-backend-gate.ps1scripts/verify/vibe-mem0-softrollout-gate.ps1scripts/verify/vibe-memory-governance-gate.ps1scripts/verify/vibe-memory-quality-eval-gate.ps1scripts/verify/vibe-memory-runtime-v3-gate.ps1scripts/verify/vibe-memory-tier-gate.ps1scripts/verify/vibe-mirror-edit-hygiene-gate.ps1scripts/verify/vibe-ml-lifecycle-overlay-gate.ps1scripts/verify/vibe-ml-skills-pruning-audit-gate.ps1scripts/verify/vibe-module-dispatch-closure-gate.ps1scripts/verify/vibe-nested-bundled-parity-gate.ps1scripts/verify/vibe-no-duplicate-canonical-surface-gate.ps1scripts/verify/vibe-no-self-introduced-fallback-gate.ps1scripts/verify/vibe-no-silent-fallback-contract-gate.ps1scripts/verify/vibe-node-zombie-gate.ps1scripts/verify/vibe-observability-gate.ps1scripts/verify/vibe-offline-hash-audit.ps1scripts/verify/vibe-offline-lock-parity-audit.ps1scripts/verify/vibe-offline-required-skills-audit.ps1scripts/verify/vibe-offline-skills-gate.ps1scripts/verify/vibe-openspec-governance-gate.ps1scripts/verify/vibe-openworld-runtime-eval-gate.ps1scripts/verify/vibe-operator-preview-contract-gate.ps1scripts/verify/vibe-ops-cockpit-gate.ps1scripts/verify/vibe-ops-dashboard-gate.ps1scripts/verify/vibe-orchestration-core-consolidation-gate.ps1scripts/verify/vibe-orchestration-core-hard-removal-gate.ps1scripts/verify/vibe-origin-provenance-gate.ps1scripts/verify/vibe-output-artifact-boundary-gate.ps1scripts/verify/vibe-output-fixture-migration-stage2-gate.ps1scripts/verify/vibe-pack-regression-matrix.ps1scripts/verify/vibe-pack-routing-smoke.ps1scripts/verify/vibe-pilot-scenarios.ps1scripts/verify/vibe-platform-doctor-parity-gate.ps1scripts/verify/vibe-platform-promotion-bundle.ps1scripts/verify/vibe-platform-support-contract-gate.ps1scripts/verify/vibe-promotion-board-gate.ps1scripts/verify/vibe-promotion-scorecard-gate.ps1scripts/verify/vibe-prompt-asset-boost-gate.ps1scripts/verify/vibe-prompt-intelligence-assets-gate.ps1scripts/verify/vibe-prompt-intelligence-eval-gate.ps1scripts/verify/vibe-prompt-intelligence-productization-gate.ps1scripts/verify/vibe-prompt-overlay-gate.ps1scripts/verify/vibe-proof-bundle-tracked-files-gate.ps1scripts/verify/vibe-python-clean-code-overlay-gate.ps1scripts/verify/vibe-quality-debt-overlay-gate.ps1scripts/verify/vibe-release-evidence-bundle-gate.ps1scripts/verify/vibe-release-install-runtime-coherence-gate.ps1scripts/verify/vibe-release-notes-quality-gate.ps1scripts/verify/vibe-release-train-v2-gate.ps1scripts/verify/vibe-release-truth-consistency-gate.ps1scripts/verify/vibe-release-truth-gate.ps1scripts/verify/vibe-remediation-foundation-gate.ps1scripts/verify/vibe-repo-cleanliness-gate.ps1scripts/verify/vibe-retrieval-overlay-gate.ps1scripts/verify/vibe-retro-context-regression-matrix.ps1scripts/verify/vibe-role-pack-governance-gate.ps1scripts/verify/vibe-role-pack-v2-gate.ps1scripts/verify/vibe-rollback-drill-gate.ps1scripts/verify/vibe-rollout-proposal-boundedness-gate.ps1scripts/verify/vibe-root-child-hierarchy-gate.ps1scripts/verify/vibe-router-ai-connectivity-gate.ps1scripts/verify/vibe-router-offline-degrade-contract-gate.ps1scripts/verify/vibe-router-provider-neutrality-gate.ps1scripts/verify/vibe-routing-local-owner-audit.ps1scripts/verify/vibe-routing-no-local-candidate-audit.ps1scripts/verify/vibe-routing-probe-research.ps1scripts/verify/vibe-routing-requested-skill-audit.ps1scripts/verify/vibe-routing-smoke.ps1scripts/verify/vibe-routing-stability-gate.ps1scripts/verify/vibe-routing-terminology-hard-cleanup-scan.ps1scripts/verify/vibe-runtime-boundary-gate.ps1scripts/verify/vibe-runtime-execution-proof-gate.ps1scripts/verify/vibe-skill-contract-parity-gate.ps1scripts/verify/vibe-skill-contract-schema-gate.ps1scripts/verify/vibe-skill-harvest-v2-gate.ps1scripts/verify/vibe-skill-index-routing-audit.ps1scripts/verify/vibe-soft-migration-practice.ps1scripts/verify/vibe-subagent-handoff-gate.ps1scripts/verify/vibe-system-design-overlay-gate.ps1scripts/verify/vibe-third-party-disclosure-parity-gate.ps1scripts/verify/vibe-uninstall-coherence-gate.ps1scripts/verify/vibe-universalization-no-regression-gate.ps1scripts/verify/vibe-upstream-corpus-manifest-gate.ps1scripts/verify/vibe-upstream-lock-coverage-gate.ps1scripts/verify/vibe-upstream-mirror-freshness-gate.ps1scripts/verify/vibe-upstream-reaudit-matrix-gate.ps1scripts/verify/vibe-upstream-value-ops-gate.ps1scripts/verify/vibe-version-consistency-gate.ps1scripts/verify/vibe-version-packaging-gate.ps1scripts/verify/vibe-wave121-upstream-mapping-gate.ps1scripts/verify/vibe-wave124-ops-cockpit-v2-gate.ps1scripts/verify/vibe-wave125-gate-family-convergence-gate.ps1scripts/verify/vibe-wave40-63-board-gate.ps1scripts/verify/vibe-wave64-82-closure-gate.ps1scripts/verify/vibe-wave83-100-closure-gate.ps1scripts/verify/vibe-workflow-acceptance-gate.ps1scripts/verify/watch-portfolio-gate.ps1scripts/verify/wave15-18-consistency-gate.ps1tests/__init__.pytests/_python_source_roots.pytests/bash_test_support.pytests/conftest.pytests/contract/test_adapter_descriptor_contract.pytests/contract/test_install_ledger_contract.pytests/contract/test_repo_layout_contract.pytests/contract/test_runtime_packet_contract.pytests/contract/test_vibe_discoverable_entry_contract.pytests/e2e/test_distribution_build.pytests/integration/test_adapter_closure_gate_registry_cutover.pytests/integration/test_adapter_registry_query_delegation.pytests/integration/test_adapter_registry_single_source.pytests/integration/test_adapter_sdk_registry_cutover.pytests/integration/test_bootstrap_entrypoint_registry_cutover.pytests/integration/test_bootstrap_host_catalog_shared_contract.pytests/integration/test_canonical_vibe_truth_gate.pytests/integration/test_catalog_contract_consumption.pytests/integration/test_check_entrypoint_registry_cutover.pytests/integration/test_check_shell_bootstrap_doctor_counting.pytests/integration/test_cli_installer_core_cutover.pytests/integration/test_cli_main_infra_separation.pytests/integration/test_cli_runtime_entrypoint_contract_cutover.pytests/integration/test_cli_verify_runtime_contract_cutover.pytests/integration/test_codex_install_prompt_discoverability.pytests/integration/test_dist_manifest_generation.pytests/integration/test_frontmatter_gate_runtime_contract_cutover.pytests/integration/test_host_capability_matrix_single_source.pytests/integration/test_host_global_bootstrap_shell_lifecycle.pytests/integration/test_install_rerun_matrix.pytests/integration/test_installed_runtime_contract_cutover.pytests/integration/test_mirror_topology_contract_cutover.pytests/integration/test_multi_host_real_host_root_docs.pytests/integration/test_new_origin_record_vendor_guard.pytests/integration/test_platform_doctor_parity_gate_single_source.pytests/integration/test_powershell_compat_shim_cutover.pytests/integration/test_powershell_installed_runtime_contract_bridge.pytests/integration/test_powershell_wrapper_host_validation_dedupe.pytests/integration/test_proof_bundle_manifest_contract.pytests/integration/test_public_install_uninstall_guidance.pytests/integration/test_pwsh_wrapper_contract.pytests/integration/test_real_canonical_entry_bounded_stop.pytests/integration/test_release_cut_gate_contract_cutover.pytests/integration/test_resolver_shim_delegation.pytests/integration/test_router_core_cutover.pytests/integration/test_router_keyword_inference.pytests/integration/test_runtime_common_registry_cutover.pytests/integration/test_runtime_config_manifest_roles.pytests/integration/test_runtime_core_packaging_roles.pytests/integration/test_runtime_payload_dependency_coverage.pytests/integration/test_runtime_script_manifest_roles.pytests/integration/test_runtime_surface_contract_cutover.pytests/integration/test_shared_run_artifact_contract.pytests/integration/test_shell_frontend_windows_handoff_contract.pytests/integration/test_shell_wrapper_contract.pytests/integration/test_target_root_guard_single_source.pytests/integration/test_verification_core_cutover.pytests/integration/test_verification_runtime_entrypoint_contract_cutover.pytests/integration/test_verification_scenario_runner.pytests/integration/test_verify_gate_single_source_cutover.pytests/integration/test_vibe_skill_bootstrap_contract.pytests/integration/test_vibe_wrapper_shim_contract.pytests/issue_167_runtime_surfaces.pytests/runtime_neutral/live_contract_fixtures.pytests/runtime_neutral/test_active_consultation_simplification.pytests/runtime_neutral/test_agent_led_skill_execution_language.pytests/runtime_neutral/test_agent_skill_organization_contract.pytests/runtime_neutral/test_apps_surface_hygiene.pytests/runtime_neutral/test_bash_test_support.pytests/runtime_neutral/test_bio_science_boundary_hardening.pytests/runtime_neutral/test_bio_science_direct_owner_routing.pytests/runtime_neutral/test_bootstrap_doctor.pytests/runtime_neutral/test_bootstrap_shell_target_root_guard.pytests/runtime_neutral/test_bundled_runtime_mirror.pytests/runtime_neutral/test_bundled_skill_governance_gate.pytests/runtime_neutral/test_check_installed_runtime_root.pytests/runtime_neutral/test_check_shell_target_root_guard.pytests/runtime_neutral/test_claude_preview_scaffold.pytests/runtime_neutral/test_codex_memory_user_simulation.pytests/runtime_neutral/test_coherence_gate.pytests/runtime_neutral/test_conftest_subprocess_run.pytests/runtime_neutral/test_cross_host_memory_identity.pytests/runtime_neutral/test_current_routing_contract_scan.pytests/runtime_neutral/test_current_routing_docs_entrypoint.pytests/runtime_neutral/test_cursor_managed_preview.pytests/runtime_neutral/test_custom_admission_bridge.pytests/runtime_neutral/test_discoverable_wrapper_host_visibility.pytests/runtime_neutral/test_docs_readme_encoding.pytests/runtime_neutral/test_docs_research_publishing_boundary_routing.pytests/runtime_neutral/test_docs_source_neutral_links.pytests/runtime_neutral/test_document_chain_layering_contract.pytests/runtime_neutral/test_forbidden_mcp_installation_contract.pytests/runtime_neutral/test_freshness_gate.pytests/runtime_neutral/test_frontmatter_gate_scope_activation.pytests/runtime_neutral/test_generated_nested_bundled.pytests/runtime_neutral/test_global_instruction_bootstrap_runtime.pytests/runtime_neutral/test_governed_runtime_bridge.pytests/runtime_neutral/test_governed_runtime_lineage.pytests/runtime_neutral/test_governed_templates.pytests/runtime_neutral/test_install_generated_nested_bundled.pytests/runtime_neutral/test_install_profile_differentiation.pytests/runtime_neutral/test_installed_host_runtime_simulation.pytests/runtime_neutral/test_installed_runtime_policy_remap.pytests/runtime_neutral/test_installed_runtime_scripts.pytests/runtime_neutral/test_installed_runtime_uninstall.pytests/runtime_neutral/test_intent_contract_host_fidelity.pytests/runtime_neutral/test_l_xl_agent_execution_handoff.pytests/runtime_neutral/test_live_document_contract_gate.pytests/runtime_neutral/test_llm_acceleration_overlay_gate.pytests/runtime_neutral/test_llm_acceleration_overlay_provider_paths.pytests/runtime_neutral/test_memory_ingest_noise_filters.pytests/runtime_neutral/test_memory_progressive_disclosure.pytests/runtime_neutral/test_memory_runtime_activation.pytests/runtime_neutral/test_module_skill_dispatch_safety.pytests/runtime_neutral/test_non_code_task_classification.pytests/runtime_neutral/test_offline_skills_gate.pytests/runtime_neutral/test_openclaw_runtime_core.pytests/runtime_neutral/test_opencode_managed_preview.pytests/runtime_neutral/test_opencode_preview_parity.pytests/runtime_neutral/test_outputs_boundary_migration.pytests/runtime_neutral/test_pack_manifest_role_contract.pytests/runtime_neutral/test_powershell_entrypoint_help.pytests/runtime_neutral/test_python_validation_contract.pytests/runtime_neutral/test_readme_benchmark_results.pytests/runtime_neutral/test_readme_install_cta_assets.pytests/runtime_neutral/test_readme_preface_assets.pytests/runtime_neutral/test_readme_star_history_assets.pytests/runtime_neutral/test_release_cut_operator.pytests/runtime_neutral/test_release_notes_quality.pytests/runtime_neutral/test_release_surface.pytests/runtime_neutral/test_release_truth_gate.pytests/runtime_neutral/test_repo_cleanliness_policy.pytests/runtime_neutral/test_repo_config_contract.pytests/runtime_neutral/test_retired_agent_execution_surfaces.pytests/runtime_neutral/test_root_child_hierarchy_bridge.pytests/runtime_neutral/test_router_ai_connectivity_probe.pytests/runtime_neutral/test_router_authority_safe_fallback.pytests/runtime_neutral/test_router_authority_safe_fallback_contract.pytests/runtime_neutral/test_router_bridge.pytests/runtime_neutral/test_router_ownership_docs_contract.pytests/runtime_neutral/test_runtime_authority_docs_contract.pytests/runtime_neutral/test_runtime_contract_schema.pytests/runtime_neutral/test_runtime_contracts.pytests/runtime_neutral/test_runtime_delivery_acceptance.pytests/runtime_neutral/test_runtime_entrypoint_helper.pytests/runtime_neutral/test_runtime_route_output_shape.pytests/runtime_neutral/test_runtime_summary_acceptance_refresh.pytests/runtime_neutral/test_scientific_visualization_latex_routing.pytests/runtime_neutral/test_shell_entrypoint_compatibility.pytests/runtime_neutral/test_simple_install_docs_contract.pytests/runtime_neutral/test_simple_powershell_installer_wrappers.pytests/runtime_neutral/test_simplified_skill_routing_contract.pytests/runtime_neutral/test_skill_authority_parity.pytests/runtime_neutral/test_skill_candidate_execution_safety.pytests/runtime_neutral/test_structured_bounded_reentry_continuation.pytests/runtime_neutral/test_test_baseline_audit.pytests/runtime_neutral/test_uninstall_vgo_adapter.pytests/runtime_neutral/test_verify_docs_contract.pytests/runtime_neutral/test_vibe_routing_chaos_audit_fixture.pytests/runtime_neutral/test_vibe_upgrade_reminder.pytests/runtime_neutral/test_windows_setup_helpers.pytests/runtime_neutral/test_windsurf_runtime_core.pytests/runtime_neutral/test_workflow_acceptance_runner.pytests/runtime_neutral/test_workspace_shared_memory_plane.pytests/unit/test_adapter_registry_support.pytests/unit/test_adapter_sdk.pytests/unit/test_artifact_receipt_sync.pytests/unit/test_canonical_entry_boundary.pytests/unit/test_canonical_vibe_contract.pytests/unit/test_canonical_vibe_entry_launcher.pytests/unit/test_codex_plugin_inventory.pytests/unit/test_delegated_lane_contract.pytests/unit/test_discoverable_entry_surface.pytests/unit/test_discoverable_wrapper_task_fidelity.pytests/unit/test_discoverable_wrappers.pytests/unit/test_entry_root_guard.pytests/unit/test_external_skill_catalog.pytests/unit/test_external_skill_selection.pytests/unit/test_gate_engine.pytests/unit/test_global_instruction_merge.pytests/unit/test_host_closure.pytests/unit/test_host_launch_receipt.pytests/unit/test_host_skill_roots.pytests/unit/test_install_runtime_cleanup.pytests/unit/test_installed_runtime_contract.pytests/unit/test_installer_adapter_registry_target_roots.pytests/unit/test_installer_ledger_service.pytests/unit/test_installer_opencode_guidance_payload.pytests/unit/test_installer_profile_inventory.pytests/unit/test_kernel_boundary_demotion_matrix.pytests/unit/test_kernel_text_tokens.pytests/unit/test_live_document_gate.pytests/unit/test_live_governance_contract.pytests/unit/test_local_installed_skill_routing.pytests/unit/test_local_kernel_execution.pytests/unit/test_local_kernel_planning.pytests/unit/test_local_kernel_resume.pytests/unit/test_local_skill_index.pytests/unit/test_materializer_path_safety.pytests/unit/test_materializer_runtime_noise.pytests/unit/test_mirror_topology_contract.pytests/unit/test_module_execution_contract.pytests/unit/test_powershell_process_tree.pytests/unit/test_proof_publication.pytests/unit/test_runtime_compatibility_exit.pytests/unit/test_runtime_contracts_helper.pytests/unit/test_runtime_entry_locator.pytests/unit/test_runtime_entry_policy.pytests/unit/test_runtime_grade_intent.pytests/unit/test_runtime_packaging_resolver.pytests/unit/test_runtime_planning.pytests/unit/test_runtime_router.pytests/unit/test_runtime_stage_machine.pytests/unit/test_runtime_stage_stop.pytests/unit/test_runtime_summary.pytests/unit/test_runtime_support.pytests/unit/test_runtime_surface_contract.pytests/unit/test_runtime_task_intent.pytests/unit/test_runtime_truth.pytests/unit/test_simple_skill_installer.pytests/unit/test_skill_authority.pytests/unit/test_skill_cache_routing.pytests/unit/test_skill_resources.pytests/unit/test_uninstall_service.pytests/unit/test_verification_repo_root.pytests/unit/test_verify_surface_default.pytests/unit/test_vgo_cli_commands.pytests/unit/test_vgo_cli_core_bridge.pytests/unit/test_vgo_cli_external.pytests/unit/test_vgo_cli_infra_split.pytests/unit/test_vgo_cli_install_gates.pytests/unit/test_vgo_cli_install_support.pytests/unit/test_vgo_cli_installer_bridge.pytests/unit/test_vgo_cli_process.pytests/unit/test_vgo_cli_repo.pytests/unit/test_vgo_cli_upgrade_service.pytests/unit/test_vgo_cli_upgrade_state.pytests/unit/test_vgo_verify_repo.pytests/unit/test_vibe_skill_entry_contract.pytests/unit/test_vibe_task_prompt_fidelity_contract.pyuninstall.ps1uninstall.shupdate.ps1update.shvgo_cli/__init__.pyvgo_python_source_roots.py
Files
.gitattributesasset382 bytes.github/workflows/vco-gates.ymlasset10,490 bytes.github/workflows/vco-optional-audits.ymlasset4,844 bytes.github/workflows/vco-release-proof.ymlasset6,028 bytes.gitignoreasset1,389 bytesCONTEXT.mddoc3,481 bytesCONTRIBUTING.mddoc8,386 bytesLICENSEasset11,362 bytesNOTICEasset525 bytesREADME.mddoc27,232 bytesREADME.zh.mddoc25,521 bytesSKILL.mdcore17,637 bytesSKILL.mdcore17,637 bytesSKILL.mdcore17,637 bytesSKILL.mdcore17,637 bytesSKILL.mdcore17,637 bytesTHIRD_PARTY_LICENSES.mddoc5,661 bytes_python_source_roots.pyruns115 bytesadapters/README.mddoc1,729 bytesadapters/claude-code/closure.jsonasset1,639 bytesadapters/claude-code/host-profile.jsonasset2,648 bytesadapters/claude-code/platform-linux.jsonasset1,654 bytesadapters/claude-code/platform-macos.jsonasset1,271 bytesadapters/claude-code/platform-windows.jsonasset1,298 bytesadapters/claude-code/settings-map.jsonasset972 bytesadapters/codex/closure.jsonasset1,680 bytesadapters/codex/host-profile.jsonasset2,311 bytesadapters/codex/platform-linux.jsonasset1,423 bytesadapters/codex/platform-macos.jsonasset374 bytesadapters/codex/platform-windows.jsonasset528 bytesadapters/codex/settings-map.jsonasset812 bytesadapters/cursor/closure.jsonasset1,661 bytesadapters/cursor/host-profile.jsonasset1,906 bytesadapters/cursor/platform-linux.jsonasset331 bytesadapters/cursor/platform-macos.jsonasset291 bytesadapters/cursor/platform-windows.jsonasset364 bytesadapters/cursor/settings-map.jsonasset623 bytesadapters/generic/closure.jsonasset682 bytesadapters/generic/host-profile.jsonasset1,163 bytesadapters/generic/settings-map.jsonasset198 bytesadapters/index.jsonasset6,903 bytesadapters/openclaw/closure.jsonasset1,827 bytesadapters/openclaw/host-profile.jsonasset1,935 bytesadapters/openclaw/platform-linux.jsonasset1,011 bytesadapters/openclaw/platform-macos.jsonasset609 bytesadapters/openclaw/platform-windows.jsonasset617 bytesadapters/openclaw/settings-map.jsonasset495 bytesadapters/opencode/closure.jsonasset1,994 bytesadapters/opencode/host-profile.jsonasset2,586 bytesadapters/opencode/platform-linux.jsonasset582 bytesadapters/opencode/platform-macos.jsonasset497 bytesadapters/opencode/platform-windows.jsonasset558 bytesadapters/opencode/settings-map.jsonasset1,501 bytesadapters/windsurf/closure.jsonasset1,864 bytesadapters/windsurf/host-profile.jsonasset1,952 bytesadapters/windsurf/platform-linux.jsonasset948 bytesadapters/windsurf/platform-macos.jsonasset609 bytesadapters/windsurf/platform-windows.jsonasset617 bytesadapters/windsurf/settings-map.jsonasset580 bytesagents/templates/debugger.mddoc323 bytesagents/templates/planner.mddoc313 bytesagents/templates/reviewer.mddoc331 bytesagents/templates/security-reviewer.mddoc341 bytesapps/.gitkeepasset0 bytesapps/vgo-cli/pyproject.tomlasset236 bytesapps/vgo-cli/src/vgo_cli/__init__.pyruns19 bytesapps/vgo-cli/src/vgo_cli/commands.pyruns16,718 bytesapps/vgo-cli/src/vgo_cli/core_bridge.pyruns2,724 bytesapps/vgo-cli/src/vgo_cli/errors.pyruns692 bytesapps/vgo-cli/src/vgo_cli/external.pyruns2,751 bytesapps/vgo-cli/src/vgo_cli/hosts.pyruns3,921 bytesapps/vgo-cli/src/vgo_cli/install_gates.pyruns2,961 bytesapps/vgo-cli/src/vgo_cli/install_support.pyruns3,780 bytesapps/vgo-cli/src/vgo_cli/installer_bridge.pyruns864 bytesapps/vgo-cli/src/vgo_cli/main.pyruns7,784 bytesapps/vgo-cli/src/vgo_cli/output.pyruns647 bytesapps/vgo-cli/src/vgo_cli/process.pyruns9,756 bytesapps/vgo-cli/src/vgo_cli/repo.pyruns3,094 bytesapps/vgo-cli/src/vgo_cli/skill_surface.pyruns1,518 bytesapps/vgo-cli/src/vgo_cli/upgrade_service.pyruns12,590 bytesapps/vgo-cli/src/vgo_cli/upgrade_state.pyruns4,110 bytesapps/vgo-cli/src/vgo_cli/version_reminder.pyruns2,235 bytesapps/vgo-cli/src/vgo_cli/workspace.pyruns435 bytesbundled/skills/.system/.codex-system-skills.markerasset17 bytesbundled/skills/shared-templates/unified-workflow-report.mddoc1,749 bytescheck.ps1runs1,621 bytescheck.shruns724 bytescommands/vibe-implement.mddoc229 bytescommands/vibe-review.mddoc196 bytescommands/vibe.mddoc319 bytesconfig/adapter-registry.jsonasset6,903 bytesconfig/adaptive-routing-eval-governance.jsonasset2,702 bytesconfig/agency-overlays.jsonasset8,067 bytesconfig/ai-rerank-policy.jsonasset1,502 bytesconfig/benchmark-results.jsonasset1,343 bytesconfig/browserops-provider-policy.jsonasset3,165 bytesconfig/browserops-scorecard.jsonasset3,197 bytesconfig/bundled-skill-governance-policy.jsonasset1,334 bytesconfig/bundled-skill-tier-policy.jsonasset1,391 bytesconfig/candidate-curation-policy.jsonasset38,770 bytesconfig/candidate-quality-board.jsonasset1,380 bytesconfig/candidate-watch-decisions.jsonasset5,589 bytesconfig/capability-catalog.jsonasset41,519 bytesconfig/capability-dedup-governance.jsonasset6,431 bytesconfig/capability-lifecycle-policy.jsonasset470 bytesconfig/closure-overlay.jsonasset2,263 bytesconfig/connector-admission-policy.jsonasset3,121 bytesconfig/connector-provider-policy.jsonasset4,185 bytesconfig/connector-sandbox-policy.jsonasset495 bytesconfig/cross-plane-conflict-policy.jsonasset3,217 bytesconfig/cuda-kernel-overlay.jsonasset5,007 bytesconfig/current-routing-debt-erasure.jsonasset4,861 bytesconfig/daily-dialectic-guard.jsonasset642 bytesconfig/data-scale-overlay.jsonasset5,528 bytesconfig/deep-discovery-policy.jsonasset5,959 bytesconfig/dependency-map.jsonasset1,737 bytesconfig/desktopops-shadow-policy.jsonasset2,259 bytesconfig/dialectic-team-policy.jsonasset807 bytesconfig/discovery-intake-policy.jsonasset552 bytesconfig/distribution-manifest-sources.jsonasset43,615 bytesconfig/distribution-tiers.jsonasset1,201 bytesconfig/docling-provider-policy.jsonasset1,933 bytesconfig/document-failure-taxonomy.jsonasset1,073 bytesconfig/egress-allowlist.jsonasset730 bytesconfig/eval-slicing-policy.jsonasset3,896 bytesconfig/execution-context-status.jsonasset673 bytesconfig/exploration-domain-map.jsonasset2,115 bytesconfig/exploration-intent-profiles.jsonasset2,545 bytesconfig/exploration-policy.jsonasset1,376 bytesconfig/fallback-governance.jsonasset961 bytesconfig/forbidden-mcp-policy.jsonasset680 bytesconfig/framework-interop-overlay.jsonasset2,982 bytesconfig/frontmatter-integrity-policy.jsonasset2,023 bytesconfig/gate-reliability-policy.jsonasset780 bytesconfig/gitnexus-overlays.jsonasset4,595 bytesconfig/global-bootstrap/claude-code-vibe-bootstrap.mddoc811 bytesconfig/global-bootstrap/codex-vibe-bootstrap.mddoc805 bytesconfig/global-bootstrap/opencode-vibe-bootstrap.mddoc811 bytesconfig/governance-family-index.jsonasset2,633 bytesconfig/gsd-overlay.jsonasset2,601 bytesconfig/heartbeat-policy.jsonasset2,551 bytesconfig/implementation-guardrails.jsonasset944 bytesconfig/index.mddoc2,468 bytesconfig/kernel-boundary-demotion-matrix.jsonasset13,129 bytesconfig/letta-governance-contract.jsonasset385 bytesconfig/live-document-contract.jsonasset6,601 bytesconfig/llm-acceleration-policy.jsonasset2,879 bytesconfig/manual-apply-policy.jsonasset461 bytesconfig/mem0-backend-policy.jsonasset549 bytesconfig/memory-backend-adapters.jsonasset1,762 bytesconfig/memory-disclosure-policy.jsonasset986 bytesconfig/memory-governance.jsonasset6,082 bytesconfig/memory-ingest-policy.jsonasset1,142 bytesconfig/memory-quality-scorecard.jsonasset1,244 bytesconfig/memory-retrieval-budget-policy.jsonasset471 bytesconfig/memory-runtime-v3-policy.jsonasset2,642 bytesconfig/memory-stage-activation-policy.jsonasset2,585 bytesconfig/memory-tier-router.jsonasset748 bytesconfig/messy-real-task-corpus.jsonasset2,485 bytesconfig/ml-lifecycle-overlay.jsonasset5,717 bytesconfig/observability-policy.jsonasset2,893 bytesconfig/official-runtime-main-chain-policy.jsonasset2,795 bytesconfig/opencode/agents/vibe-implement.mddoc399 bytesconfig/opencode/agents/vibe-plan.mddoc543 bytesconfig/opencode/agents/vibe-review.mddoc388 bytesconfig/opencode/commands/vibe-implement.mddoc382 bytesconfig/opencode/commands/vibe-review.mddoc336 bytesconfig/opencode/commands/vibe.mddoc202 bytesconfig/opencode/opencode.json.exampleasset556 bytesconfig/openspec-policy.jsonasset4,356 bytesconfig/openworld-runtime-eval-policy.jsonasset637 bytesconfig/operator-preview-contract.jsonasset4,804 bytesconfig/ops-cockpit-panel-contract.jsonasset896 bytesconfig/outputs-boundary-policy.jsonasset856 bytesconfig/pack-manifest.jsonasset40,419 bytesconfig/phase-cleanup-policy.jsonasset2,386 bytesconfig/plan-execution-policy.jsonasset1,115 bytesconfig/platform-support-policy.jsonasset1,565 bytesconfig/plugins-manifest.codex.jsonasset1,835 bytesconfig/powershell-host-policy.jsonasset170 bytesconfig/process-health-policy.jsonasset953 bytesconfig/process-ledger-policy.jsonasset746 bytesconfig/project-delivery-acceptance-contract.jsonasset2,099 bytesconfig/promotion-board.jsonasset17,498 bytesconfig/prompt-asset-boost.jsonasset1,865 bytesconfig/prompt-intelligence-policy.jsonasset347 bytesconfig/prompt-intelligence-scorecard.jsonasset731 bytesconfig/prompt-overlay.jsonasset3,269 bytesconfig/proof-class-registry.jsonasset1,778 bytesconfig/python-clean-code-overlay.jsonasset4,260 bytesconfig/python-validation-targets.txtdoc972 bytesconfig/quality-debt-overlay.jsonasset2,755 bytesconfig/repo-cleanliness-policy.jsonasset4,712 bytesconfig/requirement-doc-policy.jsonasset1,607 bytesconfig/retrieval-intent-profiles.jsonasset6,991 bytesconfig/retrieval-policy.jsonasset1,088 bytesconfig/retrieval-rerank-weights.jsonasset583 bytesconfig/retrieval-source-registry.jsonasset2,461 bytesconfig/role-pack-policy.jsonasset16,985 bytesconfig/role-pack-scorecard.jsonasset809 bytesconfig/rollout-proposal-policy.jsonasset342 bytesconfig/router-model-governance.jsonasset2,469 bytesconfig/router-provider-defaults.jsonasset805 bytesconfig/router-provider-registry.jsonasset1,998 bytesconfig/router-thresholds.jsonasset328 bytesconfig/routing-terminology-hard-cleanup.jsonasset6,024 bytesconfig/ruc-nlpir-overlays.jsonasset2,330 bytesconfig/ruc-nlpir-runtime.jsonasset2,030 bytesconfig/runtime-config-manifest.jsonasset8,040 bytesconfig/runtime-contract.jsonasset2,327 bytesconfig/runtime-core-packaging.full.jsonasset3,130 bytesconfig/runtime-core-packaging.jsonasset5,064 bytesconfig/runtime-core-packaging.minimal.jsonasset3,102 bytesconfig/runtime-input-packet-policy.jsonasset4,015 bytesconfig/runtime-modes.jsonasset544 bytesconfig/runtime-script-manifest.jsonasset11,341 bytesconfig/secrets-policy.jsonasset1,080 bytesconfig/settings.template.claude.jsonasset1,156 bytesconfig/settings.template.codex.jsonasset246 bytesconfig/skill-alias-map.jsonasset469 bytesconfig/skill-execution-safety-policy.jsonasset2,618 bytesconfig/skill-harvest-policy.jsonasset514 bytesconfig/skill-intake-priority.jsonasset1,833 bytesconfig/skill-metadata-policy.jsonasset15,584 bytesconfig/subagent-handoff-policy.jsonasset463 bytesconfig/system-design-overlay.jsonasset6,097 bytesconfig/test-baseline-policy.jsonasset5,220 bytesconfig/tool-registry.jsonasset3,841 bytesconfig/tool-risk-tiers.jsonasset1,999 bytesconfig/turix-cua-overlays.jsonasset2,780 bytesconfig/upstream-corpus-manifest.jsonasset20,875 bytesconfig/upstream-lock.jsonasset26,768 bytesconfig/upstream-reaudit-policy.jsonasset514 bytesconfig/upstream-source-aliases.jsonasset2,611 bytesconfig/upstream-value-ops-board.jsonasset2,362 bytesconfig/vco-overlays.jsonasset1,393 bytesconfig/version-governance.jsonasset4,232 bytesconfig/vibe-entry-surfaces.jsonasset513 bytesconfig/watch-lane-priority-bands.jsonasset1,635 bytesconfig/wave121-140-gate-manifest.jsonasset8,215 bytesconfig/wave40-63-execution-board.jsonasset8,687 bytesconfig/wave64-82-planning-board.jsonasset12,881 bytesconfig/wave83-100-execution-status.jsonasset1,718 bytesconfig/wave83-100-gate-manifest.jsonasset21,809 bytesconfig/wave83-100-planning-board.jsonasset14,487 bytesconfig/workspace-memory-plane.jsonasset1,008 bytescore/README.mddoc746 bytescore/skill-contracts/index.jsonasset1,103 bytescore/skill-contracts/v1/brainstorming.jsonasset516 bytescore/skill-contracts/v1/code-reviewer.jsonasset516 bytescore/skill-contracts/v1/subagent-driven-development.jsonasset544 bytescore/skill-contracts/v1/systematic-debugging.jsonasset530 bytescore/skill-contracts/v1/tdd-guide.jsonasset508 bytescore/skill-contracts/v1/vibe.jsonasset527 bytescore/skill-contracts/v1/writing-plans.jsonasset516 bytescore/skills/brainstorming/compatibility.jsonasset341 bytescore/skills/brainstorming/instruction.mddoc346 bytescore/skills/brainstorming/skill.jsonasset462 bytescore/skills/code-reviewer/compatibility.jsonasset378 bytescore/skills/code-reviewer/instruction.mddoc302 bytescore/skills/code-reviewer/skill.jsonasset478 bytescore/skills/subagent-driven-development/compatibility.jsonasset377 bytescore/skills/subagent-driven-development/instruction.mddoc360 bytescore/skills/subagent-driven-development/skill.jsonasset551 bytescore/skills/systematic-debugging/compatibility.jsonasset351 bytescore/skills/systematic-debugging/instruction.mddoc320 bytescore/skills/systematic-debugging/skill.jsonasset525 bytescore/skills/tdd-guide/compatibility.jsonasset350 bytescore/skills/tdd-guide/instruction.mddoc292 bytescore/skills/tdd-guide/skill.jsonasset452 bytescore/skills/vibe/compatibility.jsonasset561 bytescore/skills/vibe/instruction.mddoc5,488 bytescore/skills/vibe/skill.jsonasset494 bytescore/skills/writing-plans/compatibility.jsonasset335 bytescore/skills/writing-plans/instruction.mddoc337 bytescore/skills/writing-plans/skill.jsonasset485 bytesdist/README.mddoc3,508 bytesdist/core/manifest.jsonasset2,785 bytesdist/host-claude-code/manifest.jsonasset4,294 bytesdist/host-codex/manifest.jsonasset4,044 bytesdist/host-cursor/manifest.jsonasset3,395 bytesdist/host-openclaw/manifest.jsonasset3,673 bytesdist/host-opencode/manifest.jsonasset4,800 bytesdist/host-windsurf/manifest.jsonasset3,619 bytesdist/manifests/vibeskills-claude-code.jsonasset4,065 bytesdist/manifests/vibeskills-codex.jsonasset3,959 bytesdist/manifests/vibeskills-core.jsonasset3,132 bytesdist/manifests/vibeskills-cursor.jsonasset3,470 bytesdist/manifests/vibeskills-generic.jsonasset2,768 bytesdist/manifests/vibeskills-openclaw.jsonasset3,858 bytesdist/manifests/vibeskills-opencode.jsonasset4,105 bytesdist/manifests/vibeskills-windsurf.jsonasset3,852 bytesdist/official-runtime/manifest.jsonasset4,467 bytesdocs/README.mddoc2,362 bytesdocs/adr/0001-externalize-governance-history.mddoc898 bytesdocs/architecture.mddoc5,083 bytesdocs/archive/config/xl-operator-checkpoints.jsonasset2,507 bytesdocs/assets/install-cta-cn-dark.svgasset10,854 bytesdocs/assets/install-cta-cn-light.svgasset10,854 bytesdocs/assets/install-cta-en-dark.svgasset6,334 bytesdocs/assets/install-cta-en-light.svgasset6,334 bytesdocs/assets/readme-chapter-01-cn-dark.svgasset94,405 bytesdocs/assets/readme-chapter-01-cn-light.svgasset94,405 bytesdocs/assets/readme-chapter-01-en-dark.svgasset33,422 bytesdocs/assets/readme-chapter-01-en-light.svgasset33,422 bytesdocs/assets/readme-chapter-02-cn-dark.svgasset64,887 bytesdocs/assets/readme-chapter-02-cn-light.svgasset64,887 bytesdocs/assets/readme-chapter-02-en-dark.svgasset23,117 bytesdocs/assets/readme-chapter-02-en-light.svgasset23,117 bytesdocs/assets/readme-chapter-03-cn-dark.svgasset44,871 bytesdocs/assets/readme-chapter-03-cn-light.svgasset44,871 bytesdocs/assets/readme-chapter-03-en-dark.svgasset12,531 bytesdocs/assets/readme-chapter-03-en-light.svgasset12,531 bytesdocs/assets/readme-chapter-04-cn-dark.svgasset82,155 bytesdocs/assets/readme-chapter-04-cn-light.svgasset82,155 bytesdocs/assets/readme-chapter-04-en-dark.svgasset18,993 bytesdocs/assets/readme-chapter-04-en-light.svgasset18,993 bytesdocs/assets/readme-chapter-05-cn-dark.svgasset24,415 bytesdocs/assets/readme-chapter-05-cn-light.svgasset24,415 bytesdocs/assets/readme-chapter-05-en-dark.svgasset7,843 bytesdocs/assets/readme-chapter-05-en-light.svgasset7,843 bytesdocs/assets/readme-preface-cn-dark.svgasset443,573 bytesdocs/assets/readme-preface-cn-light.svgasset443,573 bytesdocs/assets/readme-preface-cn-mobile-dark.svgasset444,883 bytesdocs/assets/readme-preface-cn-mobile-light.svgasset444,883 bytesdocs/assets/readme-preface-en-dark.svgasset86,637 bytesdocs/assets/readme-preface-en-light.svgasset86,637 bytesdocs/assets/readme-preface-en-mobile-dark.svgasset87,375 bytesdocs/assets/readme-preface-en-mobile-light.svgasset87,375 bytesdocs/assets/readme-preface-v2-cn-dark.svgasset443,573 bytesdocs/assets/readme-preface-v2-cn-light.svgasset443,573 bytesdocs/assets/readme-preface-v2-cn-mobile-dark.svgasset444,883 bytesdocs/assets/readme-preface-v2-cn-mobile-light.svgasset444,883 bytesdocs/assets/readme-preface-v2-en-dark.svgasset86,637 bytesdocs/assets/readme-preface-v2-en-light.svgasset86,637 bytesdocs/assets/readme-preface-v2-en-mobile-dark.svgasset87,375 bytesdocs/assets/readme-preface-v2-en-mobile-light.svgasset87,375 bytesdocs/assets/readme-tagline-cn-dark.svgasset121,955 bytesdocs/assets/readme-tagline-cn-light.svgasset121,955 bytesdocs/assets/readme-tagline-en-dark.svgasset74,505 bytesdocs/assets/readme-tagline-en-light.svgasset74,505 bytesdocs/assets/readme-wave-divider-dark.svgasset551 bytesdocs/assets/readme-wave-divider-light.svgasset551 bytesdocs/assets/readme-wordmark-dark.svgasset5,802 bytesdocs/assets/readme-wordmark-light.svgasset5,802 bytesdocs/assets/skillsbench-resource-use.pngasset232,126 bytesdocs/assets/skillsbench-task-outcomes.pngasset195,305 bytesdocs/assets/vibeskills-harness-overview-cn.svgasset9,144 bytesdocs/assets/vibeskills-harness-overview-en.svgasset9,028 bytesdocs/assets/vibeskills-skill-orchestration-cn.pngasset1,137,447 bytesdocs/assets/vibeskills-skill-orchestration-en.pngasset1,328,704 bytesdocs/cases/ml-experiment/assets/class-balance.pngasset77,044 bytesdocs/cases/ml-experiment/assets/confusion-matrix.pngasset163,693 bytesdocs/cases/ml-experiment/assets/cv-performance-distribution.pngasset131,720 bytesdocs/cases/ml-experiment/assets/roc-and-pr-curves.pngasset199,061 bytesdocs/cases/ml-experiment/assets/slides-montage.pngasset244,375 bytesdocs/cases/ml-experiment/assets/vector/class-balance.svgasset45,650 bytesdocs/cases/ml-experiment/assets/vector/confusion-matrix.svgasset83,025 bytesdocs/cases/ml-experiment/assets/vector/cv-performance-distribution.svgasset116,199 bytesdocs/cases/ml-experiment/assets/vector/roc-and-pr-curves.svgasset83,216 bytesdocs/cases/ml-experiment/evidence/case-manifest.jsonasset18,352 bytesdocs/cases/ml-experiment/evidence/consistency-check.jsonasset8,738 bytesdocs/cases/ml-experiment/evidence/delivery-acceptance-report.jsonasset21,902 bytesdocs/cases/ml-experiment/evidence/figure-index.jsonasset6,885 bytesdocs/cases/ml-experiment/evidence/metrics.jsonasset3,621 bytesdocs/cases/ml-experiment/evidence/module-execution.jsonasset17,959 bytesdocs/cases/ml-experiment/evidence/module-work-plan.jsonasset22,924 bytesdocs/cases/ml-experiment/evidence/reproduction-check.jsonasset937 bytesdocs/cases/ml-experiment/evidence/selected-skills.jsonasset2,093 bytesdocs/cases/ml-experiment/evidence/skill-inventory-snapshot.jsonasset1,461 bytesdocs/cases/ml-experiment/evidence/slides-qa.txtdoc2,691 bytesdocs/cases/ml-experiment/reproduce/.gitignoreasset18 bytesdocs/cases/ml-experiment/reproduce/compute_uncertainty.pyruns13,993 bytesdocs/cases/ml-experiment/reproduce/create_data_audit.pyruns7,177 bytesdocs/cases/ml-experiment/reproduce/make_figures.pyruns15,748 bytesdocs/cases/ml-experiment/reproduce/reproduce.ps1runs2,375 bytesdocs/cases/ml-experiment/reproduce/requirements.lockasset304 bytesdocs/cases/ml-experiment/reproduce/run_experiment.pyruns12,002 bytesdocs/developer-change-governance.mddoc6,825 bytesdocs/docs-information-architecture.mddoc4,653 bytesdocs/governance/README.mddoc1,774 bytesdocs/governance/bundled-skill-retention-matrix.mddoc2,984 bytesdocs/governance/current-routing-contract.mddoc5,431 bytesdocs/governance/current-runtime-field-contract.mddoc23,058 bytesdocs/governance/distribution-governance.mddoc3,953 bytesdocs/governance/observability-consistency-governance.mddoc4,646 bytesdocs/governance/origin-provenance-policy.mddoc1,673 bytesdocs/governance/skill-admission-hardening.mddoc5,290 bytesdocs/governance/source-neutral-link-governance.mddoc1,998 bytesdocs/governance/vibe-governed-project-delivery-acceptance-governance.mddoc7,574 bytesdocs/install/README.en.mddoc5,412 bytesdocs/install/README.mddoc4,620 bytesdocs/repo-cleanliness-governance.mddoc6,192 bytesdocs/troubleshooting.mddoc546 bytesinstall.ps1runs1,619 bytesinstall.shruns728 byteslogo.pngasset1,794,228 bytespackages/.gitkeepasset0 bytespackages/adapter-sdk/pyproject.tomlasset235 bytespackages/adapter-sdk/src/vgo_adapters/__init__.pyruns171 bytespackages/adapter-sdk/src/vgo_adapters/descriptor_loader.pyruns1,029 bytespackages/adapter-sdk/src/vgo_adapters/target_root_resolver.pyruns488 bytespackages/contracts/pyproject.tomlasset248 bytespackages/contracts/src/vgo_contracts/__init__.pyruns5,486 bytespackages/contracts/src/vgo_contracts/adapter_descriptor.pyruns700 bytespackages/contracts/src/vgo_contracts/adapter_registry_support.pyruns1,686 bytespackages/contracts/src/vgo_contracts/canonical_vibe_contract.pyruns2,650 bytespackages/contracts/src/vgo_contracts/catalog_descriptor.pyruns360 bytespackages/contracts/src/vgo_contracts/discoverable_entry_surface.pyruns3,412 bytespackages/contracts/src/vgo_contracts/entry_root_guard.pyruns4,515 bytespackages/contracts/src/vgo_contracts/git_provenance.pyruns1,005 bytespackages/contracts/src/vgo_contracts/governance_runtime_roles.pyruns1,355 bytespackages/contracts/src/vgo_contracts/host_launch_receipt.pyruns3,059 bytespackages/contracts/src/vgo_contracts/host_runtime_readiness.pyruns5,916 bytespackages/contracts/src/vgo_contracts/install_ledger.pyruns2,906 bytespackages/contracts/src/vgo_contracts/installed_runtime_contract.pyruns2,068 bytespackages/contracts/src/vgo_contracts/live_governance_contract.pyruns54,594 bytespackages/contracts/src/vgo_contracts/mirror_topology_contract.pyruns4,905 bytespackages/contracts/src/vgo_contracts/module_execution_contract.pyruns20,226 bytespackages/contracts/src/vgo_contracts/runtime_packet.pyruns701 bytespackages/contracts/src/vgo_contracts/runtime_surface_contract.pyruns4,309 bytespackages/contracts/src/vgo_contracts/target_root_contract.pyruns1,755 bytespackages/contracts/src/vgo_contracts/tdd_evidence_contract.pyruns1,263 bytespackages/contracts/src/vgo_contracts/verification_scenario.pyruns160 bytespackages/contracts/src/vgo_contracts/workspace_memory_identity.pyruns360 bytespackages/installer-core/pyproject.tomlasset239 bytespackages/installer-core/src/vgo_installer/__init__.pyruns969 bytespackages/installer-core/src/vgo_installer/_bootstrap.pyruns565 bytespackages/installer-core/src/vgo_installer/_io.pyruns521 bytespackages/installer-core/src/vgo_installer/_path_safety.pyruns1,364 bytespackages/installer-core/src/vgo_installer/adapter_registry.pyruns9,120 bytespackages/installer-core/src/vgo_installer/discoverable_wrappers.pyruns12,175 bytespackages/installer-core/src/vgo_installer/global_instruction_contract.pyruns2,637 bytespackages/installer-core/src/vgo_installer/global_instruction_merge.pyruns6,665 bytespackages/installer-core/src/vgo_installer/global_instruction_service.pyruns8,997 bytespackages/installer-core/src/vgo_installer/host_closure.pyruns10,043 bytespackages/installer-core/src/vgo_installer/install_plan.pyruns2,571 bytespackages/installer-core/src/vgo_installer/install_runtime.pyruns41,996 bytespackages/installer-core/src/vgo_installer/ledger_service.pyruns17,119 bytespackages/installer-core/src/vgo_installer/materializer.pyruns24,216 bytespackages/installer-core/src/vgo_installer/profile_inventory.pyruns3,010 bytespackages/installer-core/src/vgo_installer/repair.pyruns893 bytespackages/installer-core/src/vgo_installer/runtime_packaging.pyruns6,308 bytespackages/installer-core/src/vgo_installer/simple_skill_installer.pyruns98,735 bytespackages/installer-core/src/vgo_installer/uninstall_plan.pyruns959 bytespackages/installer-core/src/vgo_installer/uninstall_runtime.pyruns1,218 bytespackages/installer-core/src/vgo_installer/uninstall_service.pyruns26,125 bytespackages/runtime-core/pyproject.tomlasset235 bytespackages/runtime-core/src/vgo_runtime/__init__.pyruns246 bytespackages/runtime-core/src/vgo_runtime/artifact_contract.pyruns18,362 bytespackages/runtime-core/src/vgo_runtime/canonical_entry.pyruns103,126 bytespackages/runtime-core/src/vgo_runtime/compatibility_exit.pyruns4,110 bytespackages/runtime-core/src/vgo_runtime/custom_admission.pyruns11,479 bytespackages/runtime-core/src/vgo_runtime/entry_locator.pyruns4,255 bytespackages/runtime-core/src/vgo_runtime/entry_policy.pyruns1,596 bytespackages/runtime-core/src/vgo_runtime/governance.pyruns406 bytespackages/runtime-core/src/vgo_runtime/grade_intent.pyruns5,558 bytespackages/runtime-core/src/vgo_runtime/kernel/__init__.pyruns1,406 bytespackages/runtime-core/src/vgo_runtime/kernel/_io.pyruns2,238 bytespackages/runtime-core/src/vgo_runtime/kernel/capability_bridge.pyruns24,885 bytespackages/runtime-core/src/vgo_runtime/kernel/codex_plugins.pyruns4,485 bytespackages/runtime-core/src/vgo_runtime/kernel/codex_skill_policy.pyruns9,208 bytespackages/runtime-core/src/vgo_runtime/kernel/executor.pyruns11,004 bytespackages/runtime-core/src/vgo_runtime/kernel/finder.pyruns7,377 bytespackages/runtime-core/src/vgo_runtime/kernel/host_skill_roots.pyruns6,120 bytespackages/runtime-core/src/vgo_runtime/kernel/loop.pyruns91,433 bytespackages/runtime-core/src/vgo_runtime/kernel/module_assignments.pyruns2,591 bytespackages/runtime-core/src/vgo_runtime/kernel/planner.pyruns16,689 bytespackages/runtime-core/src/vgo_runtime/kernel/run_state.pyruns2,687 bytespackages/runtime-core/src/vgo_runtime/kernel/skill_index.pyruns44,799 bytespackages/runtime-core/src/vgo_runtime/kernel/skill_manifest.pyruns20,661 bytespackages/runtime-core/src/vgo_runtime/kernel/skill_resources.pyruns2,622 bytespackages/runtime-core/src/vgo_runtime/kernel/task_card.pyruns18,763 bytespackages/runtime-core/src/vgo_runtime/kernel/text_tokens.pyruns2,375 bytespackages/runtime-core/src/vgo_runtime/kernel/verifier.pyruns9,007 bytespackages/runtime-core/src/vgo_runtime/kernel/work_plan.pyruns2,143 bytespackages/runtime-core/src/vgo_runtime/memory.pyruns1,011 bytespackages/runtime-core/src/vgo_runtime/planning.pyruns272 bytespackages/runtime-core/src/vgo_runtime/powershell_bridge.pyruns12,896 bytespackages/runtime-core/src/vgo_runtime/process_tree.pyruns7,359 bytespackages/runtime-core/src/vgo_runtime/route_index.pyruns5,269 bytespackages/runtime-core/src/vgo_runtime/router_contract_runtime.pyruns88,763 bytespackages/runtime-core/src/vgo_runtime/runtime_bridge.pyruns3,657 bytespackages/runtime-core/src/vgo_runtime/runtime_summary.pyruns15,419 bytespackages/runtime-core/src/vgo_runtime/runtime_support.pyruns14,469 bytespackages/runtime-core/src/vgo_runtime/runtime_truth.pyruns3,930 bytespackages/runtime-core/src/vgo_runtime/skill_authority.pyruns8,745 bytespackages/runtime-core/src/vgo_runtime/stage_machine.pyruns155 bytespackages/runtime-core/src/vgo_runtime/stage_stop.pyruns3,309 bytespackages/runtime-core/src/vgo_runtime/task_intent.pyruns113 bytespackages/runtime-core/src/vgo_runtime/workspace_memory.pyruns1,242 bytespackages/runtime-core/src/vgo_runtime/workspace_memory_schema.pyruns1,046 bytespackages/skill-catalog/catalog/README.mddoc516 bytespackages/skill-catalog/catalog/groups/index.jsonasset561 bytespackages/skill-catalog/catalog/metadata/index.jsonasset279 bytespackages/skill-catalog/catalog/metadata/official-skill-contracts.jsonasset997 bytespackages/skill-catalog/catalog/profiles/full.jsonasset188 bytespackages/skill-catalog/catalog/profiles/index.jsonasset286 bytespackages/skill-catalog/catalog/profiles/minimal.jsonasset194 bytespackages/skill-catalog/pyproject.tomlasset259 bytespackages/skill-catalog/src/vgo_catalog/__init__.pyruns139 bytespackages/skill-catalog/src/vgo_catalog/_bootstrap.pyruns351 bytespackages/skill-catalog/src/vgo_catalog/exporter.pyruns4,661 bytespackages/verification-core/pyproject.tomlasset239 bytespackages/verification-core/src/vgo_verify/__init__.pyruns713 bytespackages/verification-core/src/vgo_verify/_bootstrap.pyruns351 bytespackages/verification-core/src/vgo_verify/_io.pyruns519 bytespackages/verification-core/src/vgo_verify/_repo.pyruns940 bytespackages/verification-core/src/vgo_verify/bio_science_pack_consolidation_audit.pyruns20,332 bytespackages/verification-core/src/vgo_verify/bootstrap_doctor.pyruns6,034 bytespackages/verification-core/src/vgo_verify/bootstrap_doctor_runtime.pyruns17,152 bytespackages/verification-core/src/vgo_verify/bootstrap_doctor_support.pyruns11,344 bytespackages/verification-core/src/vgo_verify/code_quality_pack_consolidation_audit.pyruns18,719 bytespackages/verification-core/src/vgo_verify/gate_engine.pyruns2,723 bytespackages/verification-core/src/vgo_verify/global_pack_consolidation_audit.pyruns17,073 bytespackages/verification-core/src/vgo_verify/ml_skills_pruning_audit.pyruns37,809 bytespackages/verification-core/src/vgo_verify/opencode_preview_smoke.pyruns1,032 bytespackages/verification-core/src/vgo_verify/opencode_preview_smoke_runtime.pyruns6,603 bytespackages/verification-core/src/vgo_verify/opencode_preview_smoke_support.pyruns1,750 bytespackages/verification-core/src/vgo_verify/policies.pyruns8,628 bytespackages/verification-core/src/vgo_verify/proof_publication.pyruns12,776 bytespackages/verification-core/src/vgo_verify/release_notes_quality.pyruns1,553 bytespackages/verification-core/src/vgo_verify/release_notes_quality_runtime.pyruns1,741 bytespackages/verification-core/src/vgo_verify/release_notes_quality_support.pyruns2,010 bytespackages/verification-core/src/vgo_verify/release_truth.pyruns4,576 bytespackages/verification-core/src/vgo_verify/router_ai_connectivity_probe.pyruns12,810 bytespackages/verification-core/src/vgo_verify/router_ai_probe_advice.pyruns16,855 bytespackages/verification-core/src/vgo_verify/router_ai_probe_support.pyruns7,807 bytespackages/verification-core/src/vgo_verify/router_ai_probe_vector.pyruns5,858 bytespackages/verification-core/src/vgo_verify/router_bridge_gate.pyruns951 bytespackages/verification-core/src/vgo_verify/router_bridge_gate_runtime.pyruns3,527 bytespackages/verification-core/src/vgo_verify/router_bridge_gate_support.pyruns990 bytespackages/verification-core/src/vgo_verify/runtime_coherence.pyruns1,682 bytespackages/verification-core/src/vgo_verify/runtime_coherence_runtime.pyruns7,112 bytespackages/verification-core/src/vgo_verify/runtime_coherence_support.pyruns2,159 bytespackages/verification-core/src/vgo_verify/runtime_delivery_acceptance.pyruns8,756 bytespackages/verification-core/src/vgo_verify/runtime_delivery_acceptance_runtime.pyruns50,820 bytespackages/verification-core/src/vgo_verify/runtime_delivery_acceptance_support.pyruns13,319 bytespackages/verification-core/src/vgo_verify/runtime_freshness.pyruns4,552 bytespackages/verification-core/src/vgo_verify/scenario_runner.pyruns718 bytespackages/verification-core/src/vgo_verify/scenarios/install_matrix.jsonasset544 bytespackages/verification-core/src/vgo_verify/scenarios/runtime_matrix.jsonasset541 bytespackages/verification-core/src/vgo_verify/test_baseline_audit.pyruns25,687 bytespackages/verification-core/src/vgo_verify/workflow_acceptance.pyruns1,307 bytespackages/verification-core/src/vgo_verify/workflow_acceptance_runtime.pyruns3,790 bytespackages/verification-core/src/vgo_verify/workflow_acceptance_support.pyruns3,073 bytesprotocols/do.mddoc10,535 bytesprotocols/retro.mddoc17,570 bytesprotocols/review.mddoc7,353 bytesprotocols/runtime.mddoc18,582 bytesprotocols/team.mddoc25,560 bytesprotocols/think.mddoc12,180 bytespyproject.tomlasset251 bytespytest.iniasset31 bytesreferences/change-proof-matrix.mddoc2,615 bytesreferences/contributor-zone-decision-table.mddoc2,251 bytesreferences/developer-entry-contract.mddoc2,776 bytesreferences/fixtures/external-corpus/external-corpus-gate.jsonasset8,788 bytesreferences/fixtures/external-corpus/prompt-signals.jsonasset422,334 bytesreferences/fixtures/external-corpus/skill-keyword-index.backup.jsonasset31,358 bytesreferences/fixtures/external-corpus/skill-keyword-index.candidate.jsonasset27,168 bytesreferences/fixtures/external-corpus/vco-suggestions.jsonasset16,973 bytesreferences/fixtures/migration-map.jsonasset7,967 bytesreferences/fixtures/retro-compare/safety-gate/baseline-cer.jsonasset294 bytesreferences/fixtures/retro-compare/safety-gate/current-cer.jsonasset1,168 bytesreferences/fixtures/retro-compare/safety-gate/delta.jsonasset1,048 bytesreferences/fixtures/retro-compare/sample-run/baseline-cer.jsonasset324 bytesreferences/fixtures/retro-compare/sample-run/current-cer.jsonasset1,201 bytesreferences/fixtures/retro-compare/sample-run/delta.jsonasset1,049 bytesreferences/fixtures/retro-compare/smoke/baseline-smoke.jsonasset266 bytesreferences/fixtures/retro-compare/smoke/current-smoke.jsonasset1,075 bytesreferences/fixtures/retro-compare/smoke/delta-smoke.jsonasset1,044 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/cleanup-receipt.jsonasset1,368 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/governance-capsule.jsonasset408 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/intent-contract.jsonasset2,206 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/phase-plan-execute.jsonasset2,466 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/skeleton-receipt.jsonasset722 bytesreferences/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/stage-lineage.jsonasset1,288 bytesreferences/fixtures/skills-audit/bio-science-problem/bio-science-problem-map.csvasset9,429 bytesreferences/fixtures/skills-audit/bio-science-problem/bio-science-problem-map.jsonasset18,577 bytesreferences/fixtures/verify/routing-stability/vibe-routing-stability-gate.jsonasset25,028 bytesreferences/index.mddoc1,357 bytesreferences/proof-bundles/claude-code-managed-closure-candidate/linux-managed-run-01-local-host/installed-runtime-outputs/runtime-freshness-receipt.jsonasset262 bytesreferences/proof-bundles/claude-code-managed-closure-candidate/manifest.jsonasset2,708 bytesreferences/proof-bundles/linux-full-authoritative-candidate/linux-pwsh-run-01-wsl/installed-runtime-outputs/runtime-freshness-receipt.jsonasset298 bytesreferences/proof-bundles/linux-full-authoritative-candidate/linux-pwsh-run-02-docker/installed-runtime-outputs/runtime-freshness-receipt.jsonasset298 bytesreferences/proof-bundles/linux-full-authoritative-candidate/manifest.jsonasset3,393 bytesreferences/proof-bundles/openclaw-runtime-core-preview-candidate/manifest.jsonasset1,955 bytesreferences/release-ledger.jsonlasset5,265 bytesrules/README.mddoc462 bytesrules/common/agents.mddoc1,491 bytesrules/common/engineering.mddoc2,935 bytesrules/common/quality.mddoc1,994 bytesrules/typescript/coding-style.mddoc1,286 bytesrules/typescript/index.mddoc1,545 bytesschemas/host-capability.schema.jsonasset1,122 bytesschemas/router-provider.schema.jsonasset3,042 bytesschemas/skill-compatibility.schema.jsonasset1,316 bytesschemas/skill-contract-index.v1.schema.jsonasset1,155 bytesschemas/skill-contract.v1.schema.jsonasset2,612 bytesschemas/skill.schema.jsonasset1,357 bytesscripts.check.upstream.shruns1,884 bytesscripts/README.mddoc1,756 bytesscripts/bootstrap/one-shot-setup.ps1runs797 bytesscripts/bootstrap/one-shot-setup.shruns482 bytesscripts/bootstrap/scaffold-claude-preview.ps1runs875 bytesscripts/bootstrap/scaffold-claude-preview.shruns866 bytesscripts/bootstrap/sync-local-compat.ps1runs2,656 bytesscripts/build/assemble_distribution.pyruns5,485 bytesscripts/build/sync_adapter_registry.pyruns1,877 bytesscripts/build/sync_dist_release_manifests.pyruns7,121 bytesscripts/build/sync_runtime_core_packaging_profiles.pyruns1,864 bytesscripts/build/sync_version_governance_runtime_roles.pyruns2,372 bytesscripts/common/AntiProxyGoalDrift.ps1runs15,460 bytesscripts/common/NodeLaunchWrapper.ps1runs13,446 bytesscripts/common/ProcessLedger.ps1runs27,772 bytesscripts/common/ProtectedDocumentCleanup.ps1runs7,098 bytesscripts/common/README.mddoc1,900 bytesscripts/common/Resolve-VgoAdapter.ps1runs4,414 bytesscripts/common/adapter_registry_query.pyruns3,882 bytesscripts/common/python_helpers.shruns2,912 bytesscripts/common/resolve_vgo_adapter.pyruns2,448 bytesscripts/common/runtime_contracts.pyruns3,791 bytesscripts/common/vibe-governance-helpers.ps1runs77,393 bytesscripts/common/vibe-wave-gate-runner.ps1runs28,965 bytesscripts/governance/Invoke-NodeProcessAudit.ps1runs3,712 bytesscripts/governance/Invoke-NodeZombieCleanup.ps1runs3,789 bytesscripts/governance/README.mddoc5,193 bytesscripts/governance/audit-upstream.ps1runs23,200 bytesscripts/governance/export-repo-cleanliness-inventory.ps1runs8,854 bytesscripts/governance/install-local-worktree-excludes.ps1runs2,064 bytesscripts/governance/invoke-mem0-policy.ps1runs1,047 bytesscripts/governance/invoke-openspec-governance.ps1runs8,768 bytesscripts/governance/new-origin-record.ps1runs3,421 bytesscripts/governance/phase-end-cleanup.ps1runs10,994 bytesscripts/governance/publish-absorption-soft-rollout.ps1runs3,301 bytesscripts/governance/publish-openspec-soft-rollout.ps1runs9,512 bytesscripts/governance/release-cut.ps1runs25,731 bytesscripts/governance/set-gsd-overlay-rollout.ps1runs3,982 bytesscripts/governance/set-openspec-rollout.ps1runs3,210 bytesscripts/governance/sync-bundled-vibe.ps1runs20,792 bytesscripts/install/Install-VgoAdapter.ps1runs2,017 bytesscripts/install/install_vgo_adapter.pyruns524 bytesscripts/overlay/README.mddoc885 bytesscripts/overlay/suggest-browserops-provider.ps1runs9,488 bytesscripts/overlay/suggest-overlays.ps1runs17,731 bytesscripts/release/build_release_bundle.pyruns6,613 bytesscripts/research/README.mddoc1,108 bytesscripts/research/build-eval-slicing-catalog.ps1runs2,645 bytesscripts/research/build-watch-portfolio-review.ps1runs3,581 bytesscripts/research/build-xl-operator-checklist.ps1runs2,335 bytesscripts/research/extract-prompt-signals.ps1runs6,893 bytesscripts/research/generate-vco-suggestions.ps1runs9,917 bytesscripts/research/sync-mcp-catalog.ps1runs3,540 bytesscripts/research/vibe-adaptive-train.ps1runs10,317 bytesscripts/router/README.mddoc1,808 bytesscripts/router/invoke-pack-route.pyruns428 bytesscripts/router/modules/00-core-utils.ps1runs14,902 bytesscripts/router/modules/01-openai-responses.ps1runs18,359 bytesscripts/router/modules/10-observability.ps1runs11,986 bytesscripts/router/modules/11-route-probe.ps1runs21,226 bytesscripts/router/modules/12-heartbeat.ps1runs20,394 bytesscripts/router/modules/19-custom-admission.ps1runs16,680 bytesscripts/router/modules/20-routing-rules.ps1runs1,785 bytesscripts/router/modules/21-capability-interview.ps1runs12,115 bytesscripts/router/modules/22-intent-contract.ps1runs18,590 bytesscripts/router/modules/30-openspec.ps1runs8,459 bytesscripts/router/modules/31-gsd-overlay.ps1runs5,589 bytesscripts/router/modules/32-prompt-overlay.ps1runs8,162 bytesscripts/router/modules/33-memory-governance.ps1runs5,637 bytesscripts/router/modules/34-data-scale-overlay.ps1runs26,433 bytesscripts/router/modules/35-quality-debt-overlay.ps1runs13,764 bytesscripts/router/modules/36-framework-interop-overlay.ps1runs17,339 bytesscripts/router/modules/37-ml-lifecycle-overlay.ps1runs22,982 bytesscripts/router/modules/38-python-clean-code-overlay.ps1runs16,559 bytesscripts/router/modules/39-system-design-overlay.ps1runs15,897 bytesscripts/router/modules/40-cuda-kernel-overlay.ps1runs18,078 bytesscripts/router/modules/42-ai-rerank-overlay.ps1runs14,346 bytesscripts/router/modules/43-retrieval-overlay.ps1runs22,888 bytesscripts/router/modules/44-dialectic-team-gate.ps1runs7,660 bytesscripts/router/modules/44-exploration-overlay.ps1runs18,122 bytesscripts/router/modules/45-daily-dialectic-guard.ps1runs6,772 bytesscripts/router/modules/47-closure-overlay.ps1runs9,416 bytesscripts/router/modules/48-llm-acceleration-overlay.ps1runs107,083 bytesscripts/router/modules/49-prompt-asset-boost.ps1runs29,020 bytesscripts/router/resolve-pack-route.ps1runs4,241 bytesscripts/router/runtime_neutral/custom_admission.pyruns349 bytesscripts/router/runtime_neutral/router_contract.pyruns356 bytesscripts/ruc-nlpir/preflight.ps1runs5,460 bytesscripts/runtime/Freeze-RuntimeInputPacket.ps1runs33,779 bytesscripts/runtime/Invoke-AntiProxyGoalDriftCompaction.ps1runs551 bytesscripts/runtime/Invoke-DeepInterview.ps1runs1,127 bytesscripts/runtime/Invoke-PhaseCleanup.ps1runs11,404 bytesscripts/runtime/Invoke-PlanExecute.ps1runs14,045 bytesscripts/runtime/Invoke-SkeletonCheck.ps1runs3,182 bytesscripts/runtime/Invoke-VibeCanonicalEntry.ps1runs13,223 bytesscripts/runtime/VibeMemoryActivation.Common.ps1runs42,333 bytesscripts/runtime/VibeMemoryBackends.Common.ps1runs12,735 bytesscripts/runtime/VibeRuntime.Common.ps1runs305,785 bytesscripts/runtime/VibeSkillRouting.Common.ps1runs19,446 bytesscripts/runtime/VibeWorkspaceMemory.Common.ps1runs7,023 bytesscripts/runtime/Write-RequirementDoc.ps1runs24,303 bytesscripts/runtime/Write-XlPlan.ps1runs33,117 bytesscripts/runtime/invoke-vibe-runtime.ps1runs71,337 bytesscripts/runtime/memory_backend_driver.pyruns14,526 bytesscripts/runtime/skill_authority_driver.pyruns375 bytesscripts/runtime/workspace_memory_driver.pyruns25,386 bytesscripts/setup/check-kvm-host-readiness.shruns3,442 bytesscripts/setup/check-windows-eval-iso-readiness.shruns2,302 bytesscripts/setup/check-windows-proof-vm-state.shruns2,068 bytesscripts/setup/export-codex-settings-sanitized.ps1runs2,645 bytesscripts/setup/fetch-windows11-eval-iso.shruns4,243 bytesscripts/setup/install-local-vm-host.shruns1,607 bytesscripts/setup/persist-codex-openai-env.ps1runs2,496 bytesscripts/setup/run-windows-proof-vm.shruns11,658 bytesscripts/setup/send-qmp-boot-keys.pyruns3,036 bytesscripts/setup/send-qmp-text.pyruns3,028 bytesscripts/setup/show-windows-proof-media-options.shruns1,677 bytesscripts/setup/stop-windows-proof-vm.shruns1,631 bytesscripts/setup/sync-codex-settings-to-user-env.ps1runs2,662 bytesscripts/uninstall/Uninstall-VgoAdapter.ps1runs1,461 bytesscripts/uninstall/uninstall_vgo_adapter.pyruns526 bytesscripts/verify/README.mddoc3,841 bytesscripts/verify/cer-compare.ps1runs8,670 bytesscripts/verify/fixtures/README.mddoc1,126 bytesscripts/verify/fixtures/document-cleanup-safety/README.mddoc527 bytesscripts/verify/fixtures/document-cleanup-safety/ambiguous-cn-set/metadata.jsonasset101 bytesscripts/verify/fixtures/document-cleanup-safety/ambiguous-cn-set/source/.tmp/docs/重庆市永川区技术预见与制度创新项目申报书1-修订版.docxasset56 bytesscripts/verify/fixtures/document-cleanup-safety/ambiguous-cn-set/source/.tmp/docs/重庆市永川区技术预见与制度创新项目申报书1-补充材料.pdfasset56 bytesscripts/verify/fixtures/document-cleanup-safety/ambiguous-cn-set/source/docs/重庆市永川区技术预见与制度创新项目申报书1-正式版.docxasset36 bytesscripts/verify/fixtures/document-cleanup-safety/mixed-office-assets/metadata.jsonasset101 bytesscripts/verify/fixtures/document-cleanup-safety/mixed-office-assets/source/.tmp/staging/budget-review.xlsxasset59 bytesscripts/verify/fixtures/document-cleanup-safety/mixed-office-assets/source/.tmp/staging/quarterly-review-deck.pptxasset60 bytesscripts/verify/fixtures/document-cleanup-safety/mixed-office-assets/source/docs/reference-manual.pdfasset21 bytesscripts/verify/fixtures/document-cleanup-safety/non-protected-control/metadata.jsonasset101 bytesscripts/verify/fixtures/document-cleanup-safety/non-protected-control/source/.tmp/control.txtdoc54 bytesscripts/verify/fixtures/llm-acceleration.mock.jsonasset1,033 bytesscripts/verify/fixtures/pilot-browserops.jsonasset541 bytesscripts/verify/fixtures/pilot-deep-extraction.jsonasset731 bytesscripts/verify/fixtures/pilot-desktopops.jsonasset587 bytesscripts/verify/fixtures/pilot-memory.jsonasset575 bytesscripts/verify/fixtures/pilot-prompt.jsonasset525 bytesscripts/verify/fixtures/process-health/external-node-protected-fixture.jsonasset345 bytesscripts/verify/fixtures/process-health/healthy-managed-fixture.jsonasset1,143 bytesscripts/verify/fixtures/process-health/managed-completed-alive-fixture.jsonasset1,192 bytesscripts/verify/fixtures/process-health/managed-stale-fixture.jsonasset1,133 bytesscripts/verify/fixtures/process-health/no-node-processes-fixture.jsonasset131 bytesscripts/verify/fixtures/prompt-asset-boost.mock.jsonasset1,204 bytesscripts/verify/gate-family-index.mddoc2,572 bytesscripts/verify/lib/VibeOfflineSkillsAudit.Suites.ps1runs12,098 bytesscripts/verify/lib/VibeOfflineSkillsAudit.ps1runs12,449 bytesscripts/verify/lib/VibeRouteAudit.Suites.ps1runs8,092 bytesscripts/verify/lib/VibeRouteAudit.ps1runs5,289 bytesscripts/verify/live-document-gate.pyruns7,784 bytesscripts/verify/probe-scientific-packs.ps1runs56,462 bytesscripts/verify/publish-proof.pyruns409 bytesscripts/verify/runtime_neutral/README.mddoc2,569 bytesscripts/verify/runtime_neutral/_bootstrap.pyruns321 bytesscripts/verify/runtime_neutral/bio_science_pack_consolidation_audit.pyruns421 bytesscripts/verify/runtime_neutral/bootstrap_doctor.pyruns494 bytesscripts/verify/runtime_neutral/code_quality_pack_consolidation_audit.pyruns717 bytesscripts/verify/runtime_neutral/coherence_gate.pyruns529 bytesscripts/verify/runtime_neutral/freshness_gate.pyruns494 bytesscripts/verify/runtime_neutral/global_pack_consolidation_audit.pyruns635 bytesscripts/verify/runtime_neutral/ml_skills_pruning_audit.pyruns574 bytesscripts/verify/runtime_neutral/opencode_preview_smoke.pyruns674 bytesscripts/verify/runtime_neutral/release_notes_quality.pyruns701 bytesscripts/verify/runtime_neutral/release_truth_gate.pyruns465 bytesscripts/verify/runtime_neutral/router_ai_connectivity_probe.pyruns536 bytesscripts/verify/runtime_neutral/router_bridge_gate.pyruns522 bytesscripts/verify/runtime_neutral/runtime_delivery_acceptance.pyruns479 bytesscripts/verify/runtime_neutral/workflow_acceptance_runner.pyruns471 bytesscripts/verify/skill-metadata-gate.ps1runs51,845 bytesscripts/verify/test-baseline-audit.pyruns1,041 bytesscripts/verify/tool-governance-gate.ps1runs9,566 bytesscripts/verify/vgo-adapter-closure-gate.ps1runs2,895 bytesscripts/verify/vgo-adapter-target-root-guard-gate.ps1runs3,356 bytesscripts/verify/vibe-adaptive-routing-readiness-gate.ps1runs7,471 bytesscripts/verify/vibe-ai-rerank-gate.ps1runs7,610 bytesscripts/verify/vibe-bio-science-pack-consolidation-audit-gate.ps1runs1,207 bytesscripts/verify/vibe-bom-frontmatter-gate.ps1runs9,388 bytesscripts/verify/vibe-bootstrap-doctor-gate.ps1runs15,052 bytesscripts/verify/vibe-browserops-gate.ps1runs7,163 bytesscripts/verify/vibe-browserops-scorecard-gate.ps1runs4,277 bytesscripts/verify/vibe-browserops-softrollout-gate.ps1runs4,284 bytesscripts/verify/vibe-built-in-skill-governance-gate.ps1runs13,641 bytesscripts/verify/vibe-candidate-quality-board-gate.ps1runs265 bytesscripts/verify/vibe-canonical-entry-truth-gate.ps1runs9,082 bytesscripts/verify/vibe-capability-catalog-gate.ps1runs14,504 bytesscripts/verify/vibe-capability-dedup-gate.ps1runs7,115 bytesscripts/verify/vibe-capability-lifecycle-gate.ps1runs265 bytesscripts/verify/vibe-child-specialist-escalation-gate.ps1runs15,848 bytesscripts/verify/vibe-code-quality-pack-consolidation-audit-gate.ps1runs1,211 bytesscripts/verify/vibe-config-parity-gate.ps1runs15,215 bytesscripts/verify/vibe-connector-action-ledger-gate.ps1runs4,284 bytesscripts/verify/vibe-connector-admission-gate.ps1runs6,878 bytesscripts/verify/vibe-connector-sandbox-simulation-gate.ps1runs265 bytesscripts/verify/vibe-connector-scorecard-gate.ps1runs4,294 bytesscripts/verify/vibe-context-retro-smoke.ps1runs9,356 bytesscripts/verify/vibe-cross-host-degrade-contract-gate.ps1runs12,184 bytesscripts/verify/vibe-cross-host-install-isolation-gate.ps1runs10,115 bytesscripts/verify/vibe-cross-host-route-parity-gate.ps1runs12,187 bytesscripts/verify/vibe-cross-plane-conflict-gate.ps1runs3,964 bytesscripts/verify/vibe-cross-plane-replay-gate.ps1runs4,062 bytesscripts/verify/vibe-cross-plane-task-contract-gate.ps1runs4,083 bytesscripts/verify/vibe-cuda-kernel-overlay-gate.ps1runs7,627 bytesscripts/verify/vibe-current-routing-contract-scan.ps1runs13,493 bytesscripts/verify/vibe-current-routing-debt-gate.ps1runs17,839 bytesscripts/verify/vibe-data-scale-overlay-gate.ps1runs6,851 bytesscripts/verify/vibe-deep-discovery-gate.ps1runs6,939 bytesscripts/verify/vibe-deep-discovery-scenarios.ps1runs10,167 bytesscripts/verify/vibe-deep-extraction-pilot-gate.ps1runs4,273 bytesscripts/verify/vibe-desktopops-replay-gate.ps1runs4,255 bytesscripts/verify/vibe-desktopops-shadow-gate.ps1runs3,363 bytesscripts/verify/vibe-desktopops-softrollout-gate.ps1runs4,284 bytesscripts/verify/vibe-developer-entry-gate.ps1runs12,900 bytesscripts/verify/vibe-discovery-intake-scorecard-gate.ps1runs265 bytesscripts/verify/vibe-dist-manifest-gate.ps1runs24,467 bytesscripts/verify/vibe-docling-contract-gate.ps1runs8,178 bytesscripts/verify/vibe-docling-contract-v2-gate.ps1runs4,263 bytesscripts/verify/vibe-document-asset-safety-gate.ps1runs9,615 bytesscripts/verify/vibe-document-failure-taxonomy-gate.ps1runs265 bytesscripts/verify/vibe-ecosystem-absorption-contract-gate.ps1runs1,506 bytesscripts/verify/vibe-exploration-overlay-gate.ps1runs8,430 bytesscripts/verify/vibe-external-corpus-gate.ps1runs12,480 bytesscripts/verify/vibe-framework-interop-gate.ps1runs7,972 bytesscripts/verify/vibe-gate-reliability-gate.ps1runs265 bytesscripts/verify/vibe-generate-skills-lock.ps1runs4,326 bytesscripts/verify/vibe-global-pack-consolidation-audit-gate.ps1runs1,187 bytesscripts/verify/vibe-governance-entry-compression-gate.ps1runs5,971 bytesscripts/verify/vibe-governed-runtime-contract-gate.ps1runs23,166 bytesscripts/verify/vibe-gsd-overlay-gate.ps1runs5,861 bytesscripts/verify/vibe-heartbeat-gate.ps1runs4,872 bytesscripts/verify/vibe-host-adapter-contract-gate.ps1runs5,625 bytesscripts/verify/vibe-host-capability-schema-gate.ps1runs7,759 bytesscripts/verify/vibe-installed-runtime-freshness-gate.ps1runs2,958 bytesscripts/verify/vibe-keyword-precision-audit.ps1runs11,747 bytesscripts/verify/vibe-letta-contract-gate.ps1runs1,094 bytesscripts/verify/vibe-letta-policy-conformance-gate.ps1runs7,863 bytesscripts/verify/vibe-linux-pwsh-proof-gate.ps1runs17,389 bytesscripts/verify/vibe-linux-router-no-pwsh-gate.ps1runs625 bytesscripts/verify/vibe-llm-acceleration-overlay-gate.ps1runs6,745 bytesscripts/verify/vibe-manual-apply-policy-gate.ps1runs265 bytesscripts/verify/vibe-mem0-backend-gate.ps1runs1,207 bytesscripts/verify/vibe-mem0-softrollout-gate.ps1runs9,369 bytesscripts/verify/vibe-memory-governance-gate.ps1runs7,570 bytesscripts/verify/vibe-memory-quality-eval-gate.ps1runs265 bytesscripts/verify/vibe-memory-runtime-v3-gate.ps1runs4,624 bytesscripts/verify/vibe-memory-tier-gate.ps1runs1,680 bytesscripts/verify/vibe-mirror-edit-hygiene-gate.ps1runs12,584 bytesscripts/verify/vibe-ml-lifecycle-overlay-gate.ps1runs8,287 bytesscripts/verify/vibe-ml-skills-pruning-audit-gate.ps1runs1,155 bytesscripts/verify/vibe-module-dispatch-closure-gate.ps1runs17,650 bytesscripts/verify/vibe-nested-bundled-parity-gate.ps1runs23,228 bytesscripts/verify/vibe-no-duplicate-canonical-surface-gate.ps1runs13,051 bytesscripts/verify/vibe-no-self-introduced-fallback-gate.ps1runs7,830 bytesscripts/verify/vibe-no-silent-fallback-contract-gate.ps1runs16,058 bytesscripts/verify/vibe-node-zombie-gate.ps1runs12,182 bytesscripts/verify/vibe-observability-gate.ps1runs4,701 bytesscripts/verify/vibe-offline-hash-audit.ps1runs594 bytesscripts/verify/vibe-offline-lock-parity-audit.ps1runs637 bytesscripts/verify/vibe-offline-required-skills-audit.ps1runs530 bytesscripts/verify/vibe-offline-skills-gate.ps1runs1,721 bytesscripts/verify/vibe-openspec-governance-gate.ps1runs9,843 bytesscripts/verify/vibe-openworld-runtime-eval-gate.ps1runs265 bytesscripts/verify/vibe-operator-preview-contract-gate.ps1runs266 bytesscripts/verify/vibe-ops-cockpit-gate.ps1runs6,152 bytesscripts/verify/vibe-ops-dashboard-gate.ps1runs265 bytesscripts/verify/vibe-orchestration-core-consolidation-gate.ps1runs385 bytesscripts/verify/vibe-orchestration-core-hard-removal-gate.ps1runs6,399 bytesscripts/verify/vibe-origin-provenance-gate.ps1runs3,841 bytesscripts/verify/vibe-output-artifact-boundary-gate.ps1runs14,309 bytesscripts/verify/vibe-output-fixture-migration-stage2-gate.ps1runs266 bytesscripts/verify/vibe-pack-regression-matrix.ps1runs1,071 bytesscripts/verify/vibe-pack-routing-smoke.ps1runs17,744 bytesscripts/verify/vibe-pilot-scenarios.ps1runs6,548 bytesscripts/verify/vibe-platform-doctor-parity-gate.ps1runs3,195 bytesscripts/verify/vibe-platform-promotion-bundle.ps1runs5,149 bytesscripts/verify/vibe-platform-support-contract-gate.ps1runs1,446 bytesscripts/verify/vibe-promotion-board-gate.ps1runs7,275 bytesscripts/verify/vibe-promotion-scorecard-gate.ps1runs4,522 bytesscripts/verify/vibe-prompt-asset-boost-gate.ps1runs5,282 bytesscripts/verify/vibe-prompt-intelligence-assets-gate.ps1runs1,814 bytesscripts/verify/vibe-prompt-intelligence-eval-gate.ps1runs265 bytesscripts/verify/vibe-prompt-intelligence-productization-gate.ps1runs4,436 bytesscripts/verify/vibe-prompt-overlay-gate.ps1runs5,828 bytesscripts/verify/vibe-proof-bundle-tracked-files-gate.ps1runs6,342 bytesscripts/verify/vibe-python-clean-code-overlay-gate.ps1runs7,710 bytesscripts/verify/vibe-quality-debt-overlay-gate.ps1runs7,612 bytesscripts/verify/vibe-release-evidence-bundle-gate.ps1runs265 bytesscripts/verify/vibe-release-install-runtime-coherence-gate.ps1runs922 bytesscripts/verify/vibe-release-notes-quality-gate.ps1runs1,242 bytesscripts/verify/vibe-release-train-v2-gate.ps1runs4,359 bytesscripts/verify/vibe-release-truth-consistency-gate.ps1runs5,786 bytesscripts/verify/vibe-release-truth-gate.ps1runs1,183 bytesscripts/verify/vibe-remediation-foundation-gate.ps1runs5,870 bytesscripts/verify/vibe-repo-cleanliness-gate.ps1runs9,452 bytesscripts/verify/vibe-retrieval-overlay-gate.ps1runs8,205 bytesscripts/verify/vibe-retro-context-regression-matrix.ps1runs11,147 bytesscripts/verify/vibe-role-pack-governance-gate.ps1runs11,478 bytesscripts/verify/vibe-role-pack-v2-gate.ps1runs265 bytesscripts/verify/vibe-rollback-drill-gate.ps1runs4,141 bytesscripts/verify/vibe-rollout-proposal-boundedness-gate.ps1runs265 bytesscripts/verify/vibe-root-child-hierarchy-gate.ps1runs10,166 bytesscripts/verify/vibe-router-ai-connectivity-gate.ps1runs2,010 bytesscripts/verify/vibe-router-offline-degrade-contract-gate.ps1runs10,973 bytesscripts/verify/vibe-router-provider-neutrality-gate.ps1runs9,393 bytesscripts/verify/vibe-routing-local-owner-audit.ps1runs397 bytesscripts/verify/vibe-routing-no-local-candidate-audit.ps1runs410 bytesscripts/verify/vibe-routing-probe-research.ps1runs29,621 bytesscripts/verify/vibe-routing-requested-skill-audit.ps1runs405 bytesscripts/verify/vibe-routing-smoke.ps1runs7,944 bytesscripts/verify/vibe-routing-stability-gate.ps1runs16,873 bytesscripts/verify/vibe-routing-terminology-hard-cleanup-scan.ps1runs20,516 bytesscripts/verify/vibe-runtime-boundary-gate.ps1runs4,606 bytesscripts/verify/vibe-runtime-execution-proof-gate.ps1runs17,807 bytesscripts/verify/vibe-skill-contract-parity-gate.ps1runs10,048 bytesscripts/verify/vibe-skill-contract-schema-gate.ps1runs9,342 bytesscripts/verify/vibe-skill-harvest-v2-gate.ps1runs265 bytesscripts/verify/vibe-skill-index-routing-audit.ps1runs51,526 bytesscripts/verify/vibe-soft-migration-practice.ps1runs3,552 bytesscripts/verify/vibe-subagent-handoff-gate.ps1runs265 bytesscripts/verify/vibe-system-design-overlay-gate.ps1runs7,637 bytesscripts/verify/vibe-third-party-disclosure-parity-gate.ps1runs4,484 bytesscripts/verify/vibe-uninstall-coherence-gate.ps1runs5,647 bytesscripts/verify/vibe-universalization-no-regression-gate.ps1runs5,744 bytesscripts/verify/vibe-upstream-corpus-manifest-gate.ps1runs15,316 bytesscripts/verify/vibe-upstream-lock-coverage-gate.ps1runs4,629 bytesscripts/verify/vibe-upstream-mirror-freshness-gate.ps1runs10,645 bytesscripts/verify/vibe-upstream-reaudit-matrix-gate.ps1runs265 bytesscripts/verify/vibe-upstream-value-ops-gate.ps1runs6,653 bytesscripts/verify/vibe-version-consistency-gate.ps1runs6,976 bytesscripts/verify/vibe-version-packaging-gate.ps1runs13,618 bytesscripts/verify/vibe-wave121-upstream-mapping-gate.ps1runs266 bytesscripts/verify/vibe-wave124-ops-cockpit-v2-gate.ps1runs266 bytesscripts/verify/vibe-wave125-gate-family-convergence-gate.ps1runs266 bytesscripts/verify/vibe-wave40-63-board-gate.ps1runs6,254 bytesscripts/verify/vibe-wave64-82-closure-gate.ps1runs6,714 bytesscripts/verify/vibe-wave83-100-closure-gate.ps1runs9,887 bytesscripts/verify/vibe-workflow-acceptance-gate.ps1runs1,211 bytesscripts/verify/watch-portfolio-gate.ps1runs5,465 bytesscripts/verify/wave15-18-consistency-gate.ps1runs9,770 bytestemplates/ORIGIN.md.tmplasset1,029 bytestemplates/cer-report.json.templateasset1,758 bytestemplates/cer-report.md.templateasset2,141 bytestemplates/cer-report.schema.jsonasset7,535 bytestemplates/plans/governed-execution-plan-template.mddoc692 bytestemplates/requirements/governed-requirement-template.mddoc745 bytestests/__init__.pyruns170 bytestests/_python_source_roots.pyruns115 bytestests/bash_test_support.pyruns5,452 bytestests/conftest.pyruns1,875 bytestests/contract/test_adapter_descriptor_contract.pyruns2,353 bytestests/contract/test_install_ledger_contract.pyruns2,270 bytestests/contract/test_repo_layout_contract.pyruns980 bytestests/contract/test_runtime_packet_contract.pyruns634 bytestests/contract/test_vibe_discoverable_entry_contract.pyruns981 bytestests/e2e/test_distribution_build.pyruns7,358 bytestests/integration/test_adapter_closure_gate_registry_cutover.pyruns419 bytestests/integration/test_adapter_registry_query_delegation.pyruns1,166 bytestests/integration/test_adapter_registry_single_source.pyruns2,069 bytestests/integration/test_adapter_sdk_registry_cutover.pyruns2,194 bytestests/integration/test_bootstrap_entrypoint_registry_cutover.pyruns692 bytestests/integration/test_bootstrap_host_catalog_shared_contract.pyruns1,818 bytestests/integration/test_canonical_vibe_truth_gate.pyruns17,329 bytestests/integration/test_catalog_contract_consumption.pyruns3,846 bytestests/integration/test_check_entrypoint_registry_cutover.pyruns1,355 bytestests/integration/test_check_shell_bootstrap_doctor_counting.pyruns614 bytestests/integration/test_cli_installer_core_cutover.pyruns14,824 bytestests/integration/test_cli_main_infra_separation.pyruns8,308 bytestests/integration/test_cli_runtime_entrypoint_contract_cutover.pyruns21,353 bytestests/integration/test_cli_verify_runtime_contract_cutover.pyruns660 bytestests/integration/test_codex_install_prompt_discoverability.pyruns644 bytestests/integration/test_dist_manifest_generation.pyruns3,226 bytestests/integration/test_frontmatter_gate_runtime_contract_cutover.pyruns625 bytestests/integration/test_host_capability_matrix_single_source.pyruns3,696 bytestests/integration/test_host_global_bootstrap_shell_lifecycle.pyruns2,231 bytestests/integration/test_install_rerun_matrix.pyruns1,298 bytestests/integration/test_installed_runtime_contract_cutover.pyruns2,367 bytestests/integration/test_mirror_topology_contract_cutover.pyruns1,880 bytestests/integration/test_multi_host_real_host_root_docs.pyruns651 bytestests/integration/test_new_origin_record_vendor_guard.pyruns2,569 bytestests/integration/test_platform_doctor_parity_gate_single_source.pyruns586 bytestests/integration/test_powershell_compat_shim_cutover.pyruns3,300 bytestests/integration/test_powershell_installed_runtime_contract_bridge.pyruns2,685 bytestests/integration/test_powershell_wrapper_host_validation_dedupe.pyruns1,279 bytestests/integration/test_proof_bundle_manifest_contract.pyruns4,279 bytestests/integration/test_public_install_uninstall_guidance.pyruns4,218 bytestests/integration/test_pwsh_wrapper_contract.pyruns1,457 bytestests/integration/test_real_canonical_entry_bounded_stop.pyruns76,429 bytestests/integration/test_release_cut_gate_contract_cutover.pyruns3,633 bytestests/integration/test_resolver_shim_delegation.pyruns1,113 bytestests/integration/test_router_core_cutover.pyruns2,647 bytestests/integration/test_router_keyword_inference.pyruns3,205 bytestests/integration/test_runtime_common_registry_cutover.pyruns646 bytestests/integration/test_runtime_config_manifest_roles.pyruns5,238 bytestests/integration/test_runtime_core_packaging_roles.pyruns10,075 bytestests/integration/test_runtime_payload_dependency_coverage.pyruns3,129 bytestests/integration/test_runtime_script_manifest_roles.pyruns8,219 bytestests/integration/test_runtime_surface_contract_cutover.pyruns793 bytestests/integration/test_shared_run_artifact_contract.pyruns57,560 bytestests/integration/test_shell_frontend_windows_handoff_contract.pyruns880 bytestests/integration/test_shell_wrapper_contract.pyruns651 bytestests/integration/test_target_root_guard_single_source.pyruns844 bytestests/integration/test_verification_core_cutover.pyruns14,370 bytestests/integration/test_verification_runtime_entrypoint_contract_cutover.pyruns6,864 bytestests/integration/test_verification_scenario_runner.pyruns660 bytestests/integration/test_verify_gate_single_source_cutover.pyruns2,036 bytestests/integration/test_vibe_skill_bootstrap_contract.pyruns2,105 bytestests/integration/test_vibe_wrapper_shim_contract.pyruns739 bytestests/issue_167_runtime_surfaces.pyruns682 bytestests/replay/README.mddoc2,338 bytestests/replay/degrade/README.mddoc361 bytestests/replay/degrade/openclaw-runtime-core-preview.jsonasset1,433 bytestests/replay/fixtures/host-capability-matrix.jsonasset7,968 bytestests/replay/fixtures/provider-state-matrix.jsonasset1,585 bytestests/replay/install/README.mddoc426 bytestests/replay/install/openclaw-runtime-core-preview-isolation.jsonasset1,041 bytestests/replay/platform/README.mddoc428 bytestests/replay/platform/linux-without-pwsh.jsonasset833 bytestests/replay/promotion/README.mddoc662 bytestests/replay/promotion/claude-code-managed-closure.jsonasset1,848 bytestests/replay/promotion/openclaw-runtime-core-preview.jsonasset1,290 bytestests/replay/route/README.mddoc613 bytestests/replay/route/openclaw-runtime-core-preview.jsonasset1,790 bytestests/replay/route/recovery-wave-curated-prompts.jsonasset4,967 bytestests/replay/route/vibe-routing-chaos-audit-cases.jsonasset15,987 bytestests/replay/runtime/README.mddoc501 bytestests/runtime_neutral/live_contract_fixtures.pyruns1,405 bytestests/runtime_neutral/test_active_consultation_simplification.pyruns7,381 bytestests/runtime_neutral/test_agent_led_skill_execution_language.pyruns3,923 bytestests/runtime_neutral/test_agent_skill_organization_contract.pyruns96,968 bytestests/runtime_neutral/test_apps_surface_hygiene.pyruns1,587 bytestests/runtime_neutral/test_bash_test_support.pyruns3,762 bytestests/runtime_neutral/test_bio_science_boundary_hardening.pyruns10,646 bytestests/runtime_neutral/test_bio_science_direct_owner_routing.pyruns4,273 bytestests/runtime_neutral/test_bootstrap_doctor.pyruns5,905 bytestests/runtime_neutral/test_bootstrap_shell_target_root_guard.pyruns1,156 bytestests/runtime_neutral/test_bundled_runtime_mirror.pyruns5,864 bytestests/runtime_neutral/test_bundled_skill_governance_gate.pyruns7,387 bytestests/runtime_neutral/test_check_installed_runtime_root.pyruns1,485 bytestests/runtime_neutral/test_check_shell_target_root_guard.pyruns2,038 bytestests/runtime_neutral/test_claude_preview_scaffold.pyruns9,807 bytestests/runtime_neutral/test_codex_memory_user_simulation.pyruns41,441 bytestests/runtime_neutral/test_coherence_gate.pyruns5,782 bytestests/runtime_neutral/test_conftest_subprocess_run.pyruns1,738 bytestests/runtime_neutral/test_cross_host_memory_identity.pyruns15,227 bytestests/runtime_neutral/test_current_routing_contract_scan.pyruns7,169 bytestests/runtime_neutral/test_current_routing_docs_entrypoint.pyruns8,339 bytestests/runtime_neutral/test_cursor_managed_preview.pyruns4,298 bytestests/runtime_neutral/test_custom_admission_bridge.pyruns19,801 bytestests/runtime_neutral/test_discoverable_wrapper_host_visibility.pyruns2,981 bytestests/runtime_neutral/test_docs_readme_encoding.pyruns1,843 bytestests/runtime_neutral/test_docs_research_publishing_boundary_routing.pyruns6,302 bytestests/runtime_neutral/test_docs_source_neutral_links.pyruns2,803 bytestests/runtime_neutral/test_document_chain_layering_contract.pyruns13,430 bytestests/runtime_neutral/test_forbidden_mcp_installation_contract.pyruns18,341 bytestests/runtime_neutral/test_freshness_gate.pyruns4,201 bytestests/runtime_neutral/test_frontmatter_gate_scope_activation.pyruns8,183 bytestests/runtime_neutral/test_generated_nested_bundled.pyruns24,781 bytestests/runtime_neutral/test_global_instruction_bootstrap_runtime.pyruns9,200 bytestests/runtime_neutral/test_governed_runtime_bridge.pyruns77,781 bytestests/runtime_neutral/test_governed_runtime_lineage.pyruns5,555 bytestests/runtime_neutral/test_governed_templates.pyruns4,125 bytestests/runtime_neutral/test_install_generated_nested_bundled.pyruns10,675 bytestests/runtime_neutral/test_install_profile_differentiation.pyruns3,664 bytestests/runtime_neutral/test_installed_host_runtime_simulation.pyruns25,386 bytestests/runtime_neutral/test_installed_runtime_policy_remap.pyruns6,529 bytestests/runtime_neutral/test_installed_runtime_scripts.pyruns6,515 bytestests/runtime_neutral/test_installed_runtime_uninstall.pyruns14,478 bytestests/runtime_neutral/test_intent_contract_host_fidelity.pyruns2,875 bytestests/runtime_neutral/test_l_xl_agent_execution_handoff.pyruns87,624 bytestests/runtime_neutral/test_live_document_contract_gate.pyruns8,899 bytestests/runtime_neutral/test_llm_acceleration_overlay_gate.pyruns3,844 bytestests/runtime_neutral/test_llm_acceleration_overlay_provider_paths.pyruns12,302 bytestests/runtime_neutral/test_memory_ingest_noise_filters.pyruns11,165 bytestests/runtime_neutral/test_memory_progressive_disclosure.pyruns32,494 bytestests/runtime_neutral/test_memory_runtime_activation.pyruns24,585 bytestests/runtime_neutral/test_module_skill_dispatch_safety.pyruns9,867 bytestests/runtime_neutral/test_non_code_task_classification.pyruns55,346 bytestests/runtime_neutral/test_offline_skills_gate.pyruns8,115 bytestests/runtime_neutral/test_openclaw_runtime_core.pyruns8,826 bytestests/runtime_neutral/test_opencode_managed_preview.pyruns8,145 bytestests/runtime_neutral/test_opencode_preview_parity.pyruns4,457 bytestests/runtime_neutral/test_outputs_boundary_migration.pyruns9,323 bytestests/runtime_neutral/test_pack_manifest_role_contract.pyruns1,679 bytestests/runtime_neutral/test_powershell_entrypoint_help.pyruns3,036 bytestests/runtime_neutral/test_python_validation_contract.pyruns13,440 bytestests/runtime_neutral/test_readme_benchmark_results.pyruns3,900 bytestests/runtime_neutral/test_readme_install_cta_assets.pyruns2,820 bytestests/runtime_neutral/test_readme_preface_assets.pyruns5,329 bytestests/runtime_neutral/test_readme_star_history_assets.pyruns2,019 bytestests/runtime_neutral/test_release_cut_operator.pyruns21,768 bytestests/runtime_neutral/test_release_notes_quality.pyruns4,426 bytestests/runtime_neutral/test_release_surface.pyruns3,616 bytestests/runtime_neutral/test_release_truth_gate.pyruns3,802 bytestests/runtime_neutral/test_repo_cleanliness_policy.pyruns1,723 bytestests/runtime_neutral/test_repo_config_contract.pyruns398 bytestests/runtime_neutral/test_retired_agent_execution_surfaces.pyruns14,937 bytestests/runtime_neutral/test_root_child_hierarchy_bridge.pyruns24,910 bytestests/runtime_neutral/test_router_ai_connectivity_probe.pyruns23,365 bytestests/runtime_neutral/test_router_authority_safe_fallback.pyruns3,105 bytestests/runtime_neutral/test_router_authority_safe_fallback_contract.pyruns1,431 bytestests/runtime_neutral/test_router_bridge.pyruns8,405 bytestests/runtime_neutral/test_router_ownership_docs_contract.pyruns4,722 bytestests/runtime_neutral/test_runtime_authority_docs_contract.pyruns2,242 bytestests/runtime_neutral/test_runtime_contract_schema.pyruns10,365 bytestests/runtime_neutral/test_runtime_contracts.pyruns2,747 bytestests/runtime_neutral/test_runtime_delivery_acceptance.pyruns72,527 bytestests/runtime_neutral/test_runtime_entrypoint_helper.pyruns12,476 bytestests/runtime_neutral/test_runtime_route_output_shape.pyruns8,617 bytestests/runtime_neutral/test_runtime_summary_acceptance_refresh.pyruns8,781 bytestests/runtime_neutral/test_scientific_visualization_latex_routing.pyruns10,144 bytestests/runtime_neutral/test_shell_entrypoint_compatibility.pyruns3,847 bytestests/runtime_neutral/test_simple_install_docs_contract.pyruns5,231 bytestests/runtime_neutral/test_simple_powershell_installer_wrappers.pyruns1,344 bytestests/runtime_neutral/test_simplified_skill_routing_contract.pyruns17,469 bytestests/runtime_neutral/test_skill_authority_parity.pyruns12,993 bytestests/runtime_neutral/test_skill_candidate_execution_safety.pyruns8,398 bytestests/runtime_neutral/test_structured_bounded_reentry_continuation.pyruns24,993 bytestests/runtime_neutral/test_test_baseline_audit.pyruns33,140 bytestests/runtime_neutral/test_uninstall_vgo_adapter.pyruns7,815 bytestests/runtime_neutral/test_verify_docs_contract.pyruns947 bytestests/runtime_neutral/test_vibe_routing_chaos_audit_fixture.pyruns1,834 bytestests/runtime_neutral/test_vibe_upgrade_reminder.pyruns7,868 bytestests/runtime_neutral/test_windows_setup_helpers.pyruns3,935 bytestests/runtime_neutral/test_windsurf_runtime_core.pyruns7,666 bytestests/runtime_neutral/test_workflow_acceptance_runner.pyruns9,174 bytestests/runtime_neutral/test_workspace_shared_memory_plane.pyruns40,156 bytestests/scenarios/project_delivery/README.mddoc951 bytestests/scenarios/project_delivery/l-grade-feature-complete.jsonasset1,735 bytestests/scenarios/project_delivery/partial-completion-blocked.jsonasset1,304 bytestests/scenarios/project_delivery/xl-composite-manual-review.jsonasset2,017 bytestests/unit/test_adapter_registry_support.pyruns1,816 bytestests/unit/test_adapter_sdk.pyruns3,855 bytestests/unit/test_artifact_receipt_sync.pyruns6,617 bytestests/unit/test_canonical_entry_boundary.pyruns532 bytestests/unit/test_canonical_vibe_contract.pyruns1,754 bytestests/unit/test_canonical_vibe_entry_launcher.pyruns122,639 bytestests/unit/test_codex_plugin_inventory.pyruns14,763 bytestests/unit/test_delegated_lane_contract.pyruns61,330 bytestests/unit/test_discoverable_entry_surface.pyruns1,797 bytestests/unit/test_discoverable_wrapper_task_fidelity.pyruns646 bytestests/unit/test_discoverable_wrappers.pyruns6,708 bytestests/unit/test_entry_root_guard.pyruns3,921 bytestests/unit/test_external_skill_catalog.pyruns5,700 bytestests/unit/test_external_skill_selection.pyruns23,105 bytestests/unit/test_gate_engine.pyruns556 bytestests/unit/test_global_instruction_merge.pyruns5,477 bytestests/unit/test_host_closure.pyruns1,640 bytestests/unit/test_host_launch_receipt.pyruns2,953 bytestests/unit/test_host_skill_roots.pyruns12,445 bytestests/unit/test_install_runtime_cleanup.pyruns2,237 bytestests/unit/test_installed_runtime_contract.pyruns2,610 bytestests/unit/test_installer_adapter_registry_target_roots.pyruns8,286 bytestests/unit/test_installer_ledger_service.pyruns11,190 bytestests/unit/test_installer_opencode_guidance_payload.pyruns1,073 bytestests/unit/test_installer_profile_inventory.pyruns1,629 bytestests/unit/test_kernel_boundary_demotion_matrix.pyruns1,119 bytestests/unit/test_kernel_text_tokens.pyruns1,579 bytestests/unit/test_live_document_gate.pyruns5,981 bytestests/unit/test_live_governance_contract.pyruns23,036 bytestests/unit/test_local_installed_skill_routing.pyruns95,742 bytestests/unit/test_local_kernel_execution.pyruns82,590 bytestests/unit/test_local_kernel_planning.pyruns24,600 bytestests/unit/test_local_kernel_resume.pyruns73,040 bytestests/unit/test_local_skill_index.pyruns33,847 bytestests/unit/test_materializer_path_safety.pyruns7,971 bytestests/unit/test_materializer_runtime_noise.pyruns1,979 bytestests/unit/test_mirror_topology_contract.pyruns4,207 bytestests/unit/test_module_execution_contract.pyruns10,411 bytestests/unit/test_powershell_process_tree.pyruns7,730 bytestests/unit/test_proof_publication.pyruns8,611 bytestests/unit/test_runtime_compatibility_exit.pyruns1,792 bytestests/unit/test_runtime_contracts_helper.pyruns1,474 bytestests/unit/test_runtime_entry_locator.pyruns2,318 bytestests/unit/test_runtime_entry_policy.pyruns1,158 bytestests/unit/test_runtime_grade_intent.pyruns1,032 bytestests/unit/test_runtime_packaging_resolver.pyruns3,192 bytestests/unit/test_runtime_planning.pyruns8,423 bytestests/unit/test_runtime_router.pyruns6,672 bytestests/unit/test_runtime_stage_machine.pyruns2,560 bytestests/unit/test_runtime_stage_stop.pyruns3,127 bytestests/unit/test_runtime_summary.pyruns5,161 bytestests/unit/test_runtime_support.pyruns1,172 bytestests/unit/test_runtime_surface_contract.pyruns2,684 bytestests/unit/test_runtime_task_intent.pyruns15,526 bytestests/unit/test_runtime_truth.pyruns10,343 bytestests/unit/test_simple_skill_installer.pyruns100,817 bytestests/unit/test_skill_authority.pyruns20,583 bytestests/unit/test_skill_cache_routing.pyruns17,965 bytestests/unit/test_skill_resources.pyruns7,262 bytestests/unit/test_uninstall_service.pyruns844 bytestests/unit/test_verification_repo_root.pyruns1,767 bytestests/unit/test_verify_surface_default.pyruns1,636 bytestests/unit/test_vgo_cli_commands.pyruns41,529 bytestests/unit/test_vgo_cli_core_bridge.pyruns2,457 bytestests/unit/test_vgo_cli_external.pyruns1,598 bytestests/unit/test_vgo_cli_infra_split.pyruns7,300 bytestests/unit/test_vgo_cli_install_gates.pyruns2,852 bytestests/unit/test_vgo_cli_install_support.pyruns1,759 bytestests/unit/test_vgo_cli_installer_bridge.pyruns5,502 bytestests/unit/test_vgo_cli_process.pyruns1,261 bytestests/unit/test_vgo_cli_repo.pyruns7,201 bytestests/unit/test_vgo_cli_upgrade_service.pyruns39,991 bytestests/unit/test_vgo_cli_upgrade_state.pyruns2,813 bytestests/unit/test_vgo_verify_repo.pyruns1,653 bytestests/unit/test_vibe_skill_entry_contract.pyruns7,558 bytestests/unit/test_vibe_task_prompt_fidelity_contract.pyruns1,442 bytesthird_party/NOTICE.mddoc278 bytesthird_party/README.mddoc970 bytesthird_party/licenses/README.mddoc283 bytesthird_party/licenses/ruc-nlpir/DeepAgent-LICENSE.txtdoc1,067 bytesthird_party/licenses/ruc-nlpir/FlashRAG-LICENSE.txtdoc1,068 bytesthird_party/licenses/ruc-nlpir/README.mddoc467 bytesthird_party/licenses/ruc-nlpir/WebThinker-LICENSE.txtdoc1,067 bytesuninstall.ps1runs1,576 bytesuninstall.shruns732 bytesupdate.ps1runs1,640 bytesupdate.shruns726 bytesvendor/README.mddoc1,211 bytesvendor/mirrors/.gitkeepasset1 bytesvendor/upstreams/.gitkeepasset1 bytesvgo_cli/__init__.pyruns678 bytesvgo_python_source_roots.pyruns285 bytes
Read SKILL.md
# Vibe Governed Runtime Entry
This file is the host-facing SOP for entering canonical `vibe`. Keep it small: runtime details belong in `protocols/runtime.md`, execution discipline belongs in `protocols/do.md`, and host wrapper recipes belong in installer-generated wrapper docs.
## Trigger Contract
Enter canonical `vibe` before ordinary execution when the user explicitly invokes `$vibe`, `/vibe`, or the `vibe` skill, or when the host intentionally chooses governed requirement/plan/execution closure for a complex task.
Do not route every loosely related task into `vibe`. Lightweight questions,
single-command checks, or tasks better served by another explicitly requested
skill may proceed outside `vibe` unless the user explicitly invoked this entry.
Installed-copy updates use `update --skills-dir <skills-dir>` on the same managed directory.
skill-creator
When your agent uses it
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
3,921 tokensWhen the skill is activated
Reference documents
547 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- About Skills
- Core Principles
- Skill Creation Process
Scripts executed separately
scripts/generate_openai_yaml.pyscripts/init_skill.pyscripts/quick_validate.py
Files
SKILL.mdcore18,664 bytesagents/openai.yamlasset183 bytesassets/skill-creator-small.svgasset1,319 bytesassets/skill-creator.pngasset1,563 byteslicense.txtdoc11,358 bytesreferences/openai_yaml.mddoc2,356 bytesscripts/generate_openai_yaml.pyruns6,614 bytesscripts/init_skill.pyruns14,483 bytesscripts/quick_validate.pyruns3,293 bytes
Read SKILL.md
# Skill Creator
This skill provides guidance for creating effective skills.
## About Skills
Skills are modular, self-contained folders that extend Codex's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform Codex from a general-purpose agent into a specialized agent
equipped with procedural knowledge that no model can fully possess.
### What Skills Provide
1. Specialized workflows - Multi-step procedures for specific domainsskill-installer
When your agent uses it
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
769 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Communication
- Scripts
- Behavior and Options
- Notes
Scripts executed separately
scripts/github_utils.pyscripts/install-skill-from-github.pyscripts/list-skills.py
Files
LICENSE.txtdoc11,358 bytesSKILL.mdcore3,366 bytesSKILL.mdcore3,366 bytesagents/openai.yamlasset221 bytesassets/skill-installer-small.svgasset923 bytesassets/skill-installer.pngasset1,086 bytesscripts/github_utils.pyruns659 bytesscripts/install-skill-from-github.pyruns10,096 bytesscripts/list-skills.pyruns2,967 bytes
Read SKILL.md
# Skill Installer
Helps install skills. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimental and can be installed the same way.
Use the helper scripts based on the task:
- List skills when the user asks what is available, or if the user uses this skill without specifying what to do. Default listing is `.curated`, but you can pass `--path skills/.experimental` when they ask about experimental skills.
- Install from the curated list when the user provides a skill name.
- Install from another repo when the user provides a GitHub repo/path (including private repos).
Install skills with the helper scripts.
## Communication
When listing skills, output approximately as follows, depending on the context of the user's request. If they ask about experimental skills, list from `.experimental` instead of `.curated` and label the source accordingly:LQF_Machine_Learning_Expert_Guide
When your agent uses it
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling, prediction, training, classification, regression, clustering, deep learning, neural network, model evaluation, feature engineering, hyperparameter tuning, overfitting, underfitting, baseline, ablation study, critique my approach, review my model, is this a good idea, should I use, what's wrong with, evaluate my solution, challenge my assumptions, discuss my approach Engages in critical discussion with minimum 3 rounds of iterative refinement. Challenges both user proposals and own suggestions with fact-based critique. Demands evidence and baselines before accepting solutions.
What it loads into context
Frontmatter
186 tokensAlways available to the agent
SKILL.md
7,467 tokensWhen the skill is activated
Reference documents
7,771 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Critical Discussion Protocol
- Self-Critique Framework
- User Proposal Critique Framework
- Quick Reference
- Examples
- References
- Maintenance
Files
SKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesSKILL.mdcore31,116 bytesreferences/expert-thinking.mddoc13,011 bytesreferences/index.mddoc2,744 bytesreferences/workflow-guide.mddoc16,417 bytes
Read SKILL.md
# LQF Machine Learning Expert Guide
## When to Use This Skill
Use this skill when:
- Building ML models (classification, regression, clustering, forecasting)
- Evaluating model performance and debugging issues
- Feature engineering and data preprocessing for ML
- Hyperparameter tuning and model optimization
- Debugging overfitting, underfitting, or poor generalization
- Choosing between traditional ML and deep learning approaches
- Establishing baselines and conducting ablation studies
- Performing error analysis and model validation
- Statistical modeling with predictive componentsadaptyv
When your agent uses it
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
791 tokensWhen the skill is activated
Reference documents
13,585 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Available Experiment Types
- Protein Sequence Optimization
- API Reference
- Examples
- Important Notes
Files
SKILL.mdcore3,689 bytesSKILL.mdcore3,689 bytesSKILL.mdcore3,689 bytesSKILL.mdcore3,689 bytesreference/api_reference.mddoc6,665 bytesreference/examples.mddoc23,091 bytesreference/experiments.mddoc9,947 bytesreference/protein_optimization.mddoc17,861 bytes
Read SKILL.md
# Adaptyv
Adaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or web interface and receive experimental results in approximately 21 days.
## Quick Start
### Authentication Setup
Adaptyv requires API authentication. Set up your credentials:
1. Contact support@adaptyvbio.com to request API access (platform is in alpha/beta)
2. Receive your API access token
3. Set environment variable:
aeon
When your agent uses it
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
What it loads into context
Frontmatter
78 tokensAlways available to the agent
SKILL.md
2,490 tokensWhen the skill is activated
Reference documents
15,062 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Installation
- Core Capabilities
- Feature Extraction and Transformations
- Distance Metrics
- Deep Learning Networks
- Datasets and Benchmarking
- Common Workflows
- Best Practices
- Reference Documentation
- Additional Resources
Files
SKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesSKILL.mdcore10,515 bytesreferences/anomaly_detection.mddoc4,912 bytesreferences/classification.mddoc5,377 bytesreferences/clustering.mddoc3,744 bytesreferences/datasets_benchmarking.mddoc8,871 bytesreferences/distances.mddoc6,409 bytesreferences/forecasting.mddoc3,879 bytesreferences/networks.mddoc7,849 bytesreferences/regression.mddoc3,960 bytesreferences/segmentation.mddoc4,924 bytesreferences/similarity_search.mddoc5,242 bytesreferences/transformations.mddoc7,725 bytes
Read SKILL.md
# Aeon Time Series Machine Learning
## Overview
Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.
## When to Use This Skill
Apply this skill when:
- Classifying or predicting from time series data
- Detecting anomalies or change points in temporal sequences
- Clustering similar time series patterns
- Forecasting future values
- Finding repeated patterns (motifs) or unusual subsequences (discords)algorithmic-art
When your agent uses it
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
4,151 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- ALGORITHMIC PHILOSOPHY CREATION
- DEDUCING THE CONCEPTUAL SEED
- P5.JS IMPLEMENTATION
- INTERACTIVE ARTIFACT CREATION
- VARIATIONS & EXPLORATION
- THE CREATIVE PROCESS
- RESOURCES
Scripts executed separately
templates/generator_template.js
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore19,769 bytestemplates/generator_template.jsruns7,826 bytestemplates/viewer.htmlasset20,844 bytes
Read SKILL.md
Algorithmic philosophies are computational aesthetic movements that are then expressed through code. Output .md files (philosophy), .html files (interactive viewer), and .js files (generative algorithms).
This happens in two steps:
1. Algorithmic Philosophy Creation (.md file)
2. Express by creating p5.js generative art (.html + .js files)
First, undertake this task:
## ALGORITHMIC PHILOSOPHY CREATION
To begin, create an ALGORITHMIC PHILOSOPHY (not static images or templates) that will be interpreted through:
- Computational processes, emergent behavior, mathematical beauty
- Seeded randomness, noise fields, organic systems
- Particles, flows, fields, forcesalpha-vantage
When your agent uses it
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
What it loads into context
Frontmatter
145 tokensAlways available to the agent
SKILL.md
1,431 tokensWhen the skill is activated
Reference documents
12,244 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- API Key Setup (Required)
- Installation
- Base URL & Request Pattern
- Quick Start Examples
- API Categories
- Common Parameters
- Rate Limits
- Error Handling
- Reference Files
Files
SKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesSKILL.mdcore5,437 bytesreferences/commodities.mddoc3,822 bytesreferences/economic-indicators.mddoc3,914 bytesreferences/forex-crypto.mddoc4,172 bytesreferences/fundamentals.mddoc7,509 bytesreferences/intelligence.mddoc4,871 bytesreferences/options.mddoc2,747 bytesreferences/technical-indicators.mddoc12,397 bytesreferences/time-series.mddoc4,395 bytes
Read SKILL.md
# Alpha Vantage — Financial Market Data
Access 20+ years of global financial data: equities, options, forex, crypto, commodities, economic indicators, and 50+ technical indicators.
## API Key Setup (Required)
1. Get a free key at https://www.alphavantage.co/support/#api-key (premium plans available for higher rate limits)
2. Set as environment variable:
```bash
[Credential-related source omitted]
```
## Installationarchitecture-patterns
When your agent uses it
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
3,274 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Concepts
- Clean Architecture Pattern
- Hexagonal Architecture Pattern
- Domain-Driven Design Pattern
- Resources
- Best Practices
- Common Pitfalls
Files
SKILL.mdcore15,164 bytesSKILL.mdcore15,164 bytesSKILL.mdcore15,164 bytesSKILL.mdcore15,164 bytes
Read SKILL.md
# Architecture Patterns
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
## When to Use This Skill
- Designing new backend systems from scratch
- Refactoring monolithic applications for better maintainability
- Establishing architecture standards for your team
- Migrating from tightly coupled to loosely coupled architectures
- Implementing domain-driven design principles
- Creating testable and mockable codebases
- Planning microservices decomposition
astropy
When your agent uses it
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
What it loads into context
Frontmatter
106 tokensAlways available to the agent
SKILL.md
2,727 tokensWhen the skill is activated
Reference documents
15,969 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- Core Capabilities
- Additional Capabilities
- Installation
- Common Workflows
- Best Practices
- Documentation and Resources
- Reference Files
Files
SKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesSKILL.mdcore11,533 bytesreferences/coordinates.mddoc7,111 bytesreferences/cosmology.mddoc6,482 bytesreferences/fits.mddoc8,670 bytesreferences/tables.mddoc9,385 bytesreferences/time.mddoc9,083 bytesreferences/units.mddoc3,766 bytesreferences/wcs_and_other_modules.mddoc8,515 bytes
Read SKILL.md
# Astropy
## Overview
Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis. Use astropy for coordinate transformations, unit and quantity calculations, FITS file operations, cosmological calculations, precise time handling, tabular data manipulation, and astronomical image processing.
## When to Use This Skill
Use astropy when tasks involve:
- Converting between celestial coordinate systems (ICRS, Galactic, FK5, AltAz, etc.)
- Working with physical units and quantities (converting Jy to mJy, parsecs to km, etc.)
- Reading, writing, or manipulating FITS files (images or tables)
- Cosmological calculations (luminosity distance, lookback time, Hubble parameter)
- Precise time handling with different time scales (UTC, TAI, TT, TDB) and formats (JD, MJD, ISO)autonomous-builder
When your agent uses it
Full-stack software development agent for design, implementation, testing, and deployment. Use when the user explicitly asks for end-to-end project creation, feature development, bug fixing, or code refactoring.
What it loads into context
Frontmatter
133 tokensAlways available to the agent
SKILL.md
9,945 tokensWhen the skill is activated
Reference documents
39,497 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Architecture Pattern: Two-Agent Model
- Core Philosophy
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Rules & Constraints
- MCP Integration
- Workflow Reporting
- GitHub Integration
- Examples
- References
- Plugin 智能发现与自动使用 (ToolSearch Auto-Discovery)
- Maintenance
- Quality Gate
Scripts executed separately
assets/auto-continue.ps1assets/auto-continue.sh
Files
SKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesSKILL.mdcore43,497 bytesassets/auto-continue.ps1runs9,007 bytesassets/auto-continue.shruns8,490 bytesassets/feature-template.jsonasset1,851 bytesassets/loop-log-template.jsonasset593 bytesassets/mcp-services-template.jsonasset6,774 bytesassets/progress-template.mddoc1,204 bytesassets/safety-log-template.jsonasset1,379 bytesassets/state-template.jsonasset2,481 bytesassets/supervisor-template.jsonasset1,776 bytesreferences/architecture-patterns.mddoc4,795 bytesreferences/error-recovery.mddoc7,542 bytesreferences/github-integration.mddoc17,002 bytesreferences/index.mddoc5,648 bytesreferences/loop-prevention.mddoc14,062 bytesreferences/mcp-auto-integration.mddoc13,921 bytesreferences/mcp-integration.mddoc5,706 bytesreferences/multi-language.mddoc7,577 bytesreferences/multi-layer-security.mddoc18,586 bytesreferences/safety-protocols.mddoc8,214 bytesreferences/session-continuity.mddoc11,931 bytesreferences/skill-scheduling.mddoc12,748 bytesreferences/think-tool.mddoc9,790 bytesreferences/two-agent-architecture.mddoc23,195 bytesreferences/workflow-recording.mddoc10,848 bytes
Read SKILL.md
# Autonomous Builder
A fully autonomous software development agent that handles the complete software lifecycle: requirements analysis, architecture design, implementation, testing, debugging, and deployment.
## Architecture Pattern: Two-Agent Model
**Based on Anthropic's official claude-quickstarts architecture**
```
┌─────────────────────────────────────────────────────────────────┐
│ TWO-AGENT ARCHITECTURE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ SESSION 1: INITIALIZER AGENT │bio-database-evidence
When your agent uses it
Unified biological database evidence owner. Use for gene annotation, variant clinical significance, cancer mutation evidence, GWAS trait associations, pathway mapping, target-disease evidence, protein structures, protein interaction networks, reference single-cell census queries, and cross-database biological ID mapping. Do not use for full single-cell analysis, bulk RNA-seq differential expression, BAM/VCF processing, protein embedding models, metabolic flux modeling, genomic interval ML, or flow-cytometry file parsing.
What it loads into context
Frontmatter
106 tokensAlways available to the agent
SKILL.md
640 tokensWhen the skill is activated
Reference documents
484 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Use This Skill For
- Do Not Use This Skill For
- Workflow
- Source Guide
Files
SKILL.mdcore3,091 bytesSKILL.mdcore3,091 bytesSKILL.mdcore3,091 bytesreferences/database-evidence-sources.mddoc2,311 bytes
Read SKILL.md
# Bio Database Evidence
## Use This Skill For
Use this skill when the main task is biological database lookup, annotation, or evidence gathering across one or more biological sources:
- Gene annotation, identifiers, RefSeq, Ensembl IDs, orthologs, VEP, GO, and genomic coordinates.
- Variant clinical significance, VUS interpretation support, ClinVar review status, cancer mutations, and COSMIC evidence.
- GWAS Catalog trait associations, rs IDs, p-values, summary statistics, and genetic epidemiology evidence.
- Pathway mapping, ID conversion, KEGG pathways, Reactome enrichment, disease pathways, and pathway evidence.
- Target-disease association evidence, tractability, safety, known drugs, and Open Targets evidence.
- Protein structure evidence from AlphaFold DB or RCSB PDB, including UniProt IDs, mmCIF/PDB downloads, pLDDT, PAE, and structure metadata.
- Protein-protein interaction evidence, STRING networks, hub proteins, and enrichment evidence.
- Reference single-cell data lookup from CELLxGENE Census when the user asks for census metadata or expression data, not full downstream analysis.biopython
When your agent uses it
Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For single-cell workflows use scanpy. For direct literature REST API, use pubmed-database.
What it loads into context
Frontmatter
86 tokensAlways available to the agent
SKILL.md
3,427 tokensWhen the skill is activated
Reference documents
21,152 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Installation and Setup
- Using This Skill
- General Workflow Guidelines
- Common Patterns
- Best Practices
- Troubleshooting Common Issues
- Additional Resources
- Quick Reference
- Summary
Files
SKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesSKILL.mdcore14,182 bytesreferences/advanced.mddoc14,033 bytesreferences/alignment.mddoc8,953 bytesreferences/blast.mddoc12,649 bytesreferences/databases.mddoc11,506 bytesreferences/phylogenetics.mddoc13,835 bytesreferences/sequence_io.mddoc7,274 bytesreferences/structure.mddoc12,998 bytes
Read SKILL.md
# Biopython: Computational Molecular Biology in Python
## Overview
Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics tasks. The current version is **Biopython 1.85** (released January 2025), which supports Python 3 and requires NumPy.
## When to Use This Skill
Use this skill when:
- Working with biological sequences (DNA, RNA, or protein)
- Reading, writing, or converting biological file formats (FASTA, GenBank, FASTQ, PDB, mmCIF, etc.)
- Accessing NCBI databases (GenBank, PubMed, Protein, Gene, etc.) via Entrez
- Running BLAST searches or parsing BLAST resultsbrainstorming
When your agent uses it
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
1,021 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Anti-Pattern: "This Is Too Simple To Need A Design"
- Checklist
- Process Flow
- The Process
- After the Design
- Key Principles
Files
SKILL.mdcore4,690 bytes
Read SKILL.md
# Brainstorming Ideas Into Designs
## Overview
Help turn ideas into fully formed designs and specs through natural collaborative dialogue.
Start by understanding the current project context, then ask questions one at a time to refine the idea. Once you understand what you're building, present the design and get user approval.
<HARD-GATE>
Do NOT invoke any implementation skill, write any code, scaffold any project, or take any implementation action until you have presented a design and the user has approved it. This applies to EVERY project regardless of perceived simplicity.
</HARD-GATE>
## Anti-Pattern: "This Is Too Simple To Need A Design"
cancel-ralph
When your agent uses it
Codex-compatible cancel command for Ralph loop state, preserving the original command name.
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
259 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Script
- Usage
- Vibe compatibility
- Behavior
Scripts executed separately
scripts/cancel-ralph.ps1
Files
SKILL.mdcore988 bytesSKILL.mdcore988 bytesscripts/cancel-ralph.ps1runs2,046 bytes
Read SKILL.md
# cancel-ralph
This is a compatibility version of the Claude `cancel-ralph` command for Codex.
It only manages the local `compat` loop state used by `ralph-loop --engine compat`.
## Script
- Script path: `scripts/cancel-ralph.ps1`
## Usage
```powershell
$codexHome = if ($env:CODEX_HOME) { $env:CODEX_HOME } else { Join-Path $HOME '.codex' }
$script = Join-Path $codexHome 'skills/cancel-ralph/scripts/cancel-ralph.ps1'chembl-database
When your agent uses it
Query ChEMBL bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
2,472 tokensWhen the skill is activated
Reference documents
1,735 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Installation and Setup
- Core Capabilities
- Query Workflow
- Filter Operators
- Data Export and Analysis
- Performance Optimization
- Common Use Cases
- Resources
- Important Notes
- Additional Resources
Scripts executed separately
scripts/example_queries.py
Files
SKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesSKILL.mdcore10,249 bytesreferences/api_reference.mddoc6,879 bytesscripts/example_queries.pyruns7,160 bytes
Read SKILL.md
# ChEMBL Database
## Overview
ChEMBL is a manually curated database of bioactive molecules maintained by the European Bioinformatics Institute (EBI), containing over 2 million compounds, 19 million bioactivity measurements, 13,000+ drug targets, and data on approved drugs and clinical candidates. Access and query this data programmatically using the ChEMBL Python client for drug discovery and medicinal chemistry research.
## When to Use This Skill
This skill should be used when:
- **Compound searches**: Finding molecules by name, structure, or properties
- **Target information**: Retrieving data about proteins, enzymes, or biological targets
- **Bioactivity data**: Querying IC50, Ki, EC50, or other activity measurements
- **Drug information**: Looking up approved drugs, mechanisms, or indicationscitation-management
When your agent uses it
Comprehensive citation management for academic research. Resolve bibliographic identifiers, extract accurate metadata, validate citations, deduplicate references, and generate properly formatted BibTeX entries. This skill should be used when you need to verify citation information, convert DOIs/PMIDs/arXiv IDs to BibTeX, or ensure reference accuracy in scientific writing.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
7,564 tokensWhen the skill is activated
Reference documents
26,858 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Workflow
- Search Strategies
- Tools and Scripts
- Best Practices
- Common Pitfalls to Avoid
- Example Workflows
- Citation Outputs
- Resources
- Dependencies
- Summary
Scripts executed separately
scripts/doi_to_bibtex.pyscripts/extract_metadata.pyscripts/format_bibtex.pyscripts/search_google_scholar.pyscripts/search_pubmed.pyscripts/validate_citations.py
Files
SKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesSKILL.mdcore30,370 bytesassets/bibtex_template.bibasset9,201 bytesassets/citation_checklist.mddoc10,348 bytesreferences/bibtex_formatting.mddoc19,286 bytesreferences/citation_validation.mddoc16,075 bytesreferences/google_scholar_search.mddoc17,045 bytesreferences/metadata_extraction.mddoc19,182 bytesreferences/pubmed_search.mddoc17,735 bytesscripts/doi_to_bibtex.pyruns6,299 bytesscripts/extract_metadata.pyruns20,794 bytesscripts/format_bibtex.pyruns11,444 bytesscripts/search_google_scholar.pyruns8,982 bytesscripts/search_pubmed.pyruns12,832 bytesscripts/validate_citations.pyruns17,482 bytes
Read SKILL.md
# Citation Management
## Overview
Manage citations systematically throughout the research and writing process. This skill provides tools and strategies for extracting accurate metadata from identifiers and bibliographic sources, validating citation information, cleaning duplicate references, and generating properly formatted BibTeX entries.
Critical for maintaining citation accuracy, avoiding reference errors, and ensuring reproducible research.
## When to Use This Skill
Use this skill when:
- Resolving known or candidate papers from identifiers, titles, Google Scholar, or PubMed records
- Converting DOIs, PMIDs, or arXiv IDs to properly formatted BibTeX
- Extracting complete metadata for citations (authors, title, journal, year, etc.)claude-skills
When your agent uses it
Claude Skills meta-skill: extract domain material (docs/APIs/code/specs) into a reusable Skill (SKILL.md + references/scripts/assets), and refactor existing Skills for clarity, activation reliability, and quality gates.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
2,039 tokensWhen the skill is activated
Reference documents
5,526 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Examples
- References
- Maintenance
- Examples
- References
- Maintenance
Scripts executed separately
scripts/create-skill.shscripts/validate-skill.sh
Files
AGENTS.mddoc1,881 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesSKILL.mdcore8,119 bytesassets/template-complete.mddoc2,451 bytesassets/template-minimal.mddoc906 bytesreferences/README.mddoc7,662 bytesreferences/anti-patterns.mddoc3,032 bytesreferences/index.mddoc1,261 bytesreferences/quality-checklist.mddoc1,934 bytesreferences/skill-spec.mddoc4,834 bytesscripts/create-skill.shruns4,172 bytesscripts/validate-skill.shruns5,497 bytes
Read SKILL.md
# Claude Skills Meta-Skill
Turn scattered domain material into a Skill that is reusable, maintainable, and reliably activatable:
- `SKILL.md` as the entrypoint (triggers, constraints, patterns, examples)
- `references/` for long-form evidence and navigation
- optional `scripts/` and `assets/` for scaffolding and templates
## When to Use This Skill
Trigger this meta-skill when you need to:
- Create a new Skill from scratch from docs/specs/repos
- Refactor an existing Skill (too long, unclear, inconsistent, misfires)
- Design reliable activation (frontmatter + triggers + boundaries)
- Extract a clean Quick Reference from large materialclinical-decision-support
When your agent uses it
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
What it loads into context
Frontmatter
114 tokensAlways available to the agent
SKILL.md
5,834 tokensWhen the skill is activated
Reference documents
43,256 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Description
- Capabilities
- Pharmaceutical and Research Use Cases
- When to Use
- Visual Enhancement with Scientific Schematics
- Document Structure
- Output Format
- Integration
- Key Differentiators from Treatment-Plans Skill
- Example Usage
- Key Features
- Best Practices
- References
- Templates
- Scripts
Scripts executed separately
scripts/biomarker_classifier.pyscripts/build_decision_tree.pyscripts/create_cohort_tables.pyscripts/generate_survival_analysis.pyscripts/validate_cds_document.py
Files
README.mddoc5,021 bytesSKILL.mdcore26,205 bytesSKILL.mdcore26,205 bytesassets/biomarker_report_template.texasset13,326 bytesassets/clinical_pathway_template.texasset8,325 bytesassets/cohort_analysis_template.texasset12,601 bytesassets/color_schemes.texasset7,029 bytesassets/example_gbm_cohort.mddoc9,316 bytesassets/recommendation_strength_guide.mddoc11,322 bytesassets/treatment_recommendation_template.texasset18,843 bytesreferences/biomarker_classification.mddoc29,270 bytesreferences/clinical_decision_algorithms.mddoc21,393 bytesreferences/evidence_synthesis.mddoc33,342 bytesreferences/outcome_analysis.mddoc24,628 bytesreferences/patient_cohort_analysis.mddoc16,551 bytesreferences/treatment_recommendations.mddoc19,647 bytesscripts/biomarker_classifier.pyruns13,315 bytesscripts/build_decision_tree.pyruns15,891 bytesscripts/create_cohort_tables.pyruns18,023 bytesscripts/generate_survival_analysis.pyruns15,258 bytesscripts/validate_cds_document.pyruns12,735 bytes
Read SKILL.md
# Clinical Decision Support Documents
## Description
Generate professional clinical decision support (CDS) documents for pharmaceutical companies, clinical researchers, and medical decision-makers. This skill specializes in analytical, evidence-based documents that inform treatment strategies and drug development:
1. **Patient Cohort Analysis** - Biomarker-stratified group analyses with statistical outcome comparisons
2. **Treatment Recommendation Reports** - Evidence-based clinical guidelines with GRADE grading and decision algorithms
All documents are generated as publication-ready LaTeX/PDF files optimized for pharmaceutical research, regulatory submissions, and clinical guideline development.
**Note:** For individual patient treatment plans at the bedside, use the `treatment-plans` skill instead. This skill focuses on group-level analyses and evidence synthesis for pharmaceutical/research settings.
## Capabilitiesclinical-reports
When your agent uses it
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
8,533 tokensWhen the skill is activated
Reference documents
63,781 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- Regulatory Compliance and Privacy
- Medical Terminology and Standards
- Quality Assurance and Validation
- Data Presentation in Clinical Reports
- Integration with Other Skills
- Workflow for Clinical Report Writing
- Resources
- Common Pitfalls to Avoid
- Final Checklist
Scripts executed separately
scripts/check_deidentification.pyscripts/compliance_checker.pyscripts/extract_clinical_data.pyscripts/format_adverse_events.pyscripts/generate_report_template.pyscripts/terminology_validator.pyscripts/validate_case_report.pyscripts/validate_trial_report.py
Files
SKILL.mdcore39,695 bytesSKILL.mdcore39,695 bytesSKILL.mdcore39,695 bytesassets/case_report_template.mddoc9,771 bytesassets/clinical_trial_csr_template.mddoc9,196 bytesassets/clinical_trial_sae_template.mddoc10,565 bytesassets/consult_note_template.mddoc7,345 bytesassets/discharge_summary_template.mddoc11,984 bytesassets/hipaa_compliance_checklist.mddoc11,804 bytesassets/history_physical_template.mddoc9,266 bytesassets/lab_report_template.mddoc8,478 bytesassets/pathology_report_template.mddoc6,646 bytesassets/quality_checklist.mddoc9,973 bytesassets/radiology_report_template.mddoc8,009 bytesassets/soap_note_template.mddoc7,297 bytesreferences/README.mddoc8,563 bytesreferences/case_report_guidelines.mddoc18,830 bytesreferences/clinical_trial_reporting.mddoc20,354 bytesreferences/data_presentation.mddoc21,068 bytesreferences/diagnostic_reports_standards.mddoc18,384 bytesreferences/medical_terminology.mddoc15,523 bytesreferences/patient_documentation.mddoc21,273 bytesreferences/peer_review_standards.mddoc15,481 bytesreferences/regulatory_compliance.mddoc17,466 bytesscripts/check_deidentification.pyruns10,710 bytesscripts/compliance_checker.pyruns2,176 bytesscripts/extract_clinical_data.pyruns2,635 bytesscripts/format_adverse_events.pyruns3,049 bytesscripts/generate_report_template.pyruns4,713 bytesscripts/terminology_validator.pyruns4,140 bytesscripts/validate_case_report.pyruns11,540 bytesscripts/validate_trial_report.pyruns2,871 bytes
Read SKILL.md
# Clinical Report Writing
## Overview
Clinical report writing is the process of documenting medical information with precision, accuracy, and compliance with regulatory standards. This skill covers four major categories of clinical reports: case reports for journal publication, diagnostic reports for clinical practice, clinical trial reports for regulatory submission, and patient documentation for medical records. Apply this skill for healthcare documentation, research dissemination, and regulatory compliance.
**Critical Principle: Clinical reports must be accurate, complete, objective, and compliant with applicable regulations (HIPAA, FDA, ICH-GCP).** Patient privacy and data integrity are paramount. All clinical documentation must support evidence-based decision-making and meet professional standards.
## When to Use This Skill
This skill should be used when:
- Writing clinical case reports for journal submission (CARE guidelines)
- Creating diagnostic reports (radiology, pathology, laboratory)
- Documenting clinical trial data and adverse eventsclinicaltrials-database
When your agent uses it
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
3,450 tokensWhen the skill is activated
Reference documents
2,637 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- Core Capabilities
- Resources
- Best Practices
- Technical Specifications
Scripts executed separately
scripts/query_clinicaltrials.py
Files
SKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesSKILL.mdcore14,987 bytesreferences/api_reference.mddoc10,694 bytesscripts/query_clinicaltrials.pyruns6,992 bytes
Read SKILL.md
# ClinicalTrials.gov Database
## Overview
ClinicalTrials.gov is a comprehensive registry of clinical studies conducted worldwide, maintained by the U.S. National Library of Medicine. Access API v2 to search for trials, retrieve detailed study information, filter by various criteria, and export data for analysis. The API is public (no authentication required) with rate limits of ~50 requests per minute, supporting JSON and CSV formats.
## When to Use This Skill
This skill should be used when working with clinical trial data in scenarios such as:
- **Patient matching** - Finding recruiting trials for specific conditions or patient populations
- **Research analysis** - Analyzing clinical trial trends, outcomes, or study designs
- **Drug/intervention research** - Identifying trials testing specific drugs or interventions
- **Geographic searches** - Locating trials in specific locations or regionsclinpgx-database
When your agent uses it
Access ClinPGx pharmacogenomics data (successor to PharmGKB). Query gene-drug interactions, CPIC guidelines, allele functions, for precision medicine and genotype-guided dosing decisions.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
5,076 tokensWhen the skill is activated
Reference documents
5,048 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Installation and Setup
- Core Capabilities
- Query Workflow
- Rate Limiting and Best Practices
- PharmDOG Tool
- Resources
- Important Notes
- Common Use Cases
- Additional Resources
Scripts executed separately
scripts/query_clinpgx.py
Files
SKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesSKILL.mdcore20,947 bytesreferences/api_reference.mddoc17,360 bytesscripts/query_clinpgx.pyruns14,295 bytes
Read SKILL.md
# ClinPGx Database
## Overview
ClinPGx (Clinical Pharmacogenomics Database) is a comprehensive resource for clinical pharmacogenomics information, successor to PharmGKB. It consolidates data from PharmGKB, CPIC, and PharmCAT, providing curated information on how genetic variation affects medication response. Access gene-drug pairs, clinical guidelines, allele functions, and drug labels for precision medicine applications.
## When to Use This Skill
This skill should be used when:
- **Gene-drug interactions**: Querying how genetic variants affect drug metabolism, efficacy, or toxicity
- **CPIC guidelines**: Accessing evidence-based clinical practice guidelines for pharmacogenetics
- **Allele information**: Retrieving allele function, frequency, and phenotype data
- **Drug labels**: Exploring FDA and other regulatory pharmacogenomic drug labelingcode-reviewer
When your agent uses it
Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
1,215 tokensWhen the skill is activated
Reference documents
1,703 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Migrated Legacy Assets
- Quick Start
- Core Capabilities
- Reference Documentation
- Tech Stack
- Development Workflow
- Best Practices Summary
- Common Commands
- Troubleshooting
- Resources
Scripts executed separately
scripts/check_style.pyscripts/code_quality_checker.pyscripts/pr_analyzer.pyscripts/review_report_generator.py
Files
SKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesSKILL.mdcore5,572 bytesreferences/code_review_checklist.mddoc1,612 bytesreferences/coding_standards.mddoc1,607 bytesreferences/common_antipatterns.mddoc1,610 bytesreferences/python-style-guide.mddoc2,545 bytesscripts/check_style.pyruns2,027 bytesscripts/code_quality_checker.pyruns3,146 bytesscripts/pr_analyzer.pyruns3,103 bytesscripts/review_report_generator.pyruns3,161 bytes
Read SKILL.md
# Code Reviewer
Complete toolkit for code reviewer with modern tools and best practices.
## Routing Boundary
Use `code-reviewer` when the user asks for a fresh review of code or a PR:
- correctness and likely bugs
- maintainability and readability
- regression risk
- test coverage gaps from a reviewer's point of view
Do not let this skill own narrower problems:
- `security-reviewer` owns OWASP, secret leak, auth bypass, injection, and dedicated security audit prompts.coding-tutor
When your agent uses it
Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
2,653 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Welcome New Learners
- Setup: Ensure Tutorials Repo Exists
- First Step: Know Your Learner
- Teaching Philosophy
- Tutorial Creation
- The Living Tutorial
- What Makes Great Teaching
- Quiz Mode
Scripts executed separately
scripts/create_tutorial.pyscripts/index_tutorials.pyscripts/quiz_priority.pyscripts/setup_tutorials.py
Files
SKILL.mdcore12,017 bytesSKILL.mdcore12,017 bytesSKILL.mdcore12,017 bytesSKILL.mdcore12,017 bytesSKILL.mdcore12,017 bytesscripts/create_tutorial.pyruns6,392 bytesscripts/index_tutorials.pyruns6,398 bytesscripts/quiz_priority.pyruns5,536 bytesscripts/setup_tutorials.pyruns3,660 bytes
Read SKILL.md
This skill creates personalized coding tutorials that evolve with the learner. Each tutorial builds on previous ones, uses real examples from the current codebase, and maintains a persistent record of concepts mastered.
The user asks to learn something - either a specific concept or an open "teach me something new" request.
## Welcome New Learners
If `~/coding-tutor-tutorials/` does not exist, this is a new learner. Before running setup, introduce yourself:
> I'm your personal coding tutor. I create tutorials tailored to you - using real code from your projects, building on what you already know, and tracking your progress over time.
>
> All your tutorials live in one central library (`~/coding-tutor-tutorials/`) that works across all your projects. Use `/teach-me` to learn something new, `/quiz-me` to test your retention with spaced repetition.
Then proceed with setup and onboarding.
commit-with-reflection
When your agent uses it
Git提交与调试反思报告生成技能。用于分析开发过程中的错误、调试步骤和解决方案,生成结构化的中文反思报告,并创建包含报告引用的Git提交。显式请求词:反思提交、智能提交、生成调试报告、commit with reflection。
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
6,272 tokensWhen the skill is activated
Reference documents
18,079 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 何时使用此技能 (When to Use)
- 不适用场景 (Not For)
- 快速参考 (Quick Reference)
- 示例 (Examples)
- 参考资料 (References)
- 维护信息 (Maintenance)
- 统一模板集成 (Unified Template Integration)
- 工作流详解 (Detailed Workflow)
- 质量保证 (Quality Assurance)
- 故障排除 (Troubleshooting)
- 扩展和定制 (Extensions)
- 最佳实践建议 (Best Practices)
- Plugin 智能发现与自动使用 (ToolSearch Auto-Discovery)
- 版本历史 (Version History)
Scripts executed separately
scripts/update-index.js
Files
README.mddoc5,271 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesSKILL.mdcore21,435 bytesassets/template-chinese.mddoc1,388 bytesexamples/feature-example.mddoc20,337 bytesreferences/best-practices.mddoc18,544 bytesreferences/error-taxonomy.mddoc12,690 bytesreferences/index.mddoc2,982 bytesscripts/update-index.jsruns11,314 bytes
Read SKILL.md
# Git提交与反思报告技能 (Commit with Reflection)
自动化Git提交并生成深度调试反思报告的技能。将AI编码过程中的错误、调试经验和解决方案转化为结构化的知识文档,保存在GitHub仓库中供长期参考和学习。
## 何时使用此技能 (When to Use)
在以下情况下使用此技能:
- 用户说:"反思提交"、"智能提交"、"生成调试报告"
- 用户说:"commit with reflection"、"reflective commit"
- 完成了包含多次调试迭代的功能开发
- 修复了复杂的bug并希望记录解决过程
- 重构代码时遇到并解决了架构问题
- 希望将本次开发经验转化为可复用的知识comprehensive-research-agent
When your agent uses it
Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls
What it loads into context
Frontmatter
28 tokensAlways available to the agent
SKILL.md
1,643 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Activate
- Core Concepts
- Patterns to Avoid
- Recommended Practices
- Guidelines
- Examples
- Score Expectations
- Skill Metadata
Files
SKILL.mdcore8,515 bytesSKILL.mdcore8,515 bytesSKILL.mdcore8,515 bytesSKILL.mdcore8,515 bytesSKILL.mdcore8,515 bytesSKILL.mdcore8,515 bytesreferences/optimization_summary.jsonasset899 bytesreferences/optimized_prompt.txtdoc81 bytesreferences/patterns_found.jsonasset12,732 bytes
Read SKILL.md
# Comprehensive Research Agent Best Practices
This skill addresses common failures in multi-step research tasks: unhandled tool errors, missing validation, opaque reasoning, and premature conclusions. It provides structured protocols for source validation, error recovery, and thinking transparency that significantly improves research quality and reliability.
## When to Activate
- Task involves web research with search, read_url, or fetch operations
- Task requires gathering information from multiple sources
- Task has explicit requirements for completeness or verification
- Task includes file operations that need validation (save, write, read)
- Any research or information-gathering workflow with 3+ tool interactions
## Core Concepts
content-research-writer
When your agent uses it
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
3,389 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- What This Skill Does
- How to Use
- Instructions
- Examples
- Writing Workflows
- Pro Tips
- File Organization
- Best Practices
- Related Use Cases
Files
SKILL.mdcore14,244 bytes
Read SKILL.md
# Content Research Writer
This skill acts as your writing partner, helping you research, outline, draft, and refine content while maintaining your unique voice and style.
## When to Use This Skill
- Writing blog posts, articles, or newsletters
- Creating educational content or tutorials
- Drafting thought leadership pieces
- Researching and writing case studies
- Producing technical documentation with sources
- Writing with proper citations and references
- Improving hooks and introductions
- Getting section-by-section feedback while writingcontext-fundamentals
When your agent uses it
This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
2,116 tokensWhen the skill is activated
Reference documents
1,612 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Activate
- Core Concepts
- Detailed Topics
- Practical Guidance
- Examples
- Guidelines
- Integration
- References
- Skill Metadata
Scripts executed separately
scripts/context_manager.py
Files
SKILL.mdcore12,137 bytesSKILL.mdcore12,137 bytesSKILL.mdcore12,137 bytesreferences/context-components.mddoc7,970 bytesscripts/context_manager.pyruns11,408 bytes
Read SKILL.md
# Context Engineering Fundamentals
Context is the complete state available to a language model at inference time. It includes everything the model can attend to when generating responses: system instructions, tool definitions, retrieved documents, message history, and tool outputs. Understanding context fundamentals is prerequisite to effective context engineering.
## When to Activate
Activate this skill when:
- Designing new agent systems or modifying existing architectures
- Debugging unexpected agent behavior that may relate to context
- Optimizing context usage to reduce token costs or improve performance
- Onboarding new team members to context engineering concepts
- Reviewing context-related design decisions
## Core Conceptscontext-hunter
When your agent uses it
Discover codebase patterns, conventions, and unwritten rules before making changes. Use when implementing features, fixing bugs, or refactoring code.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
395 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Before Implementation
- During Implementation
- Checklist
Files
SKILL.mdcore2,015 bytes
Read SKILL.md
# Context Hunter
Before writing code, investigate how similar problems are already solved in this codebase.
## Before Implementation
### Discover Existing Patterns
1. **Find analogous features**: Search for code that solves similar problems. Study it before proposing your approach.
2. **Trace data flow**: How does similar data move through the system? Note caching, validation, and error handling patterns.
3. **Identify utilities**: Search for existing helpers before creating new ones.
### Detect Unwritten Conventions
create-plan
When your agent uses it
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
608 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Goal
- Minimal workflow
- Plan template (follow exactly)
- Checklist item guidance
Files
SKILL.mdcore2,448 bytes
Read SKILL.md
# Create Plan
## Goal
Turn a user prompt into a **single, actionable plan** delivered in the final assistant message.
## Minimal workflow
Throughout the entire workflow, operate in read-only mode. Do not write or update files.
1. **Scan context quickly**
- Read `README.md` and any obvious docs (`docs/`, `CONTRIBUTING.md`, `ARCHITECTURE.md`).
- Skim relevant files (the ones most likely touched).
- Identify constraints (language, frameworks, CI/test commands, deployment shape).creating-data-visualizations
When your agent uses it
Create analytical charts and plots from existing data. Use for exploratory or reporting visuals such as bars, lines, scatters, and dashboards; not for publication-grade scientific figures or AI-generated schematics.
What it loads into context
Frontmatter
96 tokensAlways available to the agent
SKILL.md
342 tokensWhen the skill is activated
Reference documents
342 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Not For / Boundaries
- Integration
- Example Requests
Scripts executed separately
scripts/chart_generator.pyscripts/data_analyzer.pyscripts/data_validator.py
Files
SKILL.mdcore1,612 bytesassets/README.mddoc456 bytesreferences/README.mddoc620 bytesscripts/README.mddoc536 bytesscripts/chart_generator.pyruns2,980 bytesscripts/data_analyzer.pyruns4,960 bytesscripts/data_validator.pyruns2,922 bytes
Read SKILL.md
# Data Visualization Creator
Use this skill when the user needs a chart from data that already exists.
## Overview
This skill focuses on everyday analytical visualization choices: bars, lines, scatters, distributions, comparisons, and simple dashboards.
## When to Use This Skill
- Plotting trends, distributions, comparisons, or correlations from structured data
- Turning query output or CSV tables into charts for analysis or slides
- Choosing a sensible chart type and axis treatment for a non-specialist audience
## Not For / Boundariescs-foundations
When your agent uses it
Master discrete mathematics, logic, formal proofs, and computational thinking. Build the mathematical foundation for all computer science.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
836 tokensWhen the skill is activated
Reference documents
1,558 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Skill Metadata
- Quick Start
- Learning Path
- Practice Problems
- Troubleshooting
- Key Concepts
- Why It Matters
- Interview Prep
Scripts executed separately
scripts/proof_validator.pyscripts/verify-proof.py
Files
SKILL.mdcore3,351 bytesassets/proof-template.mddoc1,413 bytesreferences/PROOF-TECHNIQUES.mddoc3,525 bytesscripts/proof_validator.pyruns2,213 bytesscripts/verify-proof.pyruns5,146 bytes
Read SKILL.md
# CS Foundations Skill
## Skill Metadata
```yaml
skill_config:
version: "1.0.0"
category: theoretical
prerequisites: []
estimated_time: "6-8 weeks"
difficulty: intermediate
parameter_validation:
topic:dask
When your agent uses it
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
3,237 tokensWhen the skill is activated
Reference documents
15,120 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Best Practices
- Common Workflow Patterns
- Selecting the Right Component
- Integration Considerations
- Debugging and Development
- Reference Files
Files
SKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesSKILL.mdcore14,086 bytesreferences/arrays.mddoc11,649 bytesreferences/bags.mddoc10,869 bytesreferences/best-practices.mddoc7,317 bytesreferences/dataframes.mddoc8,778 bytesreferences/futures.mddoc12,051 bytesreferences/schedulers.mddoc11,313 bytes
Read SKILL.md
# Dask
## Overview
Dask is a Python library for parallel and distributed computing that enables three critical capabilities:
- **Larger-than-memory execution** on single machines for data exceeding available RAM
- **Parallel processing** for improved computational speed across multiple cores
- **Distributed computation** supporting terabyte-scale datasets across multiple machines
Dask scales from laptops (processing ~100 GiB) to clusters (processing ~100 TiB) while maintaining familiar Python APIs.
## When to Use This Skill
This skill should be used when:data-artist
When your agent uses it
Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
1,840 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The "Data is Beautiful" Philosophy
- Visualization Domains
- Execution Strategy
- Output Format
- Visualization Types & When to Use
- Anti-Patterns to Avoid
- Inspiration Sources
- Key Principles
Files
SKILL.mdcore8,079 bytes
Read SKILL.md
# Data Artist
You are creating a work of data art. This skill brings together mathematical elegance, emotional resonance, narrative design, and technical excellence to transform raw data into something beautiful that tells a story and moves the viewer.
## The "Data is Beautiful" Philosophy
### Core Principles
1. **Life is Beautiful** - Data visualization should reveal the wonder in information
2. **Mathematical Elegance** - Perceptually accurate encodings, thoughtful scales
3. **Emotional Resonance** - Create moments of awe, reflection, insight
4. **Swiss Minimalism** - Clean geometry, purposeful color, no chartjunk
5. **Narrative Journey** - Guide the viewer through a story
data-quality-frameworks
When your agent uses it
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
3,564 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Concepts
- Quick Start
- Patterns
- Best Practices
- Resources
Files
SKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytesSKILL.mdcore15,917 bytes
Read SKILL.md
# Data Quality Frameworks
Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.
## When to Use This Skill
- Implementing data quality checks in pipelines
- Setting up Great Expectations validation
- Building comprehensive dbt test suites
- Establishing data contracts between teams
- Monitoring data quality metrics
- Automating data validation in CI/CD
## Core Conceptsdata-storytelling
When your agent uses it
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
What it loads into context
Frontmatter
38 tokensAlways available to the agent
SKILL.md
2,838 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Concepts
- Story Frameworks
- Visualization Techniques
- Presentation Templates
- Writing Techniques
- Best Practices
- Resources
Files
SKILL.mdcore12,474 bytesSKILL.mdcore12,474 bytes
Read SKILL.md
# Data Storytelling
Transform raw data into compelling narratives that drive decisions and inspire action.
## When to Use This Skill
- Presenting analytics to executives
- Creating quarterly business reviews
- Building investor presentations
- Writing data-driven reports
- Communicating insights to non-technical audiences
- Making recommendations based on data
## Core Conceptsdatacommons-client
When your agent uses it
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
What it loads into context
Frontmatter
96 tokensAlways available to the agent
SKILL.md
1,857 tokensWhen the skill is activated
Reference documents
6,891 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- Installation
- Core Capabilities
- Typical Workflow
- Finding Statistical Variables
- Working with Pandas
- API Authentication
- Reference Documentation
- Additional Resources
- Tips for Effective Use
Files
SKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesSKILL.mdcore8,472 bytesreferences/getting_started.mddoc10,145 bytesreferences/node.mddoc6,126 bytesreferences/observation.mddoc5,498 bytesreferences/resolve.mddoc7,204 bytes
Read SKILL.md
# Data Commons Client
## Overview
Provides comprehensive access to the Data Commons Python API v2 for querying statistical observations, exploring the knowledge graph, and resolving entity identifiers. Data Commons aggregates data from census bureaus, health organizations, environmental agencies, and other authoritative sources into a unified knowledge graph.
## Routing Boundary
Use this skill when the user explicitly asks for Data Commons/datacommons, Data Commons statistical variables, Data Commons entities/DCIDs, or population/economic indicators that fit the Data Commons knowledge graph.
Generic public data, open data, public dataset search, or public download-link collection by itself is not enough to select this skill. Those requests need a clearer Data Commons/statistical-graph signal before this skill becomes the route owner.
## Installation
datavis
When your agent uses it
Comprehensive data visualization toolkit for creating beautiful, mathematically elegant visualizations with D3.js, Chart.js, and custom SVG. Use when (1) building interactive data visualizations, (2) designing color palettes for charts, (3) choosing scales and visual encodings, (4) creating data pipelines from Census/SEC/Wikipedia APIs, (5) crafting narrative-driven data stories, (6) making perceptually accurate charts, or (7) implementing force-directed networks, timelines, or geographic maps.
What it loads into context
Frontmatter
109 tokensAlways available to the agent
SKILL.md
1,180 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Philosophy: "Life is Beautiful"
- Core Capabilities
- Scripts
- Anti-Patterns to Avoid
- Quality Checklist
Scripts executed separately
scripts/analyze-distribution.pyscripts/color-palette.pyscripts/d3-scaffold.py
Files
SKILL.mdcore4,611 bytesscripts/analyze-distribution.pyruns12,812 bytesscripts/color-palette.pyruns10,194 bytesscripts/d3-scaffold.pyruns26,996 bytes
Read SKILL.md
# Data Visualization Skill
Create beautiful, mathematically elegant, emotionally resonant data visualizations.
## Philosophy: "Life is Beautiful"
Every visualization should:
1. **Reveal truth** through data
2. **Evoke wonder** through design
3. **Respect the viewer** through accessibility
4. **Honor complexity** through elegant simplification
## Core Capabilities
denario
When your agent uses it
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
1,193 tokensWhen the skill is activated
Reference documents
7,944 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Installation
- LLM API Configuration
- Core Research Workflow
- Available Journals
- Launching the GUI
- Common Workflows
- Advanced Features
- Detailed References
- Troubleshooting
Files
SKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesSKILL.mdcore5,933 bytesreferences/examples.mddoc12,754 bytesreferences/installation.mddoc3,942 bytesreferences/llm_configuration.mddoc6,713 bytesreferences/research_pipeline.mddoc11,884 bytes
Read SKILL.md
# Denario
## Overview
Denario is a multiagent AI system designed to automate scientific research workflows from initial data analysis through publication-ready manuscripts. Built on AG2 and LangGraph frameworks, it orchestrates multiple specialized agents to handle hypothesis generation, methodology development, computational analysis, and paper writing.
## When to Use This Skill
Use this skill when:
- Analyzing datasets to generate novel research hypotheses
- Developing structured research methodologies
- Executing computational experiments and generating visualizations
- Conducting literature searches for research context
- Writing journal-formatted LaTeX papers from research resultsdesigning-experiments
When your agent uses it
Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
499 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Decision Framework
- Method Quick Reference
- Failed Experiment Recovery
Files
SKILL.mdcore2,399 bytes
Read SKILL.md
# Designing Experiments
Helps choose and specify a research design before data analysis starts. This skill owns study-design decisions: what is treated, what is compared, what outcome is measured, which assumptions are required, which validation or recovery experiment should follow a failed scientific experiment, and which design is defensible.
It does not fit causal models, estimate treatment effects, interpret fitted model output from existing data, or debug software/build failures.
## Decision Framework
1. **Control Group?**
* **Yes**: Go to Step 2.
* **No**: Consider **Interrupted Time Series (ITS)**.
2. **Unit Structure?**
* **Single Treated Unit**:deslop
When your agent uses it
Remove AI-generated code slop from a branch: unnecessary comments, redundant defensive checks, boilerplate, style drift, and type casts. Use for cleanup of AI-written code, not for broad code review, security audit, TDD, or final verification.
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
289 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- What to Remove
- Process
Files
SKILL.mdcore1,322 bytes
Read SKILL.md
# Remove AI Code Slop
Check the diff against main and remove all AI-generated slop introduced in this branch.
## Routing Boundary
Use this skill when the user's problem is cleanup of AI-generated code noise. If the user asks for a broad correctness/maintainability review, use `code-reviewer`. If the user asks whether existing review comments should be accepted, use `receiving-code-review`.
## What to Remove
- Extra comments that a human wouldn't add or are inconsistent with the rest of the file
- Extra defensive checks or try/catch blocks that are abnormal for that area of the codebase (especially if called by trusted/validated codepaths)
- Casts to `any` to get around type issues
- Inline imports in Python (move to top of file with other imports)detecting-data-anomalies
When your agent uses it
Investigate outliers, rare events, spikes, and suspicious records in datasets. Use as an explicit anomaly-analysis helper when you want concrete anomaly-detection workflow guidance, not generic data validation or end-to-end ML ownership.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
330 tokensWhen the skill is activated
Reference documents
870 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/algorithm_selector.pyscripts/anomaly_visualizer.pyscripts/data_loader.pyscripts/report_generator.py
Files
SKILL.mdcore1,513 bytesassets/README.mddoc404 bytesreferences/README.mddoc683 bytesreferences/errors.mddoc1,001 bytesreferences/examples.mddoc67 bytesreferences/implementation.mddoc1,771 bytesscripts/README.mddoc639 bytesscripts/algorithm_selector.pyruns2,974 bytesscripts/anomaly_visualizer.pyruns2,940 bytesscripts/data_loader.pyruns2,952 bytesscripts/report_generator.pyruns2,952 bytes
Read SKILL.md
# Detecting Data Anomalies
## Positioning
Treat this skill as an explicit/manual helper.
In governed ML routing, anomaly-detection ownership normally belongs to `scikit-learn`.
## When to Use
Use this skill when:
- Reviewing outlier transactions, fraud candidates, sensor spikes, or rare failures
- Comparing isolation forest, one-class SVM, LOF, or threshold-based anomaly workflows
- Turning suspicious records into a shortlist for human inspection
detecting-performance-regressions
When your agent uses it
Compare current benchmark results against historical baselines to spot performance regressions. Use as an explicit/manual helper for build-to-build degradation review, not for broad optimization strategy or low-level profiling ownership.
What it loads into context
Frontmatter
107 tokensAlways available to the agent
SKILL.md
288 tokensWhen the skill is activated
Reference documents
310 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/analyze_metrics.pyscripts/create_github_comment.pyscripts/generate_report.py
Files
SKILL.mdcore1,417 bytesassets/README.mddoc384 bytesreferences/README.mddoc526 bytesscripts/README.mddoc631 bytesscripts/analyze_metrics.pyruns4,990 bytesscripts/create_github_comment.pyruns3,875 bytesscripts/generate_report.pyruns3,901 bytes
Read SKILL.md
# Performance Regression Detector
## Positioning
Treat this skill as an explicit/manual helper for benchmark comparison work.
## When to Use
Use this skill when:
- Identify performance regressions in a CI/CD pipeline.
- Analyze performance metrics for potential degradation.
- Compare current performance against historical baselines.
## Not For / Boundaries
dialectic
When your agent uses it
Minimal compatibility wrapper for vibe Dialectic Mode (multi-perspective design analysis).
What it loads into context
Frontmatter
23 tokensAlways available to the agent
SKILL.md
252 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Use Cases
- Execution Contract
- Compatibility Notes
Files
SKILL.mdcore1,022 bytes
Read SKILL.md
# dialectic (Codex Compatibility)
Thin adapter for `/vibe` dialectic routing. Keep this skill lightweight and defer workflow logic to `vibe`.
## Use Cases
- User explicitly asks for the think-tank flow: "使用辩证智囊团", "启用辩证智囊团", "`$vibe dialectic`", or "dialectic-design".
- Multiple viable design approaches need structured comparison.
## Execution Contract
1. Route to `vibe` Dialectic Mode:
- `vibe/protocols/team.md` (Dialectic Mode section)
- `vibe/references/team-templates.md` (Template 6: `dialectic-design`)digital-brain
When your agent uses it
This skill should be used when the user asks to "write a post", "check my voice", "look up contact", "prepare for meeting", "weekly review", "track goals", or mentions personal brand, content creation, network management, or voice consistency.
What it loads into context
Frontmatter
69 tokensAlways available to the agent
SKILL.md
1,666 tokensWhen the skill is activated
Reference documents
21,698 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Activate
- Core Concepts
- Detailed Topics
- Practical Guidance
- Examples
- Guidelines
- Integration
- References
- Skill Metadata
Scripts executed separately
agents/scripts/content_ideas.pyagents/scripts/idea_to_draft.pyagents/scripts/stale_contacts.pyagents/scripts/weekly_review.pypackage.jsonscripts/install.sh
Files
.gitignoreasset442 bytesAGENT.mddoc1,567 bytesHOW-SKILLS-BUILT-THIS.mddoc12,982 bytesREADME.mddoc7,416 bytesSKILL.mdcore7,043 bytesSKILLS-MAPPING.mddoc8,848 bytesagents/AGENTS.mddoc2,599 bytesagents/scripts/content_ideas.pyruns4,325 bytesagents/scripts/idea_to_draft.pyruns4,164 bytesagents/scripts/stale_contacts.pyruns3,942 bytesagents/scripts/weekly_review.pyruns3,224 bytescontent/CONTENT.mddoc2,250 bytescontent/calendar.mddoc2,096 bytescontent/engagement.jsonlasset663 bytescontent/ideas.jsonlasset486 bytescontent/posts.jsonlasset627 bytescontent/templates/linkedin-post.mddoc1,605 bytescontent/templates/newsletter.mddoc1,580 bytescontent/templates/thread.mddoc1,170 bytesexamples/content-workflow.mddoc4,540 bytesexamples/meeting-prep.mddoc5,763 bytesidentity/IDENTITY.mddoc1,457 bytesidentity/bio-variants.mddoc1,696 bytesidentity/brand.mddoc3,730 bytesidentity/prompts/content-generation.xmlasset1,439 bytesidentity/prompts/reply-generator.xmlasset1,318 bytesidentity/values.yamlasset1,960 bytesidentity/voice.mddoc3,397 bytesknowledge/KNOWLEDGE.mddoc2,447 bytesknowledge/bookmarks.jsonlasset559 bytesknowledge/competitors.mddoc2,285 bytesknowledge/learning.yamlasset2,120 bytesknowledge/research/_template.mddoc1,285 bytesnetwork/NETWORK.mddoc3,096 bytesnetwork/circles.yamlasset2,020 bytesnetwork/contacts.jsonlasset897 bytesnetwork/interactions.jsonlasset454 bytesnetwork/intros.mddoc2,177 bytesoperations/OPERATIONS.mddoc2,058 bytesoperations/goals.yamlasset2,132 bytesoperations/meetings.jsonlasset635 bytesoperations/metrics.jsonlasset707 bytesoperations/reviews/_weekly_template.mddoc1,720 bytesoperations/todos.mddoc1,293 bytespackage.jsonruns1,287 bytesreferences/file-formats.mddoc7,478 bytesscripts/install.shruns1,993 bytes
Read SKILL.md
# Digital Brain
A structured personal operating system for managing digital presence, knowledge, relationships, and goals with AI assistance. Designed for founders building in public, content creators growing their audience, and tech-savvy professionals seeking AI-assisted personal management.
**Important**: This skill uses progressive disclosure. Module-specific instructions are in each subdirectory's `.md` file. Only load what's needed for the current task.
## When to Activate
Activate this skill when the user:
- Requests content creation (posts, threads, newsletters) - load identity/voice.md first
- Asks for help with personal brand or positioning
- Needs to look up or manage contacts/relationships
- Wants to capture or develop content ideasdnanexus-integration
When your agent uses it
DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
What it loads into context
Frontmatter
54 tokensAlways available to the agent
SKILL.md
2,387 tokensWhen the skill is activated
Reference documents
11,926 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Start Examples
- Workflow Decision Tree
- Installation and Authentication
- Common Patterns
- Best Practices
- Resources
- Getting Help
Files
SKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesSKILL.mdcore10,550 bytesreferences/app-development.mddoc5,291 bytesreferences/configuration.mddoc13,172 bytesreferences/data-operations.mddoc8,120 bytesreferences/job-execution.mddoc8,766 bytesreferences/python-sdk.mddoc9,776 bytes
Read SKILL.md
# DNAnexus Integration
## Overview
DNAnexus is a cloud platform for biomedical data analysis and genomics. Build and deploy apps/applets, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.
## When to Use This Skill
This skill should be used when:
- Creating, building, or modifying DNAnexus apps/applets
- Uploading, downloading, searching, or organizing files and records
- Running analyses, monitoring jobs, creating workflows
- Writing scripts using dxpy to interact with the platform
- Setting up dxapp.json, managing dependencies, using Dockerdoc
When your agent uses it
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
704 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Rendering commands
- Quality expectations
- Final checks
Scripts executed separately
scripts/render_docx.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore2,988 bytesagents/openai.yamlasset271 bytesassets/doc-small.svgasset1,678 bytesassets/doc.pngasset1,211 bytesscripts/render_docx.pyruns9,700 bytes
Read SKILL.md
# DOCX Skill
## When to use
- Read or review DOCX content where layout matters (tables, diagrams, pagination).
- Create or edit DOCX files with professional formatting.
- Validate visual layout before delivery.
## Workflow
1. Prefer visual review (layout, tables, diagrams).
- If `soffice` and `pdftoppm` are available, convert DOCX -> PDF -> PNGs.
- Or use `scripts/render_docx.py` (requires `pdf2image` and Poppler).
- If these tools are missing, install them or ask the user to review rendered pages locally.
2. Use `python-docx` for edits and structured creation (headings, styles, tables, lists).docs-review
When your agent uses it
Review documentation changes for compliance with the Metabase writing style guide. Use when reviewing pull requests, files, or diffs containing documentation markdown files.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
1,531 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Review mode detection
- Review process
- Review checklist
- Quick scan table
- Feedback format
- Final check
Files
SKILL.mdcore6,756 bytes
Read SKILL.md
# Documentation Review Skill
@./../_shared/metabase-style-guide.md
## Review mode detection
**IMPORTANT: Before starting the review, determine which mode to use:**
1. **PR review mode**: If the `mcp__github__create_pending_pull_request_review` tool is available, you are reviewing a GitHub PR
- Use the pending review workflow to post all issues as one cohesive review
- Follow the workflow steps in "PR review mode format" below
2. **Local review mode**: If the MCP tool is NOT available, output issues in the conversation
- Format all issues in a numbered markdown list (as described in "Feedback format" below)docs-write
When your agent uses it
Write documentation following Metabase's conversational, clear, and user-focused style. Use when creating or editing documentation files (markdown, MDX, etc.).
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
663 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When writing documentation
Files
SKILL.mdcore2,870 bytes
Read SKILL.md
# Documentation Writing Skill
@./../_shared/metabase-style-guide.md
## When writing documentation
### Start here
1. **Who is this for?** Match complexity to audience. Don't oversimplify hard things or overcomplicate simple ones.
2. **What do they need?** Get them to the answer fast. Nobody wants to be in docs longer than necessary.
3. **What did you struggle with?** Those common questions you had when learning? Answer them (without literally including the question).
### Writing process
document-skills
When your agent uses it
Umbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
532 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick dispatch rules
- Safety / noise controls
- Output expectations
Files
SKILL.mdcore2,194 bytes
Read SKILL.md
# Document Skills (Dispatcher)
Use this skill when the task is clearly “document work” but the exact format is not yet fixed, or when the user mixes multiple formats (e.g., “把论文里的表格做成 Excel，再导出 PDF 报告”).
Goal: **fast dispatch to the most specific skill** so we keep **high hit-rate / low noise**.
## Quick dispatch rules
1) **PDF** (`.pdf`, “PDF”, “pypdf”, “pdfplumber”, “render pages”)
- Prefer the **pdf** skill.
- Typical tasks: extract text/tables, render pages, review layout, generate PDF reports.
2) **Word / DOCX** (`.docx`, “Word”, “tracked changes”, “python-docx”)
- Prefer the **docx** skill (or **doc** when the task is explicitly `.docx` formatting/layout heavy and the doc skill is requested/required by your environment).docx
When your agent uses it
Document toolkit (.docx). Create/edit documents, tracked changes, comments, formatting preservation, text extraction, for professional document processing.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
2,656 tokensWhen the skill is activated
Reference documents
11,530 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Visual Enhancement with Scientific Schematics
- Workflow Decision Tree
- Reading and analyzing content
- Creating a new Word document
- Editing an existing Word document
- Redlining workflow for document review
- Converting Documents to Images
- Code Style Guidelines
- Dependencies
Scripts executed separately
ooxml/scripts/pack.pyooxml/scripts/unpack.pyooxml/scripts/validate.pyooxml/scripts/validation/__init__.pyooxml/scripts/validation/base.pyooxml/scripts/validation/docx.pyooxml/scripts/validation/pptx.pyooxml/scripts/validation/redlining.pyscripts/__init__.pyscripts/document.pyscripts/utilities.py
Files
LICENSE.txtdoc1,467 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesSKILL.mdcore11,268 bytesdocx-js.mddoc16,509 bytesooxml.mddoc23,649 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-chart.xsdasset74,984 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsdasset6,956 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-diagram.xsdasset51,302 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsdasset624 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-main.xsdasset152,039 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-picture.xsdasset1,231 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-spreadsheetDrawing.xsdasset8,862 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-wordprocessingDrawing.xsdasset14,795 bytesooxml/schemas/ISO-IEC29500-4_2016/pml.xsdasset83,612 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-additionalCharacteristics.xsdasset1,269 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-bibliography.xsdasset7,328 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsdasset6,382 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlDataProperties.xsdasset1,248 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlSchemaProperties.xsdasset880 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesCustom.xsdasset2,608 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesExtended.xsdasset3,507 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesVariantTypes.xsdasset7,507 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-math.xsdasset23,313 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-relationshipReference.xsdasset1,367 bytesooxml/schemas/ISO-IEC29500-4_2016/sml.xsdasset242,277 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-main.xsdasset26,148 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-officeDrawing.xsdasset25,279 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-presentationDrawing.xsdasset535 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-spreadsheetDrawing.xsdasset5,712 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-wordprocessingDrawing.xsdasset4,010 bytesooxml/schemas/ISO-IEC29500-4_2016/wml.xsdasset171,367 bytesooxml/schemas/ISO-IEC29500-4_2016/xml.xsdasset4,646 bytesooxml/schemas/ecma/fouth-edition/opc-contentTypes.xsdasset1,963 bytesooxml/schemas/ecma/fouth-edition/opc-coreProperties.xsdasset2,515 bytesooxml/schemas/ecma/fouth-edition/opc-digSig.xsdasset2,856 bytesooxml/schemas/ecma/fouth-edition/opc-relationships.xsdasset1,344 bytesooxml/schemas/mce/mc.xsdasset3,127 bytesooxml/schemas/microsoft/wml-2010.xsdasset26,549 bytesooxml/schemas/microsoft/wml-2012.xsdasset3,745 bytesooxml/schemas/microsoft/wml-2018.xsdasset901 bytesooxml/schemas/microsoft/wml-cex-2018.xsdasset1,778 bytesooxml/schemas/microsoft/wml-cid-2016.xsdasset1,002 bytesooxml/schemas/microsoft/wml-sdtdatahash-2020.xsdasset600 bytesooxml/schemas/microsoft/wml-symex-2015.xsdasset745 bytesooxml/scripts/pack.pyruns5,596 bytesooxml/scripts/unpack.pyruns1,037 bytesooxml/scripts/validate.pyruns1,959 bytesooxml/scripts/validation/__init__.pyruns336 bytesooxml/scripts/validation/base.pyruns39,892 bytesooxml/scripts/validation/docx.pyruns9,996 bytesooxml/scripts/validation/pptx.pyruns12,327 bytesooxml/scripts/validation/redlining.pyruns11,305 bytesscripts/__init__.pyruns65 bytesscripts/document.pyruns50,457 bytesscripts/templates/comments.xmlasset2,635 bytesscripts/templates/commentsExtended.xmlasset2,643 bytesscripts/templates/commentsExtensible.xmlasset2,739 bytesscripts/templates/commentsIds.xmlasset2,651 bytesscripts/templates/people.xmlasset147 bytesscripts/utilities.pyruns13,694 bytes
Read SKILL.md
# DOCX creation, editing, and analysis
## Overview
A .docx file is a ZIP archive containing XML files and resources. Create, edit, or analyze Word documents using text extraction, raw XML access, or redlining workflows. Apply this skill for professional document processing, tracked changes, and content manipulation.
## Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematicWhen your agent uses it
PDF manipulation toolkit. Extract text/tables, create PDFs, merge/split, fill forms, for programmatic document processing and analysis.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
2,033 tokensWhen the skill is activated
Reference documents
6,315 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Visual Enhancement with Scientific Schematics
- Quick Start
- Python Libraries
- Command-Line Tools
- Common Tasks
- Quick Reference
- Next Steps
Scripts executed separately
scripts/check_bounding_boxes.pyscripts/check_bounding_boxes_test.pyscripts/check_fillable_fields.pyscripts/convert_pdf_to_images.pyscripts/create_validation_image.pyscripts/extract_form_field_info.pyscripts/fill_fillable_fields.pyscripts/fill_pdf_form_with_annotations.py
Files
LICENSE.txtdoc1,467 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesSKILL.mdcore8,302 bytesforms.mddoc9,438 bytesreference.mddoc16,692 bytesscripts/check_bounding_boxes.pyruns3,139 bytesscripts/check_bounding_boxes_test.pyruns8,818 bytesscripts/check_fillable_fields.pyruns362 bytesscripts/convert_pdf_to_images.pyruns1,123 bytesscripts/create_validation_image.pyruns1,603 bytesscripts/extract_form_field_info.pyruns6,127 bytesscripts/fill_fillable_fields.pyruns4,863 bytesscripts/fill_pdf_form_with_annotations.pyruns3,596 bytes
Read SKILL.md
# PDF Processing Guide
## Overview
Extract text/tables, create PDFs, merge/split files, fill forms using Python libraries and command-line tools. Apply this skill for programmatic document processing and analysis. For advanced features or form filling, consult reference.md and forms.md.
## Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematicpptx
When your agent uses it
Presentation toolkit (.pptx). Create/edit slides, layouts, content, speaker notes, comments, for programmatic presentation creation and modification.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
6,445 tokensWhen the skill is activated
Reference documents
9,483 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Visual Enhancement with Scientific Schematics
- Reading and analyzing content
- Creating a new PowerPoint presentation **without a template**
- Editing an existing PowerPoint presentation
- Creating a new PowerPoint presentation **using a template**
- Creating Thumbnail Grids
- Converting Slides to Images
- Code Style Guidelines
- Dependencies
Scripts executed separately
ooxml/scripts/pack.pyooxml/scripts/unpack.pyooxml/scripts/validate.pyscripts/html2pptx.jsscripts/inventory.pyscripts/rearrange.pyscripts/replace.pyscripts/thumbnail.py
Files
LICENSE.txtdoc1,467 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 bytesSKILL.mdcore26,715 byteshtml2pptx.mddoc19,859 bytesooxml.mddoc10,618 bytesooxml/scripts/pack.pyruns546 bytesooxml/scripts/unpack.pyruns550 bytesooxml/scripts/validate.pyruns553 bytesscripts/html2pptx.jsruns37,795 bytesscripts/inventory.pyruns38,126 bytesscripts/rearrange.pyruns8,514 bytesscripts/replace.pyruns13,594 bytesscripts/thumbnail.pyruns15,484 bytes
Read SKILL.md
# PPTX creation, editing, and analysis
## Overview
A .pptx file is a ZIP archive containing XML files and resources. Create, edit, or analyze PowerPoint presentations using text extraction, raw XML access, or html2pptx workflows. Apply this skill for programmatic presentation creation and modification.
## Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematicdocumentation-lookup
When your agent uses it
Use when the user needs current library, framework, or API documentation and version-specific code examples.
What it loads into context
Frontmatter
27 tokensAlways available to the agent
SKILL.md
230 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Selection Rules
Files
SKILL.mdcore1,245 bytesSKILL.mdcore1,245 bytesSKILL.mdcore1,245 bytes
Read SKILL.md
# Documentation Lookup
Use current official documentation instead of relying on memory when the answer depends on a library, framework, API, or version.
## Workflow
1. Identify the exact project, package, and version from the request or local dependency files.
2. Prefer an installed documentation set, package source, or purpose-built connector, API, or CLI that reaches the official primary source.
3. Read only the pages needed to answer the question.
4. State the version or documentation date when it affects the answer.
5. Cite the official page or local source path used.
If a current official source is unavailable, say what could not be verified and do not guess. Do not install or recommend an unrelated documentation service as a workaround.
docx
When your agent uses it
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
2,473 tokensWhen the skill is activated
Reference documents
11,516 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Workflow Decision Tree
- Reading and analyzing content
- Creating a new Word document
- Editing an existing Word document
- Redlining workflow for document review
- Converting Documents to Images
- Code Style Guidelines
- Dependencies
Scripts executed separately
ooxml/scripts/pack.pyooxml/scripts/unpack.pyooxml/scripts/validate.pyooxml/scripts/validation/__init__.pyooxml/scripts/validation/base.pyooxml/scripts/validation/docx.pyooxml/scripts/validation/pptx.pyooxml/scripts/validation/redlining.pyscripts/__init__.pyscripts/document.pyscripts/utilities.py
Files
LICENSE.txtdoc1,467 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesSKILL.mdcore10,150 bytesdocx-js.mddoc16,509 bytesooxml.mddoc23,572 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-chart.xsdasset74,984 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsdasset6,956 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-diagram.xsdasset51,302 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsdasset624 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-main.xsdasset152,039 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-picture.xsdasset1,231 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-spreadsheetDrawing.xsdasset8,862 bytesooxml/schemas/ISO-IEC29500-4_2016/dml-wordprocessingDrawing.xsdasset14,795 bytesooxml/schemas/ISO-IEC29500-4_2016/pml.xsdasset83,612 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-additionalCharacteristics.xsdasset1,269 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-bibliography.xsdasset7,328 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsdasset6,382 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlDataProperties.xsdasset1,248 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlSchemaProperties.xsdasset880 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesCustom.xsdasset2,608 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesExtended.xsdasset3,507 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesVariantTypes.xsdasset7,507 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-math.xsdasset23,313 bytesooxml/schemas/ISO-IEC29500-4_2016/shared-relationshipReference.xsdasset1,367 bytesooxml/schemas/ISO-IEC29500-4_2016/sml.xsdasset242,277 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-main.xsdasset26,148 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-officeDrawing.xsdasset25,279 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-presentationDrawing.xsdasset535 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-spreadsheetDrawing.xsdasset5,712 bytesooxml/schemas/ISO-IEC29500-4_2016/vml-wordprocessingDrawing.xsdasset4,010 bytesooxml/schemas/ISO-IEC29500-4_2016/wml.xsdasset171,367 bytesooxml/schemas/ISO-IEC29500-4_2016/xml.xsdasset4,646 bytesooxml/schemas/ecma/fouth-edition/opc-contentTypes.xsdasset1,963 bytesooxml/schemas/ecma/fouth-edition/opc-coreProperties.xsdasset2,515 bytesooxml/schemas/ecma/fouth-edition/opc-digSig.xsdasset2,856 bytesooxml/schemas/ecma/fouth-edition/opc-relationships.xsdasset1,344 bytesooxml/schemas/mce/mc.xsdasset3,127 bytesooxml/schemas/microsoft/wml-2010.xsdasset26,549 bytesooxml/schemas/microsoft/wml-2012.xsdasset3,745 bytesooxml/schemas/microsoft/wml-2018.xsdasset901 bytesooxml/schemas/microsoft/wml-cex-2018.xsdasset1,778 bytesooxml/schemas/microsoft/wml-cid-2016.xsdasset1,002 bytesooxml/schemas/microsoft/wml-sdtdatahash-2020.xsdasset600 bytesooxml/schemas/microsoft/wml-symex-2015.xsdasset745 bytesooxml/scripts/pack.pyruns5,596 bytesooxml/scripts/unpack.pyruns1,037 bytesooxml/scripts/validate.pyruns1,959 bytesooxml/scripts/validation/__init__.pyruns336 bytesooxml/scripts/validation/base.pyruns39,892 bytesooxml/scripts/validation/docx.pyruns9,996 bytesooxml/scripts/validation/pptx.pyruns12,327 bytesooxml/scripts/validation/redlining.pyruns11,179 bytesscripts/__init__.pyruns65 bytesscripts/document.pyruns50,409 bytesscripts/templates/comments.xmlasset2,635 bytesscripts/templates/commentsExtended.xmlasset2,643 bytesscripts/templates/commentsExtensible.xmlasset2,739 bytesscripts/templates/commentsIds.xmlasset2,651 bytesscripts/templates/people.xmlasset147 bytesscripts/utilities.pyruns13,694 bytes
Read SKILL.md
# DOCX creation, editing, and analysis
## Overview
A user may ask you to create, edit, or analyze the contents of a .docx file. A .docx file is essentially a ZIP archive containing XML files and other resources that you can read or edit. You have different tools and workflows available for different tasks.
## Workflow Decision Tree
### Reading/Analyzing Content
Use "Text extraction" or "Raw XML access" sections below
### Creating New Document
Use "Creating a new Word document" workflow
docx-comment-reply
When your agent uses it
Reply to comments (批注) in Word .docx/.doc files: extract comment context, draft replies, write threaded replies back, and validate OOXML.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
704 tokensWhen the skill is activated
Reference documents
207 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 输出物（约定）
- 工作流（推荐）
- 并行（XL 可选）
Scripts executed separately
scripts/apply_comment_replies.pyscripts/extract_comment_context.pyscripts/lint_replies.py
Files
SKILL.mdcore2,422 bytesSKILL.mdcore2,422 bytesSKILL.mdcore2,422 bytesSKILL.mdcore2,422 bytesscripts/apply_comment_replies.pyruns2,898 bytesscripts/extract_comment_context.pyruns15,670 bytesscripts/lint_replies.pyruns1,331 bytestemplates/reply_style_generic_zh.mddoc695 bytes
Read SKILL.md
# Word 批注回复（.docx/.doc）
这个 skill 解决的问题：把 Word 文档里的批注（comments）按“原文锚点上下文”整理出来，生成待回复清单，然后把回复以 **threaded replies** 的方式写回到新的 `.docx` 文件里（不改原文件）。
适用场景：专利/论文/合同/内部评审等需要“逐条回复批注”的文档。
## 输出物（约定）
在当前工作目录的 `outputs/` 下生成：
- `*_批注定位与上下文_*.md`：人可读的批注+锚点上下文报告
- `*_comment_context_*.json`：机器可读上下文（用于并行写回复/自动化）
- `*_replies_todo_*.json`：待回复模板（键=comment_id，值=空字符串）
- `*_批注已回复_*.docx`：写回批注回复后的最终交付文件
edgartools
When your agent uses it
Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.
What it loads into context
Frontmatter
129 tokensAlways available to the agent
SKILL.md
1,190 tokensWhen the skill is activated
Reference documents
13,784 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Authentication (Required)
- Installation
- Core Workflow
- Key Company Properties
- Form → Object Mapping
- Common Pitfalls
- Reference Files
Files
SKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesSKILL.mdcore4,783 bytesreferences/ai-integration.mddoc6,888 bytesreferences/companies.mddoc6,126 bytesreferences/data-objects.mddoc5,572 bytesreferences/entity-facts.mddoc8,338 bytesreferences/filings.mddoc9,113 bytesreferences/financial-data.mddoc7,106 bytesreferences/xbrl.mddoc9,466 bytes
Read SKILL.md
# edgartools — SEC EDGAR Data
Python library for accessing all SEC filings since 1994 with structured data extraction.
## Authentication (Required)
The SEC requires identification for API access. Always set identity before any operations:
```python
from edgar import set_identity
set_identity("Your Name your.email@example.com")
```
Set via environment variable to avoid hardcoding: `EDGAR_IDENTITY="Your Name your@email.com"`.embedding-strategies
When your agent uses it
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
3,300 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Concepts
- Templates
- Best Practices
- Resources
Files
SKILL.mdcore14,558 bytesSKILL.mdcore14,558 bytesSKILL.mdcore14,558 bytesSKILL.mdcore14,558 bytesSKILL.mdcore14,558 bytesSKILL.mdcore14,558 bytes
Read SKILL.md
# Embedding Strategies
Guide to selecting and optimizing embedding models for vector search applications.
## When to Use This Skill
- Choosing embedding models for RAG
- Optimizing chunking strategies
- Fine-tuning embeddings for domains
- Comparing embedding model performance
- Reducing embedding dimensions
- Handling multilingual content
## Core Conceptsena-database
When your agent uses it
Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
1,545 tokensWhen the skill is activated
Reference documents
3,592 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Resources
Files
SKILL.mdcore6,977 bytesSKILL.mdcore6,977 bytesSKILL.mdcore6,977 bytesSKILL.mdcore6,977 bytesSKILL.mdcore6,977 bytesSKILL.mdcore6,977 bytesreferences/api_reference.mddoc13,339 bytes
Read SKILL.md
# ENA Database
## Overview
The European Nucleotide Archive (ENA) is a comprehensive public repository for nucleotide sequence data and associated metadata. Access and query DNA/RNA sequences, raw reads, genome assemblies, and functional annotations through REST APIs and FTP for genomics and bioinformatics pipelines.
## When to Use This Skill
This skill should be used when:
- Retrieving nucleotide sequences or raw sequencing reads by accession
- Searching for samples, studies, or assemblies by metadata criteria
- Downloading FASTQ files or genome assemblies for analysis
- Querying taxonomic information for organismsError Resolver
When your agent uses it
Legacy error-resolution reference archive retained for migration. Do not route user tasks here; use systematic-debugging for active bug, stack-trace, and root-cause work.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
2,076 tokensWhen the skill is activated
Reference documents
30,163 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Status
- Core Philosophy
- Quick Start
- Error Classification Framework
- Analysis Workflow
- Output Format
- Replay System
- Debug Commands
- Common Debugging Patterns
- Reference Files
Files
SKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesSKILL.mdcore8,313 bytesanalysis/root-cause.mddoc7,512 bytesanalysis/stack-trace.mddoc8,158 bytespatterns/database.mddoc10,149 bytespatterns/docker.mddoc9,294 bytespatterns/git.mddoc9,158 bytespatterns/go.mddoc9,010 bytespatterns/network.mddoc11,835 bytespatterns/nodejs.mddoc10,608 bytespatterns/python.mddoc10,768 bytespatterns/react.mddoc11,410 bytespatterns/rust.mddoc10,709 bytesreplay/README.mddoc6,735 bytesreplay/solution-template.yamlasset2,101 bytes
Read SKILL.md
# Error Resolver
Legacy reference archive for first-principle error diagnosis across languages and frameworks.
## Routing Status
This directory is retained because it contains substantial analysis, pattern, and replay material. It is not an active `code-quality` route owner. Route user-facing bug, stack-trace, and root-cause tasks to `systematic-debugging`.
## Core Philosophy
**The 5-step Error Resolution Process:**
```
1. CLASSIFY -> 2. PARSE -> 3. MATCH -> 4. ANALYZE -> 5. RESOLVEetetoolkit
When your agent uses it
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
4,512 tokensWhen the skill is activated
Reference documents
13,790 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Capabilities
- Installation and Setup
- Common Use Cases
- Reference Documentation
- Troubleshooting
- Newick Format Reference
- Best Practices
Scripts executed separately
scripts/quick_visualize.pyscripts/tree_operations.py
Files
SKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesSKILL.mdcore17,819 bytesreferences/api_reference.mddoc12,736 bytesreferences/visualization.mddoc19,529 bytesreferences/workflows.mddoc18,933 bytesscripts/quick_visualize.pyruns7,156 bytesscripts/tree_operations.pyruns8,235 bytes
Read SKILL.md
# ETE Toolkit Skill
## Overview
ETE (Environment for Tree Exploration) is a toolkit for phylogenetic and hierarchical tree analysis. Manipulate trees, analyze evolutionary events, visualize results, and integrate with biological databases for phylogenomic research and clustering analysis.
## Core Capabilities
### 1. Tree Manipulation and Analysis
Load, manipulate, and analyze hierarchical tree structures with support for:
- **Tree I/O**: Read and write Newick, NHX, PhyloXML, and NeXML formats
- **Tree traversal**: Navigate trees using preorder, postorder, or levelorder strategiesevals-context
When your agent uses it
Provides context about the Roo Code evals system structure in this monorepo. Use when tasks mention "evals", "evaluation", "eval runs", "eval exercises", or working with the evals infrastructure. Helps distinguish between the evals execution system (packages/evals, apps/web-evals) and the public website evals display page (apps/web-roo-code/src/app/evals).
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
1,856 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When NOT to Use This Skill
- Key Disambiguation: Two "Evals" Locations
- Directory Structure Reference
- Architecture Overview
- Common Tasks Quick Reference
- Running Evals Locally
- Testing
- Key Types/Exports from `@roo-code/evals`
Files
SKILL.mdcore8,228 bytesSKILL.mdcore8,228 bytesSKILL.mdcore8,228 bytesSKILL.mdcore8,228 bytes
Read SKILL.md
# Evals Codebase Context
## When to Use This Skill
Use this skill when the task involves:
- Modifying or debugging the evals execution infrastructure
- Adding new eval exercises or languages
- Working with the evals web interface (apps/web-evals)
- Modifying the public evals display page on roocode.com
- Understanding where evals code lives in this monorepo
## When NOT to Use This Skill
evaluating-code-models
When your agent uses it
Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.
What it loads into context
Frontmatter
154 tokensAlways available to the agent
SKILL.md
3,244 tokensWhen the skill is activated
Reference documents
7,120 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Common Workflows
- When to Use vs Alternatives
- Supported Benchmarks
- Common Issues
- Command Reference
- Hardware Requirements
- Resources
Files
SKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesSKILL.mdcore11,696 bytesreferences/benchmarks.mddoc9,168 bytesreferences/custom-tasks.mddoc10,378 bytesreferences/issues.mddoc8,085 bytes
Read SKILL.md
# BigCode Evaluation Harness - Code Model Benchmarking
## Quick Start
BigCode Evaluation Harness evaluates code generation models across 15+ benchmarks including HumanEval, MBPP, and MultiPL-E (18 languages).
**Installation**:
```bash
git clone https://github.com/bigcode-project/bigcode-evaluation-harness.git
cd bigcode-evaluation-harness
pip install -e .
accelerate config
```
evaluating-llms-harness
When your agent uses it
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
What it loads into context
Frontmatter
156 tokensAlways available to the agent
SKILL.md
3,474 tokensWhen the skill is activated
Reference documents
13,475 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick start
- Common workflows
- When to use vs alternatives
- Common issues
- Advanced topics
- Hardware requirements
- Resources
Files
SKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesSKILL.mdcore11,895 bytesreferences/api-evaluation.mddoc11,114 bytesreferences/benchmark-guide.mddoc10,769 bytesreferences/custom-tasks.mddoc13,125 bytesreferences/distributed-eval.mddoc11,426 bytes
Read SKILL.md
# lm-evaluation-harness - LLM Benchmarking
## Quick start
lm-evaluation-harness evaluates LLMs across 60+ academic benchmarks using standardized prompts and metrics.
**Installation**:
```bash
pip install lm-eval
```
**Evaluate any HuggingFace model**:
```bash
lm_eval --model hf \evaluating-machine-learning-models
When your agent uses it
Evaluate trained machine learning models with the right metrics and comparison logic. Use for benchmark review, threshold selection, calibration, validation, and model comparison; not for feature engineering or leakage auditing.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
324 tokensWhen the skill is activated
Reference documents
233 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
assets/visualization_script.pyscripts/data_loader.pyscripts/evaluate_model.pyscripts/metrics_calculator.py
Files
SKILL.mdcore1,560 bytesassets/README.mddoc359 bytesassets/visualization_script.pyruns5,661 bytesreferences/README.mddoc397 bytesscripts/README.mddoc407 bytesscripts/data_loader.pyruns2,836 bytesscripts/evaluate_model.pyruns2,888 bytesscripts/metrics_calculator.pyruns2,918 bytes
Read SKILL.md
# Model Evaluation Suite
Use this skill when the model exists and the question is whether it is good enough.
## Overview
This skill focuses on choosing and interpreting the right evaluation metrics for the problem, then comparing candidate models or thresholds.
## When to Use This Skill
- Comparing candidate models with consistent metrics
- Reviewing precision/recall/F1/AUC, regression error, calibration, or ranking quality
- Stress-testing validation strategy before deployment or publication
## Not For / Boundariesexplaining-machine-learning-models
When your agent uses it
Explain trained machine learning models through feature attribution, local explanations, and behavior summaries. Use as an explicit/manual helper once a model already exists, not for training ownership, leakage auditing, or general ML strategy selection.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
312 tokensWhen the skill is activated
Reference documents
274 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/data_preprocessing.pyscripts/explain_model.pyscripts/feature_importance.py
Files
SKILL.mdcore1,530 bytesassets/README.mddoc362 bytesassets/example_explanation.jsonasset3,568 bytesassets/explanation_template.htmlasset3,929 bytesassets/visualization_styles.cssasset2,589 bytesreferences/README.mddoc551 bytesscripts/README.mddoc407 bytesscripts/data_preprocessing.pyruns2,857 bytesscripts/explain_model.pyruns2,925 bytesscripts/feature_importance.pyruns2,881 bytes
Read SKILL.md
# Model Explainability Tool
## Positioning
Treat this skill as an explicit/manual helper for interpretability work.
## When to Use
Use this skill when:
- Understand why a machine learning model made a specific prediction.
- Identify the most important features influencing a model's output.
- Debug model performance issues by identifying unexpected feature interactions.
- Communicate model insights to non-technical stakeholders.
- Ensure fairness and transparency in model predictions.
exploratory-data-analysis
When your agent uses it
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
What it loads into context
Frontmatter
91 tokensAlways available to the agent
SKILL.md
3,320 tokensWhen the skill is activated
Reference documents
27,252 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Supported File Categories
- Workflow
- Detailed Format References
- Best Practices
- Examples
- Troubleshooting
- Script Usage
- Advanced Usage
- Resources
Scripts executed separately
scripts/eda_analyzer.py
Files
SKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesSKILL.mdcore14,253 bytesassets/report_template.mddoc3,488 bytesreferences/bioinformatics_genomics_formats.mddoc21,163 bytesreferences/chemistry_molecular_formats.mddoc22,029 bytesreferences/general_scientific_formats.mddoc15,287 bytesreferences/microscopy_imaging_formats.mddoc18,549 bytesreferences/proteomics_metabolomics_formats.mddoc15,543 bytesreferences/spectroscopy_analytical_formats.mddoc18,073 bytesscripts/eda_analyzer.pyruns21,318 bytes
Read SKILL.md
# Exploratory Data Analysis
## Overview
Perform comprehensive exploratory data analysis (EDA) on scientific data files across multiple domains. This skill provides automated file type detection, format-specific analysis, data quality assessment, and generates detailed markdown reports suitable for documentation and downstream analysis planning.
**Key Capabilities:**
- Automatic detection and analysis of 200+ scientific file formats
- Comprehensive format-specific metadata extraction
- Data quality and integrity assessment
- Statistical summaries and distributions
- Visualization recommendations
- Downstream analysis suggestions
- Markdown report generationfda-database
When your agent uses it
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
3,455 tokensWhen the skill is activated
Reference documents
20,840 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- FDA Database Categories
- Common Query Patterns
- Working with Results
- Best Practices
- API Reference
- Scripts
- Additional Resources
- Support and Troubleshooting
Scripts executed separately
scripts/fda_examples.pyscripts/fda_query.py
Files
SKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesSKILL.mdcore14,422 bytesreferences/animal_veterinary.mddoc11,799 bytesreferences/api_basics.mddoc15,948 bytesreferences/devices.mddoc18,934 bytesreferences/drugs.mddoc13,903 bytesreferences/foods.mddoc10,789 bytesreferences/other.mddoc13,735 bytesscripts/fda_examples.pyruns10,785 bytesscripts/fda_query.pyruns15,411 bytes
Read SKILL.md
# FDA Database Access
## Overview
Access comprehensive FDA regulatory data through openFDA, the FDA's initiative to provide open APIs for public datasets. Query information about drugs, medical devices, foods, animal/veterinary products, and substances using Python with standardized interfaces.
**Key capabilities:**
- Query adverse events for drugs, devices, foods, and veterinary products
- Access product labeling, approvals, and regulatory submissions
- Monitor recalls and enforcement actions
- Look up National Drug Codes (NDC) and substance identifiers (UNII)
- Analyze device classifications and clearances (510k, PMA)
- Track drug shortages and supply issues
- Research chemical structures and substance relationshipsfigma-implement-design
When your agent uses it
Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.
What it loads into context
Frontmatter
82 tokensAlways available to the agent
SKILL.md
2,805 tokensWhen the skill is activated
Reference documents
1,091 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Prerequisites
- Required Workflow
- Implementation Rules
- Examples
- Best Practices
- Common Issues and Solutions
- Understanding Design Implementation
- Additional Resources
Files
LICENSE.txtdoc11,358 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesSKILL.mdcore11,841 bytesagents/openai.yamlasset488 bytesassets/figma-small.svgasset818 bytesassets/figma.pngasset1,612 bytesassets/icon.svgasset964 bytesreferences/figma-mcp-config.mddoc2,231 bytesreferences/figma-tools-and-prompts.mddoc2,378 bytes
Read SKILL.md
# Implement Design
## Overview
This skill provides a structured workflow for translating Figma designs into production-ready code with pixel-perfect accuracy. It ensures consistent integration with the Figma MCP server, proper use of design tokens, and 1:1 visual parity with designs.
## Prerequisites
- Figma MCP server must be connected and accessible
- User must provide a Figma URL in the format: `https://figma.com/design/:fileKey/:fileName?node-id=1-2`
- `:fileKey` is the file key
- `1-2` is the node ID (the specific component or frame to implement)
- **OR** when using `figma-desktop` MCP: User can select a node directly in the Figma desktop app (no URL required)file-organizer
When your agent uses it
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
2,765 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- What This Skill Does
- How to Use
- Instructions
- Common Organization Tasks
- Pro Tips
- Best Practices
- Related Use Cases
Files
SKILL.mdcore11,312 bytesSKILL.mdcore11,312 bytesSKILL.mdcore11,312 bytesSKILL.mdcore11,312 bytesSKILL.mdcore11,312 bytesSKILL.mdcore11,312 bytes
Read SKILL.md
# File Organizer
This skill acts as your personal organization assistant, helping you maintain a clean, logical file structure across your computer without the mental overhead of constant manual organization.
## When to Use This Skill
- Your Downloads folder is a chaotic mess
- You can't find files because they're scattered everywhere
- You have duplicate files taking up space
- Your folder structure doesn't make sense anymore
- You want to establish better organization habits
- You're starting a new project and need a good structure
- You're cleaning up before archiving old projects
flashrag-evidence
When your agent uses it
Local evidence retrieval (FlashRAG-style) for VCO/vibe: search protocols/config/skills docs and return citeable snippets with file+line anchors.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
735 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Inputs
- Default corpus (evidence plane)
- Workflow (Lite, no heavy deps)
- Outputs
- Notes (non-redundancy)
Scripts executed separately
scripts/flashrag_evidence.py
Files
SKILL.mdcore2,769 bytesSKILL.mdcore2,769 bytesSKILL.mdcore2,769 bytesscripts/flashrag_evidence.pyruns12,666 bytes
Read SKILL.md
# FlashRAG Evidence (VCO)
## When to use
Use this skill when you need **grounded, citeable evidence** from local documentation/configuration to support VCO decisions or recommendations, especially for:
- VCO routing / pack selection rationale
- Protocol compliance (think/do/review/team/retro)
- Config semantics (thresholds, overlays, governance)
- “Show me where this rule comes from” / “give me the exact snippet”
This skill is **not** a replacement for GitNexus (code dependency graph) or web search. It focuses on **local docs and config**.
## Inputsfluidsim
When your agent uses it
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
2,593 tokensWhen the skill is activated
Reference documents
7,210 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- Core Capabilities
- Common Use Cases
- Quick Reference
- Resources
Files
SKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesSKILL.mdcore9,724 bytesreferences/advanced_features.mddoc9,011 bytesreferences/installation.mddoc1,204 bytesreferences/output_analysis.mddoc6,027 bytesreferences/parameters.mddoc4,936 bytesreferences/simulation_workflow.mddoc3,862 bytesreferences/solvers.mddoc2,419 bytes
Read SKILL.md
# FluidSim
## Routing Boundary
Use this skill only for FluidSim or explicit CFD workflows such as Navier-Stokes, turbulence, shallow-water, stratified-flow, or pseudospectral fluid simulations. Do not use it for CSS fluid layouts, responsive design, generic Python simulation, generic PDE solving, or non-FluidSim numerical physics work.
## Overview
FluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran/C++ while maintaining Python's ease of use.
**Key strengths**:
- Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
- High performance: Pythran/Transonic compilation, MPI parallelization
- Complete workflow: Parameter configuration, simulation execution, output analysisfred-economic-data
When your agent uses it
Query FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring U.S. and international economic indicators.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
2,724 tokensWhen the skill is activated
Reference documents
22,228 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- API Key Setup
- Quick Start
- Popular Economic Series
- API Endpoint Categories
- Data Transformations
- Frequency Aggregation
- Real-Time (Vintage) Data
- Common Patterns
- Error Handling
- Rate Limits
- Reference Documentation
- Scripts
- Additional Resources
Scripts executed separately
scripts/fred_examples.pyscripts/fred_query.py
Files
SKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesSKILL.mdcore11,165 bytesreferences/api_basics.mddoc4,569 bytesreferences/categories.mddoc10,766 bytesreferences/geofred.mddoc13,999 bytesreferences/releases.mddoc15,990 bytesreferences/series.mddoc14,479 bytesreferences/sources.mddoc10,654 bytesreferences/tags.mddoc11,321 bytesscripts/fred_examples.pyruns10,384 bytesscripts/fred_query.pyruns18,948 bytes
Read SKILL.md
# FRED Economic Data Access
## Overview
Access comprehensive economic data through FRED (Federal Reserve Economic Data), a database maintained by the Federal Reserve Bank of St. Louis containing over 800,000 economic time series from over 100 sources.
**Key capabilities:**
- Query economic time series data (GDP, unemployment, inflation, interest rates)
- Search and discover series by keywords, tags, and categories
- Access historical data and vintage (revision) data via ALFRED
- Retrieve release schedules and data publication dates
- Map regional economic data with GeoFRED
- Apply data transformations (percent change, log, etc.)
G2 Legend Expert
When your agent uses it
Expert skill for G2 legend development - provides comprehensive knowledge about legend rendering implementation, component architecture, layout algorithms, and interaction handling. Use when implementing, customizing, or debugging legend functionality in G2 visualizations.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,690 tokensWhen the skill is activated
Reference documents
672 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Legend Rendering Flow in G2
- Legend Types and Configuration
- Interaction Handling
- Customization and Theming
- Best Practices
- Troubleshooting Common Issues
- References
Files
SKILL.mdcore8,374 bytesknowledge/legendLayout.mddoc2,671 bytes
Read SKILL.md
# G2 Legend Expert Skill
## Overview
This skill provides comprehensive knowledge about legend rendering in G2, covering the complete legend rendering flow from component creation to layout calculation and interaction handling.
## Legend Rendering Flow in G2
The legend rendering flow in G2 follows a multi-stage process that transforms legend configuration into visual components. This flow involves several key stages:
### 1. Legend Component Inference
Legend components are inferred from the chart's scales and configuration during the initial setup phase. The inference process is handled by the `inferComponent` function in `src/runtime/component.ts`:
generate-image
When your agent uses it
Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.
What it loads into context
Frontmatter
101 tokensAlways available to the agent
SKILL.md
1,611 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Quick Start
- API Key Setup
- Model Selection
- Common Usage Patterns
- Script Parameters
- Example Use Cases
- Error Handling
- Notes
- Image Editing Tips
- Integration with Other Skills
Scripts executed separately
scripts/generate_image.py
Files
SKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesSKILL.mdcore7,047 bytesscripts/generate_image.pyruns8,815 bytes
Read SKILL.md
# Generate Image
Generate and edit high-quality images using OpenRouter's image generation models including FLUX.2 Pro and Gemini 3.1 Flash Image Preview.
## When to Use This Skill
**Use generate-image for:**
- Photos and photorealistic images
- Artistic illustrations and artwork
- Concept art and visual concepts
- Visual assets for presentations or documents
- Image editing and modifications
- Any general-purpose image generation needs
generating-test-reports
When your agent uses it
Generate structured test reports with pass/fail rollups, coverage summaries, and test artifacts. Use when the user is asking for test-result packaging or delivery, not for root-cause debugging or feature implementation.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
315 tokensWhen the skill is activated
Reference documents
259 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/aggregate_results.pyscripts/analyze_trends.pyscripts/generate_report.py
Files
SKILL.mdcore1,407 bytesassets/README.mddoc285 bytesassets/example_config.yamlasset2,653 bytesassets/report_template.htmlasset3,693 bytesassets/sample_test_results.jsonasset3,665 bytesreferences/README.mddoc387 bytesscripts/README.mddoc592 bytesscripts/aggregate_results.pyruns2,949 bytesscripts/analyze_trends.pyruns4,854 bytesscripts/generate_report.pyruns3,739 bytes
Read SKILL.md
# Test Report Generator
## Purpose
Use this skill when the next deliverable is a readable test report rather than another round of debugging.
## When to Use
Use this skill when:
- Summarizing pass/fail status, flaky tests, or coverage output for others to read
- Turning raw `pytest`, JUnit, or coverage artifacts into a concise report
- Producing release, QA, or review-facing test documentation
## Not For / Boundaries
geo-database
When your agent uses it
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
5,834 tokensWhen the skill is activated
Reference documents
5,560 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Installation and Setup
- Common Use Cases
- Key Concepts
- GEO2R Web Tool
- Rate Limiting and Best Practices
- Resources
- Important Notes
- Additional Resources
Files
SKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesSKILL.mdcore24,528 bytesreferences/geo_reference.mddoc21,102 bytes
Read SKILL.md
# GEO Database
## Overview
The Gene Expression Omnibus (GEO) is NCBI's public repository for high-throughput gene expression and functional genomics data. GEO contains over 264,000 studies with more than 8 million samples from both array-based and sequence-based experiments.
## When to Use This Skill
This skill should be used when searching for gene expression datasets, retrieving experimental data, downloading raw and processed files, querying expression profiles, or integrating GEO data into computational analysis workflows.
## Core Capabilities
### 1. Understanding GEO Data Organization
geomaster
When your agent uses it
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
What it loads into context
Frontmatter
151 tokensAlways available to the agent
SKILL.md
5,345 tokensWhen the skill is activated
Reference documents
34,238 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Installation
- Quick Start
- Core Concepts
- Common Operations
- Detailed Documentation
- Common Workflows
- Performance Tips
- Best Practices
Files
README.mddoc3,219 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesSKILL.mdcore19,663 bytesreferences/advanced-gis.mddoc10,745 bytesreferences/big-data.mddoc8,455 bytesreferences/code-examples.mddoc12,492 bytesreferences/core-libraries.mddoc6,593 bytesreferences/data-sources.mddoc9,001 bytesreferences/gis-software.mddoc8,915 bytesreferences/industry-applications.mddoc13,071 bytesreferences/machine-learning.mddoc12,783 bytesreferences/programming-languages.mddoc9,302 bytesreferences/remote-sensing.mddoc10,104 bytesreferences/scientific-domains.mddoc10,611 bytesreferences/specialized-topics.mddoc10,686 bytes
Read SKILL.md
# GeoMaster
GeoMaster is a comprehensive geospatial science skill covering the full spectrum of geographic information systems, remote sensing, spatial analysis, and machine learning for Earth observation. This skill provides expert knowledge across 70+ topics with 500+ code examples in 7 programming languages.
## Installation
### Core Python Geospatial Stack
```bash
# Install via conda (recommended for geospatial dependencies)
conda install -c conda-forge gdal rasterio fiona shapely pyproj geopandas
# Or via uv
uv pip install geopandas rasterio fiona shapely pyprojgeopandas
When your agent uses it
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
What it loads into context
Frontmatter
147 tokensAlways available to the agent
SKILL.md
1,769 tokensWhen the skill is activated
Reference documents
6,744 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Installation
- Quick Start
- Core Concepts
- Common Operations
- Detailed Documentation
- Common Workflows
- Performance Tips
- Best Practices
Files
SKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesSKILL.mdcore7,116 bytesreferences/crs-management.mddoc4,835 bytesreferences/data-io.mddoc3,690 bytesreferences/data-structures.mddoc1,638 bytesreferences/geometric-operations.mddoc4,183 bytesreferences/spatial-analysis.mddoc4,816 bytesreferences/visualization.mddoc5,415 bytes
Read SKILL.md
# GeoPandas
GeoPandas extends pandas to enable spatial operations on geometric types. It combines the capabilities of pandas and shapely for geospatial data analysis.
## Installation
```bash
uv pip install geopandas
```
### Optional Dependencies
```bash
# For interactive mapsget-available-resources
When your agent uses it
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
What it loads into context
Frontmatter
135 tokensAlways available to the agent
SKILL.md
2,299 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- How This Skill Works
- Usage Instructions
- Dependencies
- Platform Support
- Best Practices
- Troubleshooting
Scripts executed separately
scripts/detect_resources.py
Files
SKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesSKILL.mdcore9,836 bytesscripts/detect_resources.pyruns14,081 bytes
Read SKILL.md
# Get Available Resources
## Overview
Detect available computational resources and generate strategic recommendations for scientific computing tasks. This skill automatically identifies CPU capabilities, GPU availability (NVIDIA CUDA, AMD ROCm, Apple Silicon Metal), memory constraints, and disk space to help make informed decisions about computational approaches.
## When to Use This Skill
Use this skill proactively before any computationally intensive task:
- **Before data analysis**: Determine if datasets can be loaded into memory or require out-of-core processing
- **Before model training**: Check if GPU acceleration is available and which backend to use
- **Before parallel processing**: Identify optimal number of workers for joblib, multiprocessing, or Dask
- **Before large file operations**: Verify sufficient disk space and appropriate storage strategiesgh-address-comments
When your agent uses it
Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
283 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 1) Inspect comments needing attention
- 2) Ask the user for clarification
- 3) If user chooses comments
Scripts executed separately
scripts/fetch_comments.py
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore1,278 bytesagents/openai.yamlasset303 bytesassets/github-small.svgasset853 bytesassets/github.pngasset1,838 bytesscripts/fetch_comments.pyruns6,537 bytes
Read SKILL.md
# PR Comment Handler
Guide to find the open PR for the current branch and address its comments with gh CLI. Run all `gh` commands with elevated network access.
Prereq: ensure `gh` is authenticated (for example, run `gh auth login` once), then run `gh auth status` with escalated permissions (include workflow/repo scopes) so `gh` commands succeed. If sandboxing blocks `gh auth status`, rerun it with `sandbox_permissions=require_escalated`.
## 1) Inspect comments needing attention
- Run scripts/fetch_comments.py which will print out all the comments and review threads on the PR
## 2) Ask the user for clarification
- Number all the review threads and comments and provide a short summary of what would be required to apply a fix for it
- Ask the user which numbered comments should be addressed
## 3) If user chooses commentsgh-fix-ci
When your agent uses it
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
What it loads into context
Frontmatter
78 tokensAlways available to the agent
SKILL.md
898 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Inputs
- Quick start
- Workflow
- Bundled Resources
Scripts executed separately
scripts/inspect_pr_checks.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore3,651 bytesSKILL.mdcore3,651 bytesSKILL.mdcore3,651 bytesSKILL.mdcore3,651 bytesSKILL.mdcore3,651 bytesSKILL.mdcore3,651 bytesagents/openai.yamlasset302 bytesassets/github-small.svgasset853 bytesassets/github.pngasset1,838 bytesscripts/inspect_pr_checks.pyruns15,222 bytes
Read SKILL.md
# Gh Pr Checks Plan Fix
## Overview
Use gh to locate failing PR checks, fetch GitHub Actions logs for actionable failures, summarize the failure snippet, then propose a fix plan and implement after explicit approval.
- If a plan-oriented skill (for example `create-plan`) is available, use it; otherwise draft a concise plan inline and request approval before implementing.
Prereq: authenticate with the standard GitHub CLI once (for example, run `gh auth login`), then confirm with `gh auth status` (repo + workflow scopes are typically required).
## Inputs
- `repo`: path inside the repo (default `.`)
- `pr`: PR number or URL (optional; defaults to current branch PR)gradient-methods
When your agent uses it
Problem-solving strategies for gradient methods in optimization
What it loads into context
Frontmatter
27 tokensAlways available to the agent
SKILL.md
1,054 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Decision Tree
- Tool Commands
- Key Techniques
- Cognitive Tools Reference
Files
SKILL.mdcore4,066 bytesSKILL.mdcore4,066 bytesSKILL.mdcore4,066 bytesSKILL.mdcore4,066 bytes
Read SKILL.md
# Gradient Methods
## When to Use
Use this skill when working on gradient-methods problems in optimization.
## Decision Tree
1. **Basic Gradient Descent**
- Update: x_{k+1} = x_k - alpha * grad f(x_k)
- Step size alpha: fixed, diminishing, or line search
- Convergence: O(1/k) for convex, linear for strongly convex
gtars
When your agent uses it
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
What it loads into context
Frontmatter
54 tokensAlways available to the agent
SKILL.md
1,755 tokensWhen the skill is activated
Reference documents
5,565 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Installation
- Core Capabilities
- Common Workflows
- Python vs CLI Usage
- Reference Documentation
- Integration with geniml
- Performance Characteristics
- Data Formats
- Error Handling and Debugging
Files
SKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesreferences/cli.mddoc5,060 bytesreferences/coverage.mddoc3,995 bytesreferences/overlap.mddoc3,679 bytesreferences/python-api.mddoc4,222 bytesreferences/refget.mddoc3,165 bytesreferences/tokenizers.mddoc2,444 bytes
Read SKILL.md
# Gtars: Genomic Tools and Algorithms in Rust
## Overview
Gtars is a high-performance Rust toolkit for manipulating, analyzing, and processing genomic interval data. It provides specialized tools for overlap detection, coverage analysis, tokenization for machine learning, and reference sequence management.
Use this skill when working with:
- Genomic interval files (BED format)
- Overlap detection between genomic regions
- Coverage track generation (WIG, BigWig)
- Genomic ML preprocessing and tokenization
- Fragment analysis in single-cell genomics
- Reference sequence retrieval and validation
hedgefundmonitor
When your agent uses it
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
What it loads into context
Frontmatter
141 tokensAlways available to the agent
SKILL.md
1,547 tokensWhen the skill is activated
Reference documents
9,159 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Authentication
- Datasets
- Data Categories
- Core Endpoints
- Common Parameters
- Key FPF Mnemonic Patterns
- Reference Files
Files
SKILL.mdcore6,002 bytesSKILL.mdcore6,002 bytesSKILL.mdcore6,002 bytesreferences/api-overview.mddoc2,429 bytesreferences/datasets.mddoc5,827 bytesreferences/endpoints-combined.mddoc5,849 bytesreferences/endpoints-metadata.mddoc4,439 bytesreferences/endpoints-series-data.mddoc3,640 bytesreferences/examples.mddoc7,886 bytesreferences/parameters.mddoc3,329 bytes
Read SKILL.md
# OFR Hedge Fund Monitor API
Free, open REST API from the U.S. Office of Financial Research (OFR) providing aggregated hedge fund time series data. No API key or registration required.
**Base URL:** `https://data.financialresearch.gov/hf/v1`
## Quick Start
```python
import requests
import pandas as pd
BASE = "https://data.financialresearch.gov/hf/v1"
histolab
When your agent uses it
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
What it loads into context
Frontmatter
84 tokensAlways available to the agent
SKILL.md
4,564 tokensWhen the skill is activated
Reference documents
12,048 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- Installation
- Quick Start
- Core Capabilities
- Typical Workflows
- Best Practices
- Common Use Cases
- Troubleshooting
- Resources
Files
SKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesSKILL.mdcore20,520 bytesreferences/filters_preprocessing.mddoc12,700 bytesreferences/slide_management.mddoc4,701 bytesreferences/tile_extraction.mddoc11,297 bytesreferences/tissue_masks.mddoc7,232 bytesreferences/visualization.mddoc13,970 bytes
Read SKILL.md
# Histolab
## Overview
Histolab is a Python library for processing whole slide images (WSI) in digital pathology. It automates tissue detection, extracts informative tiles from gigapixel images, and prepares datasets for deep learning pipelines. The library handles multiple WSI formats, implements sophisticated tissue segmentation, and provides flexible tile extraction strategies.
## Routing Boundary
Use this skill for basic WSI tile extraction, tissue detection, H&E tile preprocessing, and quick histolab dataset preparation. Full computational pathology workflows, PathML pipelines, nucleus segmentation, spatial pathology, multiplex pathology, DICOM/IDC retrieval, OMERO server work, and generic image-processing tasks are outside this skill.
## Installation
```bash
uv pip install histolabhive-mind-advanced
When your agent uses it
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
What it loads into context
Frontmatter
71 tokensAlways available to the agent
SKILL.md
3,908 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Concepts
- Getting Started
- Advanced Workflows
- Integration Patterns
- Performance Optimization
- Configuration
- Hooks Integration
- Best Practices
- Troubleshooting
- Advanced Topics
- API Reference
- Examples
- Skill Progression
- Related Skills
- References
Files
SKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytesSKILL.mdcore16,723 bytes
Read SKILL.md
# Hive Mind Advanced Skill
Master the advanced Hive Mind collective intelligence system for sophisticated multi-agent coordination using queen-led architecture, Byzantine consensus, and collective memory.
## Overview
The Hive Mind system represents the pinnacle of multi-agent coordination in Claude Flow, implementing a queen-led hierarchical architecture where a strategic queen coordinator directs specialized worker agents through collective decision-making and shared memory.
## Core Concepts
### Architecture Patterns
**Queen-Led Coordination**
- Strategic queen agents orchestrate high-level objectiveshypothesis-generation
When your agent uses it
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Also owns explicit HypoGeniC-style or automated LLM-driven hypothesis generation/testing requests inside this single skill. For open-ended ideation use scientific-brainstorming.
What it loads into context
Frontmatter
100 tokensAlways available to the agent
SKILL.md
2,539 tokensWhen the skill is activated
Reference documents
14,060 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Outputs
- Workflow
- Quality Standards
- Resources
Files
SKILL.mdcore12,462 bytesSKILL.mdcore12,462 bytesassets/FORMATTING_GUIDE.mddoc19,304 bytesassets/hypothesis_generation.styasset7,625 bytesassets/hypothesis_report_template.texasset20,148 bytesreferences/experimental_design_patterns.mddoc14,208 bytesreferences/hypothesis_quality_criteria.mddoc8,051 bytesreferences/literature_search_strategies.mddoc20,277 bytes
Read SKILL.md
# Scientific Hypothesis Generation
## Overview
Hypothesis generation is a systematic process for developing testable explanations. Formulate evidence-based hypotheses from observations, design experiments, explore competing explanations, and develop predictions. Apply this skill for scientific inquiry across domains.
## When to Use This Skill
This skill should be used when:
- Developing hypotheses from observations or preliminary data
- Designing experiments to test scientific questions
- Exploring competing explanations for phenomena
- Formulating testable predictions for research
- Conducting literature-based hypothesis generationhypothesis-testing
When your agent uses it
Property-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains. Triggered by: hypothesis, property-based testing, @given, strategies, generative testing.
What it loads into context
Frontmatter
102 tokensAlways available to the agent
SKILL.md
5,761 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Core Concept
- Installation
- Configuration
- Basic Usage
- Strategies
- Advanced Patterns
- When to Use Hypothesis vs Example-Based Tests
- Best Practices
- Common Patterns
- CI Integration
- Debugging Failing Tests
- Resources
- Summary
Files
SKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytesSKILL.mdcore23,245 bytes
Read SKILL.md
# Hypothesis Property-Based Testing
Hypothesis is a powerful property-based testing library that automatically generates test cases to find edge cases and validate properties of your code.
## Core Concept
**Traditional example-based testing:**
```python
def test_addition():
assert add(2, 3) == 5
assert add(0, 0) == 0
assert add(-1, 1) == 0
```
imagegen
When your agent uses it
Use when the user asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (`scripts/image_gen.py`) and require `OPENAI_API_KEY` for live calls.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
2,206 tokensWhen the skill is activated
Reference documents
6,697 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree (generate vs edit vs batch)
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Defaults & rules
- Prompt augmentation
- Use-case taxonomy (exact slugs)
- Examples
- Prompting best practices (short list)
- Guidance by asset type
- CLI + environment notes
- Reference map
Scripts executed separately
scripts/image_gen.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore9,916 bytesagents/openai.yamlasset291 bytesassets/imagegen-small.svgasset2,889 bytesassets/imagegen.pngasset1,711 bytesreferences/cli.mddoc5,288 bytesreferences/codex-network.mddoc1,146 bytesreferences/image-api.mddoc1,629 bytesreferences/prompting.mddoc5,903 bytesreferences/sample-prompts.mddoc14,901 bytesscripts/image_gen.pyruns29,949 bytes
Read SKILL.md
# Image Generation Skill
Generates or edits images for the current project (e.g., website assets, game assets, UI mockups, product mockups, wireframes, logo design, photorealistic images, infographics). Defaults to `gpt-image-1.5` and the OpenAI Image API, and prefers the bundled CLI for deterministic, reproducible runs.
## When to use
- Generate a new image (concept art, product shot, cover, website hero)
- Edit an existing image (inpainting, masked edits, lighting or weather transformations, background replacement, object removal, compositing, transparent background)
- Batch runs (many prompts, or many variants across prompts)
## Decision tree (generate vs edit vs batch)
- If the user provides an input image (or says “edit/retouch/inpaint/mask/translate/localize/change only X”) → **edit**
- Else if the user needs many different prompts/assets → **generate-batch**
- Else → **generate**imaging-data-commons
When your agent uses it
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
What it loads into context
Frontmatter
170 tokensAlways available to the agent
SKILL.md
8,126 tokensWhen the skill is activated
Reference documents
23,345 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- When to Use This Skill
- Quick Navigation
- IDC Data Model
- Index Tables
- Data Access Options
- Installation and Setup
- Core Capabilities
- Common Use Cases
- Best Practices
- Troubleshooting
- Common SQL Query Patterns
- Related Skills
- Resources
Files
SKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesSKILL.mdcore34,791 bytesreferences/bigquery_guide.mddoc18,766 bytesreferences/cli_guide.mddoc7,742 bytesreferences/clinical_data_guide.mddoc11,757 bytesreferences/cloud_storage_guide.mddoc14,065 bytesreferences/dicomweb_guide.mddoc14,985 bytesreferences/digital_pathology_guide.mddoc9,507 bytesreferences/index_tables_guide.mddoc6,864 bytesreferences/sql_patterns.mddoc7,153 bytesreferences/use_cases.mddoc5,370 bytes
Read SKILL.md
# Imaging Data Commons
## Overview
Use the `idc-index` Python package to query and download public cancer imaging data from the National Cancer Institute Imaging Data Commons (IDC). No authentication required for data access.
## Routing Boundary
Use this skill for NCI Imaging Data Commons, IDC, TCIA cancer imaging cohorts, DICOMWeb, public cancer imaging data, radiology datasets, and DICOM imaging cohort retrieval. This is not generic Data Commons, public statistical data, population indicators, statistical variables, DCIDs, PubMed, ClinicalTrials.gov, or generic public dataset search.
**Current IDC Data Version: v23** (always verify with `IDCClient().get_idc_version()`)
**Primary tool:** `idc-index` ([GitHub](https://github.com/imagingdatacommons/idc-index))
infographics
When your agent uses it
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
4,135 tokensWhen the skill is activated
Reference documents
16,091 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start
- When to Use This Skill
- Research Integration
- Infographic Types
- Style Presets
- Colorblind-Safe Palettes
- Smart Iterative Refinement
- Command-Line Reference
- Configuration
- Prompt Engineering Tips
- Reference Files
- Troubleshooting
- Integration with Other Skills
- Quick Reference Checklist
Scripts executed separately
scripts/generate_infographic.pyscripts/generate_infographic_ai.py
Files
SKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesSKILL.mdcore18,071 bytesreferences/color_palettes.mddoc14,120 bytesreferences/design_principles.mddoc19,080 bytesreferences/infographic_types.mddoc28,996 bytesscripts/generate_infographic.pyruns10,198 bytesscripts/generate_infographic_ai.pyruns49,715 bytes
Read SKILL.md
# Infographics
## Overview
Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. **This skill uses Nano Banana Pro AI for infographic generation with Gemini 3 Pro quality review and Perplexity Sonar for research.**
**How it works:**
- (Optional) **Research phase**: Gather accurate facts and statistics using Perplexity Sonar
- Describe your infographic in natural language
- Nano Banana Pro generates publication-quality infographics automatically
- **Gemini 3 Pro reviews quality** against document-type thresholds
- **Smart iteration**: Only regenerates if quality is below threshold
- Professional-ready output in minutes
- No design skills requirediso-13485-certification
When your agent uses it
Comprehensive toolkit for preparing ISO 13485 certification documentation for medical device Quality Management Systems. Use when users need help with ISO 13485 QMS documentation, including (1) conducting gap analysis of existing documentation, (2) creating Quality Manuals, (3) developing required procedures and work instructions, (4) preparing Medical Device Files, (5) understanding ISO 13485 requirements, or (6) identifying missing documentation for medical device certification. Also use when users mention medical device regulations, QMS certification, FDA QMSR, EU MDR, or need help with quality system documentation.
What it loads into context
Frontmatter
145 tokensAlways available to the agent
SKILL.md
5,298 tokensWhen the skill is activated
Reference documents
34,757 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Workflow
- Common Scenarios
- Best Practices
- Resources
- Quick Reference
- Getting Started
Scripts executed separately
scripts/gap_analyzer.py
Files
SKILL.mdcore23,248 bytesSKILL.mdcore23,248 bytesassets/templates/procedures/CAPA-procedure-template.mddoc15,055 bytesassets/templates/procedures/document-control-procedure-template.mddoc18,062 bytesassets/templates/quality-manual-template.mddoc20,618 bytesreferences/gap-analysis-checklist.mddoc27,586 bytesreferences/iso-13485-requirements.mddoc25,697 bytesreferences/mandatory-documents.mddoc21,428 bytesreferences/quality-manual-guide.mddoc26,197 bytesscripts/gap_analyzer.pyruns15,529 bytes
Read SKILL.md
# ISO 13485 Certification Documentation Assistant
## Overview
This skill helps medical device manufacturers prepare comprehensive documentation for ISO 13485:2016 certification. It provides tools, templates, references, and guidance to create, review, and gap-analyze all required Quality Management System (QMS) documentation.
**What this skill provides:**
- Gap analysis of existing documentation
- Templates for all mandatory documents
- Comprehensive requirements guidance
- Step-by-step documentation creation
- Identification of missing documentation
- Compliance checklists
jupyter-notebook
When your agent uses it
Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
929 tokensWhen the skill is activated
Reference documents
577 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree
- Skill path (set once)
- Workflow
- Templates and helper script
- Temp and output conventions
- Dependencies (install only when needed)
- Environment
- Reference map
Scripts executed separately
assets/experiment-template.ipynbassets/tutorial-template.ipynbscripts/new_notebook.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesSKILL.mdcore4,154 bytesagents/openai.yamlasset325 bytesassets/experiment-template.ipynbruns2,570 bytesassets/jupyter-small.svgasset1,043 bytesassets/jupyter.pngasset2,713 bytesassets/tutorial-template.ipynbruns2,490 bytesreferences/experiment-patterns.mddoc699 bytesreferences/notebook-structure.mddoc751 bytesreferences/quality-checklist.mddoc572 bytesreferences/tutorial-patterns.mddoc685 bytesscripts/new_notebook.pyruns4,086 bytes
Read SKILL.md
# Jupyter Notebook Skill
Create clean, reproducible Jupyter notebooks for two primary modes:
- Experiments and exploratory analysis
- Tutorials and teaching-oriented walkthroughs
Prefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes.
## When to use
- Create a new `.ipynb` notebook from scratch.
- Convert rough notes or scripts into a structured notebook.
- Refactor an existing notebook to be more reproducible and skimmable.knowledge-steward
When your agent uses it
AI工作经验知识库管理。适用于用户明确要求'保存到Obsidian'、'记录这个'、'save this insight'、'memo this'、'capture this'等知识沉淀场景。将对话中的提示词、模式、问题修复、想法和效率优化保存到Obsidian知识库，并自动同步到GitHub。
What it loads into context
Frontmatter
90 tokensAlways available to the agent
SKILL.md
3,277 tokensWhen the skill is activated
Reference documents
5,862 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Examples
- References
- GitHub Sync Feature
- Plugin 智能发现与自动使用 (ToolSearch Auto-Discovery)
- Maintenance
Scripts executed separately
scripts/distill_experience.pyscripts/git_sync.pyscripts/init_git_repos.pyscripts/parse_workflow_report.pyscripts/save_to_obsidian.pyscripts/setup_github.pyscripts/sync_skill_code.py
Files
.gitignoreasset202 bytesREADME.mddoc723 bytesSKILL.mdcore11,742 bytesSKILL.mdcore11,742 bytesSKILL.mdcore11,742 bytesSKILL.mdcore11,742 bytesSKILL.mdcore11,742 bytesassets/note-template.mddoc1,776 bytesassets/setup-guide.mddoc8,215 bytesassets/workflow-analysis-template.mddoc675 bytesconfig.example.yamlasset2,316 bytesreferences/index.mddoc8,631 bytesscripts/distill_experience.pyruns8,308 bytesscripts/git_sync.pyruns12,152 bytesscripts/init_git_repos.pyruns9,364 bytesscripts/parse_workflow_report.pyruns5,002 bytesscripts/save_to_obsidian.pyruns12,191 bytesscripts/setup_github.pyruns8,112 bytesscripts/sync_skill_code.pyruns4,972 bytes
Read SKILL.md
# Knowledge Steward Skill
你的"数字记账员"——防止智力剩余价值随着电缆流失。将稍纵即逝的灵感、有效的提示词、踩过的坑和突然的顿悟转化为永久存储的知识资产，并自动备份到GitHub云端。
## When to Use This Skill
当用户想要保存以下内容时使用此技能：
- **提示词复盘**：发现某个Prompt效果惊人地好或差时
- 触发词："保存这个提示词"、"save this prompt"、"记录这个Prompt"
- **工程排坑**：花了很长时间解决了一个Bug时
- 触发词："记录这个Bug"、"save this bugfix"、"保存解决方案"
- **灵感闪现**：突然想到一个架构优化或设计模式时
- 触发词："保存这个想法"、"capture this idea"、"记录这个灵感"lamindb
When your agent uses it
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
What it loads into context
Frontmatter
139 tokensAlways available to the agent
SKILL.md
3,252 tokensWhen the skill is activated
Reference documents
18,195 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Common Use Case Workflows
- Getting Started Checklist
- Key Principles
- Reference Files
- Additional Resources
Files
SKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesSKILL.mdcore14,300 bytesreferences/annotation-validation.mddoc12,276 bytesreferences/core-concepts.mddoc9,782 bytesreferences/data-management.mddoc10,709 bytesreferences/integrations.mddoc13,489 bytesreferences/ontologies.mddoc13,535 bytesreferences/setup-deployment.mddoc14,576 bytes
Read SKILL.md
# LaminDB
## Overview
LaminDB is an open-source data framework for biology designed to make data queryable, traceable, reproducible, and FAIR (Findable, Accessible, Interoperable, Reusable). It provides a unified platform that combines lakehouse architecture, lineage tracking, feature stores, biological ontologies, LIMS (Laboratory Information Management System), and ELN (Electronic Lab Notebook) capabilities through a single Python API.
**Core Value Proposition:**
- **Queryability**: Search and filter datasets by metadata, features, and ontology terms
- **Traceability**: Automatic lineage tracking from raw data through analysis to results
- **Reproducibility**: Version control for data, code, and environment
- **FAIR Compliance**: Standardized annotations using biological ontologies
## When to Use This Skill
latchbio-integration
When your agent uses it
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
2,277 tokensWhen the skill is activated
Reference documents
8,557 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Capabilities
- Quick Start
- When to Use This Skill
- Detailed Documentation
- Common Workflow Patterns
- Best Practices
- Troubleshooting
- Additional Resources
- Support
Files
SKILL.mdcore9,815 bytesSKILL.mdcore9,815 bytesSKILL.mdcore9,815 bytesSKILL.mdcore9,815 bytesSKILL.mdcore9,815 bytesSKILL.mdcore9,815 bytesreferences/data-management.mddoc9,737 bytesreferences/resource-configuration.mddoc9,569 bytesreferences/verified-workflows.mddoc10,472 bytesreferences/workflow-creation.mddoc6,333 bytes
Read SKILL.md
# LatchBio Integration
## Overview
Latch is a Python framework for building and deploying bioinformatics workflows as serverless pipelines. Built on Flyte, create workflows with @workflow/@task decorators, manage cloud data with LatchFile/LatchDir, configure resources, and integrate Nextflow/Snakemake pipelines.
## Core Capabilities
The Latch platform provides four main areas of functionality:
### 1. Workflow Creation and Deployment
- Define serverless workflows using Python decorators
- Support for native Python, Nextflow, and Snakemake pipelines
- Automatic containerization with Dockerlatex-posters
When your agent uses it
Use when creating or revising LaTeX research posters with beamerposter, tikzposter, or baposter, including poster layout, typography, color, print sizing, figure placement, QR codes, compilation, and print-ready PDF checks.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
7,024 tokensWhen the skill is activated
Reference documents
27,354 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Boundary
- Core Capabilities
- Workflow for Poster Creation
- Scope Boundary
- Common Pitfalls to Avoid
- Package Installation
- Scripts and Automation
- References
- Templates
Scripts executed separately
scripts/review_poster.sh
Files
README.mddoc11,654 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesSKILL.mdcore28,917 bytesassets/baposter_template.texasset7,432 bytesassets/beamerposter_template.texasset7,652 bytesassets/poster_quality_checklist.mddoc11,172 bytesassets/tikzposter_template.texasset7,887 bytesreferences/latex_poster_packages.mddoc17,836 bytesreferences/poster_content_guide.mddoc20,361 bytesreferences/poster_design_principles.mddoc22,916 bytesreferences/poster_layout_design.mddoc22,327 bytesscripts/review_poster.shruns7,939 bytes
Read SKILL.md
# LaTeX Research Posters
## Overview
Research posters are a critical medium for scientific communication at conferences, symposia, and academic events. This skill provides comprehensive guidance for creating professional, visually appealing research posters using LaTeX packages. Generate publication-quality posters with proper layout, typography, color schemes, and visual hierarchy.
## When to Use This Skill
This skill should be used when:
- Creating research posters for conferences, symposia, or poster sessions
- Designing academic posters for university events or thesis defenses
- Preparing visual summaries of research for public engagement
- Converting scientific papers into poster format
- Creating template posters for research groups or departmentslatex-submission-pipeline
When your agent uses it
Use when building a LaTeX manuscript submission pipeline with templates, latexmk, BibTeX/Biber, chktex, latexindent, CI PDF builds, compile debugging, and submission zip packaging.
What it loads into context
Frontmatter
68 tokensAlways available to the agent
SKILL.md
568 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 适用
- 最小流程（从 0 到可提交）
- 常见失败点（速查）
Files
SKILL.mdcore1,949 bytestemplates/github-actions-latex.ymlasset572 bytestemplates/latexmkrcasset115 bytes
Read SKILL.md
# LaTeX Submission Pipeline（LaTeX 投稿工程链）
## 适用
当用户需要：
- 套用期刊/会议 LaTeX 模板（ACM/IEEE/NeurIPS 等）
- 解决编译错误、引用错误、字体缺失、图片格式不兼容
- 接入 GitHub Actions 自动编译 PDF / 打包 submission zip
- 做格式化（latexindent）与 lint（chktex）
---
## 最小流程（从 0 到可提交）
literature-review
When your agent uses it
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
5,021 tokensWhen the skill is activated
Reference documents
9,003 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Workflow
- Database-Specific Search Guidance
- Citation Style Guide
- Best Practices
- Common Pitfalls to Avoid
- Example Workflow
- Resources
- Dependencies
- Summary
Scripts executed separately
scripts/generate_pdf.pyscripts/search_databases.pyscripts/verify_citations.py
Files
SKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesSKILL.mdcore21,754 bytesassets/review_template.mddoc12,982 bytesreferences/citation_styles.mddoc6,112 bytesreferences/database_strategies.mddoc15,603 bytesscripts/generate_pdf.pyruns5,410 bytesscripts/search_databases.pyruns9,036 bytesscripts/verify_citations.pyruns7,050 bytes
Read SKILL.md
# Literature Review
## Overview
Conduct systematic, comprehensive literature reviews following rigorous academic methodology. Search multiple literature sources, synthesize findings thematically, verify citations for accuracy, and generate professional output documents in markdown and PDF formats.
## When to Use This Skill
Use this skill when:
- Conducting a systematic literature review for research or publication
- Synthesizing current knowledge on a specific topic across multiple sources
- Performing meta-analysis or scoping reviews
- Writing the literature review section of a research paper or thesis
- Investigating the state of the art in a research domainlocal-vco-roles
When your agent uses it
Codex-local role pack for dialectic multi-agent reviews, designed to be compatible with the local vibe skill.
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
457 tokensWhen the skill is activated
Reference documents
698 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Vibe Compatibility Contract (Must Follow)
- Role Prompt Library
- Recommended XL Workflow
- Optional Utility
Scripts executed separately
scripts/new-run.ps1
Files
SKILL.mdcore1,937 bytesreferences/role-prompts/arch-critic.mddoc401 bytesreferences/role-prompts/bug-analyst.mddoc423 bytesreferences/role-prompts/integration-analyst.mddoc420 bytesreferences/role-prompts/team-lead.mddoc460 bytesreferences/role-prompts/usability-analyst.mddoc379 bytesreferences/vibe-compatibility.mddoc1,222 bytesscripts/new-run.ps1runs903 bytes
Read SKILL.md
# local-vco-roles
Codex-local role pack for dialectic multi-agent reviews, designed to be compatible with the local `vibe` skill.
## When to Use
Use this skill when:
1. You run `/vibe` and need a stable role set for dialectic review.
2. You want reproducible multi-role analysis using TeamCreate-style orchestration.
3. You need standardized outputs across team-lead / bug / architecture / integration / usability roles.
## Vibe Compatibility Contract (Must Follow)
1. Grade handshake:manuscript-as-code
When your agent uses it
Treat manuscripts as software: version control, reproducible builds, figure pipelines, CI, and structured repo layout. Helps teams avoid 'final_v7' chaos and ensures submission-ready artifacts.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
527 tokensWhen the skill is activated
Reference documents
235 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 目标
- 推荐仓库结构（最小可行）
- 元规则（工程化的关键）
- 案例（推荐学习）
Files
SKILL.mdcore1,861 bytesSKILL.mdcore1,861 bytestemplates/repo-structure.mddoc856 bytes
Read SKILL.md
# Manuscript as Code（论文工程化）
## 目标
把“写论文”升级成“交付可复现的出版工程”：
- 结构清晰：任何人进仓库都知道哪里改正文、哪里改图、哪里改引用
- 可复现：一条命令能构建 PDF/HTML；CI 自动验证
- 可审计：每张图/每个结果都有来源（代码/数据/参数）
适用：
- 多人协作写作（导师/合作者/跨机构）
- 反复投稿/返修（需要明确改动轨迹）
- 图表多、实验多、容易“找不到版本”的项目
markdown-mermaid-writing
When your agent uses it
Comprehensive markdown and Mermaid diagram writing skill that establishes text-based diagrams as the DEFAULT documentation standard. Use this skill when creating ANY scientific document, report, analysis, or visualization — it ensures all outputs are in version-controlled, token-efficient markdown with embedded Mermaid diagrams as the source of truth, with clear pathways to downstream Python or AI-generated images. Includes full style guides (markdown + mermaid), 24 diagram type references, and 9 document templates ready to use.
What it loads into context
Frontmatter
241 tokensAlways available to the agent
SKILL.md
3,641 tokensWhen the skill is activated
Reference documents
62,652 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- 🎨 The Source Format Philosophy
- 🔧 Core workflow
- ⚠<U+FE0F> Common pitfalls
- 🔗 Integration with other skills
- 📚 Reference index
- 📝 Attribution
Files
SKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesSKILL.mdcore15,135 bytesassets/examples/example-research-report.mddoc9,010 bytesreferences/diagrams/architecture.mddoc4,369 bytesreferences/diagrams/block.mddoc4,825 bytesreferences/diagrams/c4.mddoc6,201 bytesreferences/diagrams/class.mddoc8,521 bytesreferences/diagrams/complex_examples.mddoc17,079 bytesreferences/diagrams/er.mddoc7,601 bytesreferences/diagrams/flowchart.mddoc6,961 bytesreferences/diagrams/gantt.mddoc5,851 bytesreferences/diagrams/git_graph.mddoc2,009 bytesreferences/diagrams/kanban.mddoc3,544 bytesreferences/diagrams/mindmap.mddoc2,232 bytesreferences/diagrams/packet.mddoc1,721 bytesreferences/diagrams/pie.mddoc1,560 bytesreferences/diagrams/quadrant.mddoc2,163 bytesreferences/diagrams/radar.mddoc2,176 bytesreferences/diagrams/requirement.mddoc2,463 bytesreferences/diagrams/sankey.mddoc2,143 bytesreferences/diagrams/sequence.mddoc5,510 bytesreferences/diagrams/state.mddoc5,464 bytesreferences/diagrams/timeline.mddoc4,181 bytesreferences/diagrams/treemap.mddoc2,039 bytesreferences/diagrams/user_journey.mddoc5,049 bytesreferences/diagrams/xy_chart.mddoc1,887 bytesreferences/diagrams/zenuml.mddoc2,285 bytesreferences/markdown_style_guide.mddoc35,114 bytesreferences/mermaid_style_guide.mddoc26,433 bytestemplates/decision_record.mddoc7,169 bytestemplates/how_to_guide.mddoc7,091 bytestemplates/issue.mddoc12,835 bytestemplates/kanban.mddoc11,403 bytestemplates/presentation.mddoc8,068 bytestemplates/project_documentation.mddoc11,489 bytestemplates/pull_request.mddoc12,903 bytestemplates/research_paper.mddoc10,157 bytestemplates/status_report.mddoc7,185 bytes
Read SKILL.md
# Markdown and Mermaid Writing
## Overview
This skill teaches you — and enforces a standard for — creating scientific documentation
using **markdown with embedded Mermaid diagrams as the default and canonical format**.
The core bet: a relationship expressed as a Mermaid diagram inside a `.md` file is more
valuable than any image. It is text, so it diffs cleanly in git. It requires no build step.
It renders natively on GitHub, GitLab, Notion, VS Code, and any markdown viewer. It uses
fewer tokens than a prose description of the same relationship. And it can always be
converted to a polished image later — but the text version remains the source of truth.
> "The more you get your reports and files in .md in just regular text, which mermaid ismarket-research-reports
When your agent uses it
Generate comprehensive market research reports and industry/competitive analysis in the style of top consulting firms. Use for market sizing, competitive landscape, market entry, investment thesis, strategic recommendations, and consulting-style business reports. Do not use for scientific reports, paper writing, LaTeX submission/PDF builds, EDGAR/FRED/Treasury/Data Commons data retrieval, or biomedical literature evidence work.
What it loads into context
Frontmatter
111 tokensAlways available to the agent
SKILL.md
2,075 tokensWhen the skill is activated
Reference documents
21,497 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- When to Use This Skill
- Workflow
- Report Structure
- LaTeX Formatting
- Quality Standards
- Checklist
- Resources
Scripts executed separately
scripts/generate_market_visuals.py
Files
SKILL.mdcore9,883 bytesSKILL.mdcore9,883 bytesSKILL.mdcore9,883 bytesSKILL.mdcore9,883 bytesSKILL.mdcore9,883 bytesSKILL.mdcore9,883 bytesassets/FORMATTING_GUIDE.mddoc10,110 bytesassets/market_report_template.texasset50,218 bytesassets/market_research.styasset15,617 bytesreferences/data_analysis_patterns.mddoc17,690 bytesreferences/report_structure_guide.mddoc23,572 bytesreferences/visual_generation_guide.mddoc37,281 bytesscripts/generate_market_visuals.pyruns20,423 bytes
Read SKILL.md
# Market Research Reports
## Overview
Market research reports are strategic documents for analyzing industries, markets, and competitive landscapes. They support business decisions, investment theses, due diligence, market entry, product strategy, and executive planning.
**Key Features:**
- **Comprehensive length**: Reports are designed to be 50+ pages with no token constraints
- **Visual-rich content**: Plan the core market, competitive, risk, and roadmap visuals before drafting
- **Data-driven analysis**: Ground market claims in cited public, company, industry, and government sources
- **Multi-framework approach**: Porter's Five Forces, PESTLE, SWOT, BCG Matrix, TAM/SAM/SOM
- **Professional formatting**: Consulting-firm quality typography, colors, and layout
- **Actionable recommendations**: Strategic focus with implementation roadmaps
markitdown
When your agent uses it
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
What it loads into context
Frontmatter
81 tokensAlways available to the agent
SKILL.md
3,033 tokensWhen the skill is activated
Reference documents
6,900 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Visual Enhancement with Scientific Schematics
- Supported Formats
- Quick Start
- Advanced Features
- Optional Dependencies
- Common Use Cases
- Docker Usage
- Best Practices
- Integration with Scientific Workflows
- Troubleshooting
- Performance Considerations
- Next Steps
- Resources
Scripts executed separately
scripts/batch_convert.pyscripts/convert_literature.pyscripts/convert_with_ai.py
Files
SKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesSKILL.mdcore12,631 bytesassets/example_usage.mddoc10,378 bytesreferences/api_reference.mddoc8,851 bytesreferences/file_formats.mddoc8,985 bytesscripts/batch_convert.pyruns6,650 bytesscripts/convert_literature.pyruns8,915 bytesscripts/convert_with_ai.pyruns7,461 bytes
Read SKILL.md
# MarkItDown - File to Markdown Conversion
## Overview
MarkItDown is a Python tool developed by Microsoft for converting various file formats to Markdown. It's particularly useful for converting documents into LLM-friendly text format, as Markdown is token-efficient and well-understood by modern language models.
**Key Benefits**:
- Convert documents to clean, structured Markdown
- Token-efficient format for LLM processing
- Supports 15+ file formats
- Optional AI-enhanced image descriptions
- OCR for images and scanned documents
- Speech transcription for audio files
matchms
When your agent uses it
Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.
What it loads into context
Frontmatter
86 tokensAlways available to the agent
SKILL.md
1,645 tokensWhen the skill is activated
Reference documents
13,061 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- Core Capabilities
- Common Workflows
- Installation
- Reference Documentation
Files
SKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesSKILL.mdcore7,329 bytesreferences/filtering.mddoc10,038 bytesreferences/importing_exporting.mddoc10,894 bytesreferences/similarity.mddoc12,974 bytesreferences/workflows.mddoc22,230 bytes
Read SKILL.md
# Matchms
## Routing Boundary
Use this skill only for matchms, mass spectra, MS/MS spectrum processing, spectral similarity, and metabolomics spectrum workflows. Do not use it for PubMed searches, generic chemistry, non-spectral metabolomics, plotting-only requests, or literature review tasks that do not process mass spectra.
## Overview
Matchms is an open-source Python library for mass spectrometry data processing and analysis. Import spectra from various formats, standardize metadata, filter peaks, calculate spectral similarities, and build reproducible analytical workflows.
## Core Capabilities
### 1. Importing and Exporting Mass Spectrometry Data
math
When your agent uses it
Unified math capabilities - computation, solving, and explanation. I route to the right tool.
What it loads into context
Frontmatter
101 tokensAlways available to the agent
SKILL.md
1,821 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Examples
- Computation Scripts
- Topic Skills (For Explanation)
- Routing Logic
- Examples
- When to Use /prove Instead
Files
SKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytesSKILL.mdcore6,251 bytes
Read SKILL.md
# /math - Unified Math Capabilities
**One entry point for all computation and explanation.** I route to the right tool based on your request.
For formal proofs, use `/prove` instead.
---
## Quick Examples
| You Say | I Use |
|---------|-------|
| "Solve x² - 4 = 0" | SymPy solve |
| "Integrate sin(x) from 0 to π" | SymPy integrate |math-model-selector
When your agent uses it
Routes problems to appropriate mathematical frameworks using expert heuristics
What it loads into context
Frontmatter
18 tokensAlways available to the agent
SKILL.md
762 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Process
- Key Questions to Ask
- Output Format
- Example Interaction
- Co-activates
Files
SKILL.mdcore3,362 bytes
Read SKILL.md
# Math Model Selector
## When to Use
Trigger on phrases like:
- "what math should I use"
- "which mathematical framework"
- "how do I model this"
- "what kind of problem is this"
- "formalize this problem"
Use when user has a problem but doesn't know which mathematical domain applies.
## Processmath-tools
When your agent uses it
Deterministic mathematical computation using SymPy. Use for ANY math operation requiring exact/verified results - basic arithmetic, algebra (simplify, expand, factor, solve equations), calculus (derivatives, integrals, limits, series), linear algebra (matrices, determinants, eigenvalues), trigonometry, number theory (primes, GCD/LCM, factorization), and statistics. Ensures mathematical accuracy by using symbolic computation rather than LLM estimation.
What it loads into context
Frontmatter
101 tokensAlways available to the agent
SKILL.md
1,493 tokensWhen the skill is activated
Reference documents
2,546 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Quick Start
- Core Operations
- Expression Syntax
- Complex Operations (JSON Input)
- Full API Reference
- Dependencies
Scripts executed separately
scripts/math_calculator.py
Files
SKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesSKILL.mdcore5,075 bytesreferences/api_reference.mddoc8,181 bytesscripts/math_calculator.pyruns17,337 bytes
Read SKILL.md
# Math Tools
Deterministic mathematical computation engine using SymPy. All calculations use symbolic math - no LLM estimation.
## When to Use
Use this skill whenever mathematical accuracy matters:
- Arithmetic involving fractions, roots, or large numbers
- Algebraic simplification, expansion, factoring
- Solving equations (polynomial, transcendental, systems)
- Calculus (derivatives, integrals, limits, series)
- Linear algebra (matrices, eigenvalues, determinants)
- Number theory (primes, factorization, GCD/LCM)
- Statistical calculationsmathematical-logic-expert
When your agent uses it
Expert in formal logic, model theory, computability, and foundations of mathematics
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
279 tokensWhen the skill is activated
Reference documents
1,117 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- How to use this skill
- Module overview
- Research status
Files
README.mddoc258 bytesSKILL.mdcore1,227 bytes_toc.mddoc442 bytesmodules/core-guidance.mddoc2,596 bytesmodules/known-gaps.mddoc526 bytesmodules/research-checklist.mddoc861 bytes
Read SKILL.md
# Mathematical Logic Expert
> **Status**: ⚠<U+FE0F> Legacy template awaiting research upgrade
> **Last validated**: 2025-11-08
> **Confidence**: 🔴 Low — Legacy template awaiting research upgrade
## How to use this skill
1. Start with [modules/research-checklist.md](modules/research-checklist.md) and capture up-to-date sources.
2. Review [modules/known-gaps.md](modules/known-gaps.md) and resolve outstanding items.
3. Load topic-specific modules from [_toc.md](_toc.md) only after verification.
4. Update metadata when confidence improves.
## Module overview
- [Core guidance](modules/core-guidance.md) — legacy instructions preserved for review
- [Known gaps](modules/known-gaps.md) — validation tasks and open questionsmatlab
When your agent uses it
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
What it loads into context
Frontmatter
160 tokensAlways available to the agent
SKILL.md
2,774 tokensWhen the skill is activated
Reference documents
26,102 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Quick Start
- Core Capabilities
- Common Patterns
- Reference Files
- GNU Octave Compatibility
- Best Practices
- Additional Resources
Files
SKILL.mdcore9,547 bytesSKILL.mdcore9,547 bytesSKILL.mdcore9,547 bytesSKILL.mdcore9,547 bytesSKILL.mdcore9,547 bytesreferences/data-import-export.mddoc10,600 bytesreferences/executing-scripts.mddoc9,508 bytesreferences/graphics-visualization.mddoc12,845 bytesreferences/mathematics.mddoc15,237 bytesreferences/matrices-arrays.mddoc10,913 bytesreferences/octave-compatibility.mddoc9,977 bytesreferences/programming.mddoc11,885 bytesreferences/python-integration.mddoc9,504 bytes
Read SKILL.md
# MATLAB/Octave Scientific Computing
## Routing Boundary
Use this skill only when the user explicitly asks for MATLAB, Octave, Simulink, `.m` scripts, M-files, or MATLAB-specific tooling. Do not use it for generic NumPy, Python matrix work, Jupyter notebooks, scientific visualization, data analysis, or numerical computing unless MATLAB or Octave is explicit.
MATLAB is a numerical computing environment optimized for matrix operations and scientific computing. GNU Octave is a free, open-source alternative with high MATLAB compatibility.
## Quick Start
**Running MATLAB scripts:**
```bash
# MATLAB (commercial)
matlab -nodisplay -nosplash -r "run('script.m'); exit;"matplotlib
When your agent uses it
Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
2,893 tokensWhen the skill is activated
Reference documents
14,638 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Concepts
- Common Workflows
- Best Practices
- Quick Reference Scripts
- Detailed References
- Integration with Other Tools
- Common Gotchas
- Additional Resources
Scripts executed separately
scripts/plot_template.pyscripts/style_configurator.py
Files
SKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesSKILL.mdcore11,119 bytesreferences/api_reference.mddoc11,233 bytesreferences/common_issues.mddoc12,836 bytesreferences/plot_types.mddoc11,839 bytesreferences/styling_guide.mddoc13,583 bytesscripts/plot_template.pyruns12,093 bytesscripts/style_configurator.pyruns13,179 bytes
Read SKILL.md
# Matplotlib
## Overview
Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots. This skill provides guidance on using matplotlib effectively, covering both the pyplot interface (MATLAB-style) and the object-oriented API (Figure/Axes), along with best practices for creating publication-quality visualizations.
## When to Use This Skill
This skill should be used when:
- Creating any type of plot or chart (line, scatter, bar, histogram, heatmap, contour, etc.)
- Generating scientific or statistical visualizations
- Customizing plot appearance (colors, styles, labels, legends)
- Creating multi-panel figures with subplots
- Exporting visualizations to various formats (PNG, PDF, SVG, etc.)MCP Integration
When your agent uses it
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
What it loads into context
Frontmatter
108 tokensAlways available to the agent
SKILL.md
3,032 tokensWhen the skill is activated
Reference documents
8,181 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- MCP Server Configuration Methods
- MCP Server Types
- Environment Variable Expansion
- MCP Tool Naming
- Lifecycle Management
- Authentication Patterns
- Integration Patterns
- Security Best Practices
- Error Handling
- Performance Considerations
- Testing MCP Integration
- Debugging
- Quick Reference
- Additional Resources
- Implementation Workflow
Files
SKILL.mdcore12,519 bytesSKILL.mdcore12,519 bytesexamples/http-server.jsonasset502 bytesexamples/sse-server.jsonasset413 bytesexamples/stdio-server.jsonasset686 bytesreferences/authentication.mddoc10,196 bytesreferences/server-types.mddoc10,613 bytesreferences/tool-usage.mddoc11,674 bytes
Read SKILL.md
# MCP Integration for Claude Code Plugins
## Overview
Model Context Protocol (MCP) enables Claude Code plugins to integrate with external services and APIs by providing structured tool access. Use MCP integration to expose external service capabilities as tools within Claude Code.
**Key capabilities:**
- Connect to external services (databases, APIs, file systems)
- Provide 10+ related tools from a single service
- Handle OAuth and complex authentication flows
- Bundle MCP servers with plugins for automatic setup
## MCP Server Configuration Methods
medchem
When your agent uses it
Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
2,448 tokensWhen the skill is activated
Reference documents
6,809 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Installation
- Core Capabilities
- Workflow Patterns
- Best Practices
- Resources
- Documentation
Scripts executed separately
scripts/filter_molecules.py
Files
SKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesSKILL.mdcore10,152 bytesreferences/api_guide.mddoc12,344 bytesreferences/rules_catalog.mddoc12,512 bytesscripts/filter_molecules.pyruns15,696 bytes
Read SKILL.md
# Medchem
## Overview
Medchem is a Python library for molecular filtering and prioritization in drug discovery workflows. Apply hundreds of well-established and novel molecular filters, structural alerts, and medicinal chemistry rules to efficiently triage and prioritize compound libraries at scale. Rules and filters are context-specific—use as guidelines combined with domain expertise.
## When to Use This Skill
This skill should be used when:
- Applying drug-likeness rules (Lipinski, Veber, etc.) to compound libraries
- Filtering molecules by structural alerts or PAINS patterns
- Prioritizing compounds for lead optimization
- Assessing compound quality and medicinal chemistry properties
- Detecting reactive or problematic functional groupsmetabolomics-workbench-database
When your agent uses it
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
2,329 tokensWhen the skill is activated
Reference documents
4,535 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Common Workflows
- Output Formats
- Best Practices
- Resources
Files
SKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesSKILL.mdcore10,253 bytesreferences/api_reference.mddoc16,384 bytes
Read SKILL.md
# Metabolomics Workbench Database
## Overview
The Metabolomics Workbench is a comprehensive NIH Common Fund-sponsored platform hosted at UCSD that serves as the primary repository for metabolomics research data. It provides programmatic access to over 4,200 processed studies (3,790+ publicly available), standardized metabolite nomenclature through RefMet, and powerful search capabilities across multiple analytical platforms (GC-MS, LC-MS, NMR).
## When to Use This Skill
This skill should be used when querying metabolite structures, accessing study data, standardizing nomenclature, performing mass spectrometry searches, or retrieving gene/protein-metabolite associations through the Metabolomics Workbench REST API.
## Core Capabilities
### 1. Querying Metabolite Structures and Data
metric-calculator
When your agent uses it
Compute well-defined metrics from existing formulas, datasets, or test outputs. Use as an explicit/manual helper when the metric definition is already known, not for choosing the overall analysis owner or dashboard strategy.
What it loads into context
Frontmatter
91 tokensAlways available to the agent
SKILL.md
298 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Files
SKILL.mdcore1,382 bytes
Read SKILL.md
# Metric Calculator
## Positioning
Treat this skill as an explicit/manual helper for narrow metric-computation work.
## When to Use
Use this skill when:
- Calculating a named business, statistical, or QA metric from available data
- Converting raw counts into rates, ratios, deltas, or scorecards
- Verifying that a metric formula is implemented consistently across outputs
## Not For / Boundariesml-data-leakage-guard
When your agent uses it
Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
3,283 tokensWhen the skill is activated
Reference documents
11,296 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Core Principle
- Quick Reference
- Examples
- Leakage Severity Levels
- References
- Maintenance
Files
SKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesSKILL.mdcore13,481 bytesreferences/detection-strategies.mddoc17,358 bytesreferences/index.mddoc1,726 bytesreferences/leakage-patterns.mddoc13,564 bytesreferences/temporal-leakage.mddoc14,003 bytes
Read SKILL.md
# ML Data Leakage Guard Skill
Automatically detects and prevents data leakage in machine learning workflows by verifying that all preprocessing steps, feature engineering, and statistical computations would be available at prediction time.
## When to Use This Skill
Use this skill after work involving:
- Data preprocessing (normalization, standardization, scaling)
- Missing value imputation
- Feature engineering and feature selection
- Dimensionality reduction (PCA, SVD, t-SNE)
- Target encoding or label encoding
- Time series feature construction
- Data augmentation strategiesml-pipeline-workflow
When your agent uses it
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
1,479 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- What This Skill Provides
- Usage Patterns
- Best Practices
- Integration Points
- Progressive Disclosure
- Common Patterns
- Troubleshooting
- Next Steps
- Related Skills
Files
SKILL.mdcore7,030 bytesSKILL.mdcore7,030 bytesSKILL.mdcore7,030 bytesSKILL.mdcore7,030 bytes
Read SKILL.md
# ML Pipeline Workflow
Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment.
## Overview
This skill provides comprehensive guidance for building production ML pipelines that handle the full lifecycle: data ingestion → preparation → training → validation → deployment → monitoring.
## When to Use This Skill
- Building new ML pipelines from scratch
- Designing workflow orchestration for ML systems
- Implementing data → model → deployment automation
- Setting up reproducible training workflowsnetlify-deploy
When your agent uses it
Deploy web projects to Netlify using the Netlify CLI (`npx netlify`). Use when the user asks to deploy, host, publish, or link a site/repo on Netlify, including preview and production deploys.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
1,646 tokensWhen the skill is activated
Reference documents
3,580 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Prerequisites
- Authentication Pattern
- Workflow
- Handling netlify.toml
- Example Full Workflow
- Error Handling
- Troubleshooting
- Environment Variables
- Tips
- Reference
- Bundled References (Load As Needed)
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesSKILL.mdcore7,011 bytesagents/openai.yamlasset318 bytesassets/netlify-small.svgasset1,291 bytesassets/netlify.pngasset933 bytesreferences/cli-commands.mddoc2,652 bytesreferences/deployment-patterns.mddoc6,702 bytesreferences/netlify-toml.mddoc3,972 bytes
Read SKILL.md
# Netlify Deployment Skill
Deploy web projects to Netlify using the Netlify CLI with intelligent detection of project configuration and deployment context.
## Overview
This skill automates Netlify deployments by:
- Verifying Netlify CLI authentication
- Detecting project configuration and framework
- Linking to existing sites or creating new ones
- Deploying to production or preview environments
## Prerequisites
networkx
When your agent uses it
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
3,139 tokensWhen the skill is activated
Reference documents
12,808 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Working with NetworkX
- Quick Reference
- Resources
- Additional Resources
Files
SKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesSKILL.mdcore12,642 bytesreferences/algorithms.mddoc9,170 bytesreferences/generators.mddoc8,228 bytesreferences/graph-basics.mddoc6,261 bytesreferences/io.mddoc9,395 bytesreferences/visualization.mddoc12,388 bytes
Read SKILL.md
# NetworkX
## Overview
NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs. Use this skill when working with network or graph data structures, including social networks, biological networks, transportation systems, citation networks, knowledge graphs, or any system involving relationships between entities.
## When to Use This Skill
Invoke this skill when tasks involve:
- **Creating graphs**: Building network structures from data, adding nodes and edges with attributes
- **Graph analysis**: Computing centrality measures, finding shortest paths, detecting communities, measuring clustering
- **Graph algorithms**: Running standard algorithms like Dijkstra's, PageRank, minimum spanning trees, maximum flow
- **Network generation**: Creating synthetic networks (random, scale-free, small-world models) for testing or simulationneurokit2
When your agent uses it
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
2,831 tokensWhen the skill is activated
Reference documents
42,087 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Analysis Modes
- Installation
- Common Workflows
- References
- Additional Resources
Files
SKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesSKILL.mdcore11,957 bytesreferences/bio_module.mddoc13,099 bytesreferences/complexity.mddoc17,352 bytesreferences/ecg_cardiac.mddoc10,810 bytesreferences/eda.mddoc14,733 bytesreferences/eeg.mddoc14,306 bytesreferences/emg.mddoc12,390 bytesreferences/eog.mddoc12,271 bytesreferences/epochs_events.mddoc14,793 bytesreferences/hrv.mddoc15,493 bytesreferences/ppg.mddoc11,168 bytesreferences/rsp.mddoc13,946 bytesreferences/signal_processing.mddoc16,652 bytes
Read SKILL.md
# NeuroKit2
## Overview
NeuroKit2 is a comprehensive Python toolkit for processing and analyzing physiological signals (biosignals). Use this skill to process cardiovascular, neural, autonomic, respiratory, and muscular signals for psychophysiology research, clinical applications, and human-computer interaction studies.
## When to Use This Skill
Apply this skill when working with:
- **Cardiac signals**: ECG, PPG, heart rate variability (HRV), pulse analysis
- **Brain signals**: EEG frequency bands, microstates, complexity, source localization
- **Autonomic signals**: Electrodermal activity (EDA/GSR), skin conductance responses (SCR)
- **Respiratory signals**: Breathing rate, respiratory variability (RRV), volume per time
- **Muscular signals**: EMG amplitude, muscle activation detectionneuropixels-analysis
When your agent uses it
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
What it loads into context
Frontmatter
128 tokensAlways available to the agent
SKILL.md
2,998 tokensWhen the skill is activated
Reference documents
23,298 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- When to Use This Skill
- Supported Hardware & Formats
- Quick Start
- Standard Analysis Workflow
- Common Pitfalls and Best Practices
- Key Parameters to Adjust
- Bundled Resources
- Detailed Reference Guides
- Installation
- Project Structure
- Additional Resources
Scripts executed separately
assets/analysis_template.pyscripts/compute_metrics.pyscripts/explore_recording.pyscripts/export_to_phy.pyscripts/neuropixels_pipeline.pyscripts/preprocess_recording.pyscripts/run_sorting.py
Files
SKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesSKILL.mdcore11,854 bytesassets/analysis_template.pyruns9,014 bytesreferences/AI_CURATION.mddoc8,635 bytesreferences/ANALYSIS.mddoc9,869 bytesreferences/AUTOMATED_CURATION.mddoc10,033 bytesreferences/MOTION_CORRECTION.mddoc8,670 bytesreferences/PREPROCESSING.mddoc6,696 bytesreferences/QUALITY_METRICS.mddoc9,454 bytesreferences/SPIKE_SORTING.mddoc7,918 bytesreferences/api_reference.mddoc8,153 bytesreferences/plotting_guide.mddoc10,837 bytesreferences/standard_workflow.mddoc8,646 bytesscripts/compute_metrics.pyruns5,226 bytesscripts/explore_recording.pyruns5,529 bytesscripts/export_to_phy.pyruns2,477 bytesscripts/neuropixels_pipeline.pyruns13,286 bytesscripts/preprocess_recording.pyruns4,235 bytesscripts/run_sorting.pyruns2,573 bytes
Read SKILL.md
# Neuropixels Data Analysis
## Routing Boundary
Use this skill only for Neuropixels, SpikeGLX, Kilosort, Open Ephys, spike sorting, probe/channel maps, or electrophysiology recording workflows tied to these tools. Do not use it for generic neuroscience literature, clinical EEG, fMRI, flow cytometry, or single-cell RNA analysis.
## Overview
Comprehensive toolkit for analyzing Neuropixels high-density neural recordings using current best practices from SpikeInterface, Allen Institute, and International Brain Laboratory (IBL). Supports the full workflow from raw data to publication-ready curated units.
## When to Use This Skill
This skill should be used when:
- Working with Neuropixels recordings (.ap.bin, .lf.bin, .meta files)node-zombie-guardian
When your agent uses it
Use when diagnosing stale or orphaned Node.js processes launched by VCO, auditing ownership/liveness, or safely simulating cleanup without touching external Node workloads.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
703 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Safety Boundary
- When To Use
- Operator Surfaces
- Quick Start
- Verification
Files
SKILL.mdcore3,034 bytes
Read SKILL.md
# Node Zombie Guardian
This skill is for managed-process hygiene inside the VCO ecosystem.
It exists to answer one question safely: which Node processes belong to VCO, which of them are stale, and which of those are eligible for cleanup without risking live external workloads.
## Safety Boundary
- Only processes with `ownership = vco-managed` can ever become cleanup candidates.
- `external` and `unknown` processes remain audit-only.
- Cleanup is report-first by default.
- Fixture `-Apply` mode remains simulation-only and must never terminate real processes.
## When To Usenowait-reasoning-optimizer
When your agent uses it
Implements the NOWAIT technique for efficient reasoning in R1-style LLMs. Use when optimizing inference of reasoning models (QwQ, DeepSeek-R1, Phi4-Reasoning, Qwen3, Kimi-VL, QvQ), reducing chain-of-thought token usage by 27-51% while preserving accuracy. Triggers on "optimize reasoning", "reduce thinking tokens", "efficient inference", "suppress reflection tokens", or when working with verbose CoT outputs.
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
1,257 tokensWhen the skill is activated
Reference documents
1,024 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use
- Supported Models
- Quick Start
- How It Works
- Key Findings
- Integration Examples
- Expected Results
- Limitations
- References
Scripts executed separately
scripts/nowait_processor.py
Files
SKILL.mdcore4,888 bytesSKILL.mdcore4,888 bytesSKILL.mdcore4,888 bytesSKILL.mdcore4,888 bytesrefrences/keywords.mddoc4,115 bytesscripts/nowait_processor.pyruns10,186 bytes
Read SKILL.md
# NOWAIT Reasoning Optimizer
Implements the NOWAIT technique from the paper "Wait, We Don't Need to 'Wait'! Removing Thinking Tokens Improves Reasoning Efficiency" (Wang et al., 2025).
## Overview
NOWAIT is a training-free inference-time intervention that suppresses self-reflection tokens (e.g., "Wait", "Hmm", "Alternatively") during generation, reducing chain-of-thought (CoT) trajectory length by **27-51%** without compromising model utility.
## When to Use
- Deploying R1-style reasoning models with limited compute
- Reducing inference latency for production systems
- Optimizing token costs for reasoning tasks
- Working with verbose CoT outputs that need streamliningomero-integration
When your agent uses it
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
1,836 tokensWhen the skill is activated
Reference documents
29,698 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- When to Use This Skill
- Core Capabilities
- Installation
- Quick Start
- Selecting the Right Capability
- Common Workflows
- Error Handling
- Additional Resources
- Notes
Files
SKILL.mdcore8,455 bytesSKILL.mdcore8,455 bytesSKILL.mdcore8,455 bytesSKILL.mdcore8,455 bytesSKILL.mdcore8,455 bytesSKILL.mdcore8,455 bytesreferences/advanced.mddoc15,013 bytesreferences/connection.mddoc8,404 bytesreferences/data_access.mddoc13,555 bytesreferences/image_processing.mddoc15,705 bytesreferences/metadata.mddoc17,020 bytesreferences/rois.mddoc16,388 bytesreferences/scripts.mddoc17,319 bytesreferences/tables.mddoc14,835 bytes
Read SKILL.md
# OMERO Integration
## Overview
OMERO is an open-source platform for managing, visualizing, and analyzing microscopy images and metadata. Access images via Python API, retrieve datasets, analyze pixels, manage ROIs and annotations, for high-content screening and microscopy workflows.
## Routing Boundary
Use this skill for OMERO server access, OMERO Python API work, microscopy image server data retrieval, ROI annotation, image metadata management, and high-content screening image management. Generic microscopy literature search, DICOM tags, IDC/TCIA retrieval, histolab tiling, PathML computational pathology, scRNA-seq, flow cytometry, and generic image processing are outside this skill.
## When to Use This Skill
This skill should be used when:
- Working with OMERO Python API (omero-py) to access microscopy dataopenai-docs
When your agent uses it
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to official OpenAI domains.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
782 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick start
- OpenAI product snapshots
- If MCP server is missing
- Workflow
- Quality rules
- Tooling notes
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore3,446 bytesSKILL.mdcore3,446 bytesagents/openai.yamlasset504 bytesassets/openai-small.svgasset1,091 bytesassets/openai.pngasset1,429 bytes
Read SKILL.md
# OpenAI Docs
Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. Always prioritize the developer docs MCP tools over web.run for OpenAI-related questions. Only if the MCP server is installed and returns no meaningful results should you fall back to web search.
## Quick start
- Use `mcp__openaiDeveloperDocs__search_openai_docs` to find the most relevant doc pages.
- Use `mcp__openaiDeveloperDocs__fetch_openai_doc` to pull exact sections and quote/paraphrase accurately.
- Use `mcp__openaiDeveloperDocs__list_openai_docs` only when you need to browse or discover pages without a clear query.
## OpenAI product snapshots
1. Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT.openai-knowledge
When your agent uses it
Compatibility alias for OpenAI platform documentation guidance. Delegate to the canonical local `openai-docs` payload while preserving route compatibility.
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
264 tokensWhen the skill is activated
Reference documents
782 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Resolution Order
- Minimal Workflow
Files
../openai-docs/SKILL.mddoc3,446 bytesSKILL.mdcore1,181 bytes
Read SKILL.md
# openai-knowledge (Compatibility Alias)
## Purpose
Provide a stable compatibility alias for callers that still request
`openai-knowledge`, while canonical OpenAI documentation guidance is maintained
under the sibling `openai-docs` skill directory.
This preserves:
- existing route compatibility for `openai-knowledge`
- `skills-lock` and catalog continuity for legacy callers
- a thin alias surface instead of duplicated docs guidance payload
openalex-database
When your agent uses it
Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.
What it loads into context
Frontmatter
95 tokensAlways available to the agent
SKILL.md
2,981 tokensWhen the skill is activated
Reference documents
5,385 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start
- Core Capabilities
- Critical Best Practices
- Common Filter Patterns
- Entity Types
- External IDs
- Reference Documentation
- Scripts
- Troubleshooting
- Rate Limits
- Notes
Scripts executed separately
scripts/openalex_client.pyscripts/query_helpers.py
Files
SKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesSKILL.mdcore12,071 bytesreferences/api_guide.mddoc10,185 bytesreferences/common_queries.mddoc9,587 bytesscripts/openalex_client.pyruns10,148 bytesscripts/query_helpers.pyruns8,443 bytes
Read SKILL.md
# OpenAlex Database
## Overview
OpenAlex is a comprehensive open catalog of 240M+ scholarly works, authors, institutions, topics, sources, publishers, and funders. This skill provides tools and workflows for querying the OpenAlex API to search literature, analyze research output, track citations, and conduct bibliometric studies.
## Quick Start
### Basic Setup
Always initialize the client with an email address to access the polite pool (10x rate limit boost):
```python
from scripts.openalex_client import OpenAlexClientpaper-2-web
When your agent uses it
Use when converting academic papers into dissemination assets such as Paper2Web websites, Paper2Video video abstracts, or Paper2Poster conference posters from LaTeX or PDF sources.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
3,470 tokensWhen the skill is activated
Reference documents
9,255 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Boundary
- Core Capabilities
- Quick Start
- Workflow Decision Tree
- Input Requirements
- Common Parameters
- Output Structure
- Best Practices
- Resource Requirements
- Troubleshooting
- Platform-Specific Features
- Integration and Deployment
- Advanced Usage
- References and Resources
- Evaluation and Quality Metrics
Files
SKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesSKILL.mdcore15,072 bytesreferences/installation.mddoc3,644 bytesreferences/paper2poster.mddoc10,207 bytesreferences/paper2video.mddoc9,796 bytesreferences/paper2web.mddoc5,388 bytesreferences/usage_examples.mddoc10,633 bytes
Read SKILL.md
# Paper2All: Academic Paper Transformation Pipeline
## Overview
This skill enables the transformation of academic papers into multiple promotional and presentation formats using the Paper2All autonomous pipeline. The system converts research papers (LaTeX or PDF) into three primary outputs:
1. **Paper2Web**: Interactive, explorable academic homepages with layout-aware design
2. **Paper2Video**: Professional presentation videos with narration, slides, and optional talking-head
3. **Paper2Poster**: Print-ready conference posters with professional layouts
The pipeline uses LLM-powered content extraction, design generation, and iterative refinement to create high-quality outputs suitable for conferences, journals, preprint repositories, and academic promotion.
## When to Use This Skill
pathml
When your agent uses it
Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,607 tokensWhen the skill is activated
Reference documents
25,735 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- When to Use This Skill
- Core Capabilities
- Quick Start
- References to Detailed Documentation
- Resources
Files
SKILL.mdcore7,866 bytesSKILL.mdcore7,866 bytesSKILL.mdcore7,866 bytesreferences/data_management.mddoc19,018 bytesreferences/graphs.mddoc16,726 bytesreferences/image_loading.mddoc12,146 bytesreferences/machine_learning.mddoc19,946 bytesreferences/multiparametric.mddoc18,199 bytesreferences/preprocessing.mddoc18,209 bytes
Read SKILL.md
# PathML
## Overview
PathML is a comprehensive Python toolkit for computational pathology workflows, designed to facilitate machine learning and image analysis for whole-slide pathology images. The framework provides modular, composable tools for loading diverse slide formats, preprocessing images, constructing spatial graphs, training deep learning models, and analyzing multiparametric imaging data from technologies like CODEX and multiplex immunofluorescence.
## Routing Boundary
Use this skill for full computational pathology workflows, PathML pipelines, WSI analysis, nucleus segmentation, tissue or cell graphs, spatial pathology, multiplex pathology, and multiparametric imaging. Basic WSI tile extraction should stay with histolab, DICOM tag/anonymization work with pydicom, IDC/TCIA/DICOMWeb retrieval with imaging-data-commons, and OMERO server or ROI management with omero-integration.
## When to Use This Skill
Apply this skill for:
- Loading and processing whole-slide images (WSI) in various proprietary formatsWhen your agent uses it
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
564 tokensWhen the skill is activated
Reference documents
6,315 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Rendering command
- Quality expectations
- Final checks
Scripts executed separately
scripts/check_bounding_boxes.pyscripts/check_bounding_boxes_test.pyscripts/check_fillable_fields.pyscripts/convert_pdf_to_images.pyscripts/create_validation_image.pyscripts/extract_form_field_info.pyscripts/fill_fillable_fields.pyscripts/fill_pdf_form_with_annotations.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore2,517 bytesagents/openai.yamlasset219 bytesassets/pdf.pngasset1,312 bytesforms.mddoc9,438 bytesreference.mddoc16,692 bytesscripts/check_bounding_boxes.pyruns3,139 bytesscripts/check_bounding_boxes_test.pyruns8,818 bytesscripts/check_fillable_fields.pyruns362 bytesscripts/convert_pdf_to_images.pyruns1,123 bytesscripts/create_validation_image.pyruns1,603 bytesscripts/extract_form_field_info.pyruns6,127 bytesscripts/fill_fillable_fields.pyruns4,863 bytesscripts/fill_pdf_form_with_annotations.pyruns3,596 bytes
Read SKILL.md
# PDF Skill
## When to use
- Read or review PDF content where layout and visuals matter.
- Create PDFs programmatically with reliable formatting.
- Validate final rendering before delivery.
## Workflow
1. Prefer visual review: render PDF pages to PNGs and inspect them.
- Use `pdftoppm` if available.
- If unavailable, install Poppler or ask the user to review the output locally.
2. Use `reportlab` to generate PDFs when creating new documents.
3. Use `pdfplumber` (or `pypdf`) for text extraction and quick checks; do not rely on it for layout fidelity.peer-review
When your agent uses it
Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
4,549 tokensWhen the skill is activated
Reference documents
5,909 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Peer Review Workflow
- Structuring Peer Review Reports
- Tone and Approach
- Special Considerations by Manuscript Type
- Resources
- Final Checklist
Files
SKILL.mdcore23,119 bytesSKILL.mdcore23,119 bytesSKILL.mdcore23,119 bytesSKILL.mdcore23,119 bytesreferences/common_issues.mddoc19,321 bytesreferences/reporting_standards.mddoc10,200 bytes
Read SKILL.md
# Scientific Critical Evaluation and Peer Review
## Overview
Peer review is a systematic process for evaluating scientific manuscripts. Assess methodology, statistics, design, reproducibility, ethics, and reporting standards. Apply this skill for manuscript and grant review across disciplines with constructive, rigorous evaluation.
## When to Use This Skill
This skill should be used when:
- Conducting peer review of scientific manuscripts for journals
- Evaluating grant proposals and research applications
- Assessing methodology and experimental design rigor
- Reviewing statistical analyses and reporting standards
- Evaluating reproducibility and data availabilityperformance-testing
When your agent uses it
Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
770 tokensWhen the skill is activated
Reference documents
1,030 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Running benchmarks
- Adding benchmarks
- Performance targets
- Expected execution times (502 periods)
- Regression detection
- Creating baselines
- Required optimization patterns
- Prohibited patterns
Files
SKILL.mdcore3,125 bytesSKILL.mdcore3,125 bytesSKILL.mdcore3,125 bytesSKILL.mdcore3,125 bytesSKILL.mdcore3,125 bytesSKILL.mdcore3,125 bytesreferences/benchmark-patterns.mddoc3,733 bytes
Read SKILL.md
# Performance testing
## Running benchmarks
```bash
cd tools/performance
# Run all benchmarks (~15-20 minutes)
dotnet run -c Release
# Run specific category
dotnet run -c Release --filter *StreamIndicators*
dotnet run -c Release --filter *BufferIndicators*
dotnet run -c Release --filter *SeriesIndicators*performing-causal-analysis
When your agent uses it
Estimate causal effects from existing data. Use when fitting or interpreting DiD, ITS, synthetic control, regression discontinuity, or other treatment-effect analyses, including robustness checks and counterfactual plots. For choosing a study design before analysis, use designing-experiments instead.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
304 tokensWhen the skill is activated
Reference documents
1,254 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Core Methods
- References
Files
SKILL.mdcore1,477 bytesreference/diff_in_diff.mddoc1,752 bytesreference/interrupted_time_series.mddoc1,522 bytesreference/synthetic_control.mddoc1,458 bytes
Read SKILL.md
# Performing Causal Analysis
Executes causal analysis on existing data. This skill owns model setup, treatment-effect estimation, counterfactual comparison, robustness checks, and interpretation of fitted causal results.
It does not own the earlier question of which experiment or quasi-experiment should be designed before analysis begins.
## Workflow
1. **Load Data**: Ensure data is in a Pandas DataFrame.
2. **Initialize Experiment**: Use the appropriate class (see References).
3. **Fit & Model**: Models are fitted automatically upon initialization if arguments are provided.
4. **Analyze Results**: Use `summary()`, `print_coefficients()`, and `plot()`.
## Core Methodsperplexity-search
When your agent uses it
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
What it loads into context
Frontmatter
134 tokensAlways available to the agent
SKILL.md
3,203 tokensWhen the skill is activated
Reference documents
7,492 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- Available Models
- Crafting Effective Queries
- Common Use Cases
- Working with Results
- Cost Management
- Troubleshooting
- Integration with Other Skills
- Best Practices
- Resources
- Dependencies
- Summary
Scripts executed separately
scripts/perplexity_search.pyscripts/setup_env.py
Files
SKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesSKILL.mdcore14,084 bytesreferences/model_comparison.mddoc10,378 bytesreferences/openrouter_setup.mddoc11,522 bytesreferences/search_strategies.mddoc10,021 bytesscripts/perplexity_search.pyruns8,068 bytesscripts/setup_env.pyruns4,656 bytes
Read SKILL.md
# Perplexity Search
## Overview
Perform AI-powered web searches using Perplexity models through LiteLLM and OpenRouter. Perplexity provides real-time, web-grounded answers with source citations, making it ideal for finding current information, recent scientific literature, and facts beyond the model's training data cutoff.
This skill provides access to all Perplexity models through OpenRouter, requiring only a single API key (no separate Perplexity account needed).
## When to Use This Skill
Use this skill when:
- Searching for current information or recent developments (2024 and beyond)
- Finding latest scientific publications and research
- Getting real-time answers grounded in web sourcesplanning-with-files
When your agent uses it
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
What it loads into context
Frontmatter
270 tokensAlways available to the agent
SKILL.md
1,559 tokensWhen the skill is activated
Reference documents
5,502 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Important: Where Files Go
- Quick Start
- The Core Pattern
- File Purposes
- Critical Rules
- The 3-Strike Error Protocol
- Read vs Write Decision Matrix
- The 5-Question Reboot Test
- When to Use This Pattern
- Templates
- Scripts
- Advanced Topics
- Anti-Patterns
Scripts executed separately
scripts/check-complete.shscripts/init-session.sh
Files
SKILL.mdcore6,626 bytesexamples.mddoc4,426 bytesreference.mddoc8,066 bytesscripts/check-complete.shruns1,160 bytesscripts/init-session.shruns2,254 bytestemplates/findings.mddoc3,561 bytestemplates/progress.mddoc4,001 bytestemplates/task_plan.mddoc4,613 bytes
Read SKILL.md
# Planning with Files
Work like Manus: Use persistent markdown files as your "working memory on disk."
## Important: Where Files Go
When using this skill:
- **Templates** are stored in the skill directory at `${CLAUDE_PLUGIN_ROOT}/templates/`
- **Your planning files** (`task_plan.md`, `findings.md`, `progress.md`) should be created in **your project directory** — the folder where you're working
| Location | What Goes There |
|----------|-----------------|
| Skill directory (`${CLAUDE_PLUGIN_ROOT}/`) | Templates, scripts, reference docs |playwright
When your agent uses it
Use when the task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
950 tokensWhen the skill is activated
Reference documents
1,023 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisite check (required)
- Skill path (set once)
- Quick start
- Core workflow
- When to snapshot again
- Recommended patterns
- Wrapper script
- References
- Guardrails
Scripts executed separately
scripts/playwright_cli.sh
Files
LICENSE.txtdoc11,351 bytesNOTICE.txtdoc403 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesSKILL.mdcore3,771 bytesagents/openai.yamlasset313 bytesassets/playwright-small.svgasset828 bytesassets/playwright.pngasset1,730 bytesreferences/cli.mddoc1,863 bytesreferences/workflows.mddoc1,864 bytesscripts/playwright_cli.shruns526 bytes
Read SKILL.md
# Playwright CLI Skill
Drive a real browser from the terminal using `playwright-cli`. Prefer the bundled wrapper script so the CLI works even when it is not globally installed.
Treat this skill as CLI-first automation. Do not pivot to `@playwright/test` unless the user explicitly asks for test files.
## Prerequisite check (required)
Before proposing commands, check whether `npx` is available (the wrapper depends on it):
```bash
command -v npx >/dev/null 2>&1
```
plotly
When your agent uses it
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
What it loads into context
Frontmatter
89 tokensAlways available to the agent
SKILL.md
1,895 tokensWhen the skill is activated
Reference documents
10,958 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Choosing Between APIs
- Core Capabilities
- Common Workflows
- Integration with Dash
- Reference Files
- Additional Resources
Files
SKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesSKILL.mdcore7,333 bytesreference/chart-types.mddoc8,763 bytesreference/export-interactivity.mddoc9,204 bytesreference/graph-objects.mddoc5,986 bytesreference/layouts-styling.mddoc9,128 bytesreference/plotly-express.mddoc4,893 bytes
Read SKILL.md
# Plotly
Python graphing library for creating interactive, publication-quality visualizations with 40+ chart types.
## Quick Start
Install Plotly:
```bash
uv pip install plotly
```
Basic usage with Plotly Express (high-level API):
```python
import plotly.express as pxpolars
When your agent uses it
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.
What it loads into context
Frontmatter
101 tokensAlways available to the agent
SKILL.md
2,439 tokensWhen the skill is activated
Reference documents
19,605 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start
- Core Concepts
- Common Operations
- Aggregations and Window Functions
- Data I/O
- Transformations
- Pandas Migration
- Best Practices
- Resources
Files
SKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesSKILL.mdcore9,430 bytesreferences/best_practices.mddoc14,181 bytesreferences/core_concepts.mddoc8,348 bytesreferences/io_guide.mddoc11,208 bytesreferences/operations.mddoc12,080 bytesreferences/pandas_migration.mddoc12,353 bytesreferences/transformations.mddoc11,183 bytes
Read SKILL.md
# Polars
## Overview
Polars is a lightning-fast DataFrame library for Python and Rust built on Apache Arrow. Work with Polars' expression-based API, lazy evaluation framework, and high-performance data manipulation capabilities for efficient data processing, pandas migration, and data pipeline optimization.
## Quick Start
### Installation and Basic Usage
Install Polars:
```python
uv pip install polars
```pptx-posters
When your agent uses it
Create research posters using HTML/CSS that can be exported to PDF or PPTX. Use this skill ONLY when the user explicitly requests PowerPoint/PPTX poster format. For standard research posters, use latex-posters instead. This skill provides modern web-based poster design with responsive layouts and easy visual integration.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
3,587 tokensWhen the skill is activated
Reference documents
19,567 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- AI-Powered Visual Element Generation
- Core Capabilities
- Workflow for PPTX Poster Creation
- HTML Template Structure
- Quality Checklist
- Common Pitfalls to Avoid
- Integration with Other Skills
- Template Assets
- References
Files
SKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesSKILL.mdcore14,146 bytesassets/poster_html_template.htmlasset5,643 bytesassets/poster_quality_checklist.mddoc11,172 bytesreferences/poster_content_guide.mddoc20,361 bytesreferences/poster_design_principles.mddoc22,916 bytesreferences/poster_layout_design.mddoc22,327 bytes
Read SKILL.md
# PPTX Research Posters (HTML-Based)
## Overview
**⚠<U+FE0F> USE THIS SKILL ONLY WHEN USER EXPLICITLY REQUESTS PPTX/POWERPOINT POSTER FORMAT.**
For standard research posters, use the **latex-posters** skill instead, which provides better typographic control and is the default for academic conferences.
This skill creates research posters using HTML/CSS, which can then be exported to PDF or converted to PowerPoint format. The web-based approach offers:
- Modern, responsive layouts
- Easy integration of AI-generated visuals
- Quick iteration and preview in browser
- Export to PDF via browser print function
- Conversion to PPTX if specifically neededpreprocessing-data-with-automated-pipelines
When your agent uses it
Design and implement repeatable preprocessing pipelines for cleaning, encoding, transforming, and validating ML input data.
What it loads into context
Frontmatter
79 tokensAlways available to the agent
SKILL.md
319 tokensWhen the skill is activated
Reference documents
234 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/handle_errors.pyscripts/pipeline.pyscripts/transform_data.pyscripts/validate_data.py
Files
SKILL.mdcore1,493 bytesassets/README.mddoc309 bytesassets/example_data.csvasset1,381 bytesreferences/README.mddoc437 bytesscripts/README.mddoc426 bytesscripts/handle_errors.pyruns10,307 bytesscripts/pipeline.pyruns11,792 bytesscripts/transform_data.pyruns13,429 bytesscripts/validate_data.pyruns7,692 bytes
Read SKILL.md
# Data Preprocessing Pipeline
## Positioning
Use this skill as the direct owner for ML input-preparation pipelines.
It covers preprocessing-heavy tasks where the requested deliverable is a repeatable pipeline for cleaning, encoding, transforming, and validating input data.
## When to Use
Use this skill when:
- Prepare raw data for machine learning models.
- Automate data cleaning and transformation processes.
- Implement a robust ETL (Extract, Transform, Load) pipeline.
prompt-lookup
When your agent uses it
Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
481 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Available Tools
- How to Search for Prompts
- How to Get a Prompt
- How to Improve a Prompt
- Guidelines
Files
SKILL.mdcore2,109 bytes
Read SKILL.md
When the user needs AI prompts, prompt templates, or wants to improve their prompts, use the prompts.chat MCP server to help them.
## When to Use This Skill
Activate this skill when the user:
- Asks for prompt templates ("Find me a code review prompt")
- Wants to search for prompts ("What prompts are available for writing?")
- Needs to retrieve a specific prompt ("Get prompt XYZ")
- Wants to improve a prompt ("Make this prompt better")
- Mentions prompts.chat or prompt libraries
## Available Tools
property-based-testing
When your agent uses it
Property-based testing with fast-check (TypeScript/JavaScript) and Hypothesis (Python). Generate test cases automatically, find edge cases, and test mathematical properties. Use when user mentions property-based testing, fast-check, Hypothesis, generating test data, QuickCheck-style testing, or finding edge cases automatically.
What it loads into context
Frontmatter
125 tokensAlways available to the agent
SKILL.md
4,852 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Core Expertise
- TypeScript/JavaScript (fast-check)
- Python (Hypothesis)
- Real-World Examples
- Best Practices
- Common Pitfalls
- CI/CD Integration
- Troubleshooting
- See Also
- References
Files
SKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytesSKILL.mdcore19,017 bytes
Read SKILL.md
# Property-Based Testing
Expert knowledge for property-based testing - automatically generating test cases to verify code properties rather than testing specific examples.
## Core Expertise
**Property-Based Testing Concept**
- **Traditional testing**: Test specific examples
- **Property-based testing**: Test properties that should hold for all inputs
- **Generators**: Automatically create diverse test inputs
- **Shrinking**: Minimize failing cases to simplest example
- **Coverage**: Explore edge cases humans might miss
**When to Use Property-Based Testing**propositional-logic
When your agent uses it
Problem-solving strategies for propositional logic in mathematical logic
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
459 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Decision Tree
- Tool Commands
- Cognitive Tools Reference
Files
SKILL.mdcore1,639 bytesSKILL.mdcore1,639 bytesSKILL.mdcore1,639 bytesSKILL.mdcore1,639 bytesSKILL.mdcore1,639 bytes
Read SKILL.md
# Propositional Logic
## When to Use
Use this skill when working on propositional-logic problems in mathematical logic.
## Decision Tree
1. **Identify Formula Structure**
- Classify: tautology, contradiction, or contingent?
- Main connective: AND, OR, IMPLIES, NOT, IFF?
- `z3_solve.py sat "formula"` to check satisfiability
providing-performance-optimization-advice
When your agent uses it
Produce a prioritized performance-optimization roadmap across frontend, backend, and infrastructure. Use as an explicit/manual helper after bottlenecks are known or suspected, not as the owner of regression detection, profiling capture, or test execution.
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
322 tokensWhen the skill is activated
Reference documents
326 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/impact_estimator.pyscripts/optimization_suggestions.pyscripts/performance_profiler.py
Files
SKILL.mdcore1,562 bytesassets/README.mddoc432 bytesreferences/README.mddoc870 bytesscripts/README.mddoc481 bytesscripts/impact_estimator.pyruns2,938 bytesscripts/optimization_suggestions.pyruns2,948 bytesscripts/performance_profiler.pyruns2,992 bytes
Read SKILL.md
# Performance Optimization Advisor
## Positioning
Treat this skill as an explicit/manual advisor for prioritizing optimization work.
## When to Use
Use this skill when:
- Prioritizing known or suspected performance bottlenecks from existing logs, traces, benchmarks, or user reports.
- Get recommendations for improving website loading speed.
- Optimize database query performance.
- Improve API response times.
- Reduce infrastructure costs.
prowler-docs
When your agent uses it
Prowler documentation style guide and writing standards. Trigger: When writing documentation for Prowler features, tutorials, or guides.
What it loads into context
Frontmatter
101 tokensAlways available to the agent
SKILL.md
770 tokensWhen the skill is activated
Reference documents
67 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Brand Voice
- Formatting Standards
- SEO Optimization
- MDX Components
- Prowler Features (Proper Nouns)
- Documentation Structure
- Resources
Files
SKILL.mdcore3,153 bytesreferences/documentation-docs.mddoc355 bytes
Read SKILL.md
## When to Use
Use this skill when writing Prowler documentation for:
- Feature documentation
- API/SDK references
- Tutorials and guides
- Release notes
## Brand Voice
### Unbiased Communication
- Avoid gendered pronouns (use "you/your" or "they/them")
- Use inclusive alternatives: businessman → businessperson, mankind → humanity
- No generalizations about gender, race, nationality, culturepubmed-database
When your agent uses it
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
3,621 tokensWhen the skill is activated
Reference documents
8,167 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Working with Reference Files
- Common Workflows
- Tips and Best Practices
- Limitations and Considerations
- Support Resources
Files
SKILL.mdcore15,569 bytesSKILL.mdcore15,569 bytesSKILL.mdcore15,569 bytesreferences/api_reference.mddoc7,934 bytesreferences/common_queries.mddoc10,725 bytesreferences/search_syntax.mddoc10,272 bytes
Read SKILL.md
# PubMed Database
## Overview
PubMed is the U.S. National Library of Medicine's comprehensive database providing free access to MEDLINE and life sciences literature. Construct advanced queries with Boolean operators, MeSH terms, and field tags, access data programmatically via E-utilities API for systematic reviews and literature analysis.
## When to Use This Skill
This skill should be used when:
- Searching for biomedical or life sciences research articles
- Constructing complex search queries with Boolean operators, field tags, or MeSH terms
- Conducting systematic literature reviews or meta-analyses
- Accessing PubMed data programmatically via the E-utilities API
- Finding articles by specific criteria (author, journal, publication date, article type)pufferlib
When your agent uses it
This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or developing policies with CNNs/LSTMs.
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
2,997 tokensWhen the skill is activated
Reference documents
16,598 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Start Workflow
- Resources
- Tips for Success
- Common Use Cases
- Installation
- Documentation
Scripts executed separately
scripts/env_template.pyscripts/train_template.py
Files
SKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesSKILL.mdcore13,464 bytesreferences/environments.mddoc12,489 bytesreferences/integration.mddoc15,165 bytesreferences/policies.mddoc19,183 bytesreferences/training.mddoc8,127 bytesreferences/vectorization.mddoc12,962 bytesscripts/env_template.pyruns10,157 bytesscripts/train_template.pyruns8,027 bytes
Read SKILL.md
# PufferLib - High-Performance Reinforcement Learning
## Overview
PufferLib is a high-performance reinforcement learning library designed for fast parallel environment simulation and training. It achieves training at millions of steps per second through optimized vectorization, native multi-agent support, and efficient PPO implementation (PuffeRL). The library provides the Ocean suite of 20+ environments and seamless integration with Gymnasium, PettingZoo, and specialized RL frameworks.
## When to Use This Skill
Use this skill when:
- **Training RL agents** with PPO on any environment (single or multi-agent)
- **Creating custom environments** using the PufferEnv API
- **Optimizing performance** for parallel environment simulation (vectorization)
- **Integrating existing environments** from Gymnasium, PettingZoo, Atari, Procgen, etc.
- **Developing policies** with CNN, LSTM, or custom architecturespydeseq2
When your agent uses it
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
4,032 tokensWhen the skill is activated
Reference documents
5,014 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start Workflow
- Core Workflow Steps
- Common Analysis Patterns
- Using the Analysis Script
- Result Interpretation
- Visualization Guidelines
- Troubleshooting Common Issues
- Reference Documentation
- Key Reminders
- Installation and Requirements
- Additional Resources
Scripts executed separately
scripts/run_deseq2_analysis.py
Files
SKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesSKILL.mdcore16,105 bytesreferences/api_reference.mddoc7,162 bytesreferences/workflow_guide.mddoc13,026 bytesscripts/run_deseq2_analysis.pyruns11,887 bytes
Read SKILL.md
# PyDESeq2
## Overview
PyDESeq2 is a Python implementation of DESeq2 for differential expression analysis with bulk RNA-seq data. Design and execute complete workflows from data loading through result interpretation, including single-factor and multi-factor designs, Wald tests with multiple testing correction, optional apeGLM shrinkage, and integration with pandas and AnnData.
## When to Use This Skill
This skill should be used when:
- Analyzing bulk RNA-seq count data for differential expression
- Comparing gene expression between experimental conditions (e.g., treated vs control)
- Performing multi-factor designs accounting for batch effects or covariates
- Converting R-based DESeq2 workflows to Python
- Integrating differential expression analysis into Python-based pipelinespydicom
When your agent uses it
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
What it loads into context
Frontmatter
141 tokensAlways available to the agent
SKILL.md
3,370 tokensWhen the skill is activated
Reference documents
5,832 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- When to Use This Skill
- Installation
- Core Workflows
- Helper Scripts
- Reference Materials
- Common Issues and Solutions
- Best Practices
- Documentation
Scripts executed separately
scripts/anonymize_dicom.pyscripts/dicom_to_image.pyscripts/extract_metadata.py
Files
SKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesSKILL.mdcore13,567 bytesreferences/common_tags.mddoc10,246 bytesreferences/transfer_syntaxes.mddoc9,627 bytesscripts/anonymize_dicom.pyruns5,254 bytesscripts/dicom_to_image.pyruns6,101 bytesscripts/extract_metadata.pyruns5,686 bytes
Read SKILL.md
# Pydicom
## Overview
Pydicom is a pure Python package for working with DICOM files, the standard format for medical imaging data. This skill provides guidance on reading, writing, and manipulating DICOM files, including working with pixel data, metadata, and various compression formats.
## Routing Boundary
Use this skill for DICOM files, tags, pixel data, anonymization, CT/MRI/PET/X-ray medical scans, PACS-oriented processing, and pydicom-specific coding. Generic PNG/JPEG image processing, OCR, screenshots, PubMed/literature search, ClinicalTrials.gov lookup, LaTeX/PDF builds, bioinformatics, chemistry, or generic Data Commons tasks are outside this skill.
## When to Use This Skill
Use this skill when working with:
- Medical imaging files (CT, MRI, X-ray, ultrasound, PET, etc.)pyhealth
When your agent uses it
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
What it loads into context
Frontmatter
112 tokensAlways available to the agent
SKILL.md
4,032 tokensWhen the skill is activated
Reference documents
16,869 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Start Workflow
- Detailed Documentation
- Installation
- Common Use Cases
- Best Practices
- Limitations and Considerations
- Troubleshooting
- Example: Complete Workflow
- Resources
Files
SKILL.mdcore17,590 bytesSKILL.mdcore17,590 bytesSKILL.mdcore17,590 bytesSKILL.mdcore17,590 bytesSKILL.mdcore17,590 bytesSKILL.mdcore17,590 bytesreferences/datasets.mddoc5,468 bytesreferences/medical_coding.mddoc8,476 bytesreferences/models.mddoc13,776 bytesreferences/preprocessing.mddoc14,388 bytesreferences/tasks.mddoc11,404 bytesreferences/training_evaluation.mddoc16,982 bytes
Read SKILL.md
# PyHealth: Healthcare AI Toolkit
## Overview
PyHealth is a comprehensive Python library for healthcare AI that provides specialized tools, models, and datasets for clinical machine learning. Use this skill when developing healthcare prediction models, processing clinical data, working with medical coding systems, or deploying AI solutions in healthcare settings.
## When to Use This Skill
Invoke this skill when:
- **Working with healthcare datasets**: MIMIC-III, MIMIC-IV, eICU, OMOP, sleep EEG data, medical images
- **Clinical prediction tasks**: Mortality prediction, hospital readmission, length of stay, drug recommendation
- **Medical coding**: Translating between ICD-9/10, NDC, RxNorm, ATC coding systems
- **Processing clinical data**: Sequential events, physiological signals, clinical text, medical imagespymatgen
When your agent uses it
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
5,080 tokensWhen the skill is activated
Reference documents
15,997 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start Guide
- Core Capabilities
- Bundled Resources
- Common Workflows
- Best Practices
- Units and Conventions
- Integration with Other Tools
- Troubleshooting
- Additional Resources
- Version Notes
Scripts executed separately
scripts/phase_diagram_generator.pyscripts/structure_analyzer.pyscripts/structure_converter.py
Files
SKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesSKILL.mdcore20,033 bytesreferences/analysis_modules.mddoc12,942 bytesreferences/core_classes.mddoc9,445 bytesreferences/io_formats.mddoc10,518 bytesreferences/materials_project_api.mddoc12,770 bytesreferences/transformations_workflows.mddoc16,805 bytesscripts/phase_diagram_generator.pyruns7,353 bytesscripts/structure_analyzer.pyruns8,452 bytesscripts/structure_converter.pyruns5,179 bytes
Read SKILL.md
# Pymatgen - Python Materials Genomics
## Overview
Pymatgen is a comprehensive Python library for materials analysis that powers the Materials Project. Create, analyze, and manipulate crystal structures and molecules, compute phase diagrams and thermodynamic properties, analyze electronic structure (band structures, DOS), generate surfaces and interfaces, and access Materials Project's database of computed materials. Supports 100+ file formats from various computational codes.
## When to Use This Skill
This skill should be used when:
- Working with crystal structures or molecular systems in materials science
- Converting between structure file formats (CIF, POSCAR, XYZ, etc.)
- Analyzing symmetry, space groups, or coordination environments
- Computing phase diagrams or assessing thermodynamic stability
- Analyzing electronic structure data (band gaps, DOS, band structures)pymc-bayesian-modeling
When your agent uses it
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
4,190 tokensWhen the skill is activated
Reference documents
9,357 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- When to Use This Skill
- Standard Bayesian Workflow
- Common Model Patterns
- Model Comparison
- Distribution Selection Guide
- Sampling and Inference
- Diagnostic Scripts
- Common Issues and Solutions
- Best Practices
- Resources
- Quick Reference
- Additional Notes
Scripts executed separately
assets/hierarchical_model_template.pyassets/linear_regression_template.pyscripts/model_comparison.pyscripts/model_diagnostics.py
Files
SKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesSKILL.mdcore16,111 bytesassets/hierarchical_model_template.pyruns11,858 bytesassets/linear_regression_template.pyruns8,118 bytesreferences/distributions.mddoc10,834 bytesreferences/sampling_inference.mddoc10,384 bytesreferences/workflows.mddoc14,106 bytesscripts/model_comparison.pyruns12,411 bytesscripts/model_diagnostics.pyruns11,113 bytes
Read SKILL.md
# PyMC Bayesian Modeling
## Routing Boundary
Use this skill only for PyMC, probabilistic programming, Bayesian hierarchical models, NUTS/MCMC sampling, posterior predictive checks, and PyMC model diagnostics. Do not use it for generic regression, scikit-learn modeling, causal analysis, pymoo optimization, or materials-science prompts.
## Overview
PyMC is a Python library for Bayesian modeling and probabilistic programming. Build, fit, validate, and compare Bayesian models using PyMC's modern API (version 5.x+), including hierarchical models, MCMC sampling (NUTS), variational inference, and model comparison (LOO, WAIC).
## When to Use This Skill
This skill should be used when:
- Building Bayesian models (linear/logistic regression, hierarchical models, time series, etc.)pymc-bayesian-modeling
When your agent uses it
Compatibility alias for the descriptive PyMC skill name. Delegate to the canonical local `pymc` payload while preserving route and README compatibility.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
266 tokensWhen the skill is activated
Reference documents
4,190 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Resolution Order
- Minimal Workflow
Files
SKILL.mdcore1,108 bytes../pymc/SKILL.mddoc16,111 bytes
Read SKILL.md
# pymc-bayesian-modeling (Compatibility Alias)
## Purpose
Provide a stable descriptive alias for Bayesian modeling workflows that are
canonically maintained under the sibling `pymc` skill directory.
This preserves:
- README-facing descriptive naming
- existing `skills-lock` and catalog entries
- route compatibility for callers that still ask for `pymc-bayesian-modeling`
## Resolution Orderpymoo
When your agent uses it
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
What it loads into context
Frontmatter
69 tokensAlways available to the agent
SKILL.md
4,135 tokensWhen the skill is activated
Reference documents
10,112 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- When to Use This Skill
- Core Concepts
- Quick Start Workflows
- Algorithm Selection Guide
- Benchmark Problems
- Genetic Operator Customization
- Performance and Troubleshooting
- Resources
- Additional Notes
Scripts executed separately
scripts/custom_problem_example.pyscripts/decision_making_example.pyscripts/many_objective_example.pyscripts/multi_objective_example.pyscripts/single_objective_example.py
Files
SKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesSKILL.mdcore17,065 bytesreferences/algorithms.mddoc6,124 bytesreferences/constraints_mcdm.mddoc10,852 bytesreferences/operators.mddoc8,815 bytesreferences/problems.mddoc7,116 bytesreferences/visualization.mddoc9,229 bytesscripts/custom_problem_example.pyruns4,770 bytesscripts/decision_making_example.pyruns4,588 bytesscripts/many_objective_example.pyruns2,103 bytesscripts/multi_objective_example.pyruns1,731 bytesscripts/single_objective_example.pyruns1,620 bytes
Read SKILL.md
# Pymoo - Multi-Objective Optimization in Python
## Routing Boundary
Use this skill only for pymoo, NSGA-II/NSGA, Pareto-front analysis, multi-objective optimization, constrained optimization, and pymoo algorithm implementation. Do not use it for generic optimization planning, experiment design, gradient descent, Bayesian modeling, PyMC, or causal analysis.
## Overview
Pymoo is a comprehensive Python framework for optimization with emphasis on multi-objective problems. Solve single and multi-objective optimization using state-of-the-art algorithms (NSGA-II/III, MOEA/D), benchmark problems (ZDT, DTLZ), customizable genetic operators, and multi-criteria decision making methods. Excels at finding trade-off solutions (Pareto fronts) for problems with conflicting objectives.
## When to Use This Skill
This skill should be used when:
- Solving optimization problems with one or multiple objectivespyopenms
When your agent uses it
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
What it loads into context
Frontmatter
90 tokensAlways available to the agent
SKILL.md
1,341 tokensWhen the skill is activated
Reference documents
16,530 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Installation
- Core Capabilities
- Data Structures
- Common Workflows
- Integration with Other Tools
- Resources
- References
Files
SKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesSKILL.mdcore5,626 bytesreferences/data_structures.mddoc12,390 bytesreferences/feature_detection.mddoc10,539 bytesreferences/file_io.mddoc7,716 bytesreferences/identification.mddoc11,329 bytesreferences/metabolomics.mddoc13,349 bytesreferences/signal_processing.mddoc9,335 bytes
Read SKILL.md
# PyOpenMS
## Overview
PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use for handling mass spectrometry file formats, processing spectral data, detecting features, identifying peptides/proteins, and performing quantitative analysis.
## Installation
Install using uv:
```bash
uv uv pip install pyopenms
```
pytorch-lightning
When your agent uses it
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
1,469 tokensWhen the skill is activated
Reference documents
24,902 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Workflow
- Resources
Scripts executed separately
scripts/quick_trainer_setup.pyscripts/template_datamodule.pyscripts/template_lightning_module.py
Files
SKILL.mdcore6,607 bytesSKILL.mdcore6,607 bytesSKILL.mdcore6,607 bytesSKILL.mdcore6,607 bytesreferences/best_practices.mddoc16,071 bytesreferences/callbacks.mddoc15,540 bytesreferences/data_module.mddoc14,497 bytesreferences/distributed_training.mddoc14,213 bytesreferences/lightning_module.mddoc13,728 bytesreferences/logging.mddoc14,259 bytesreferences/trainer.mddoc14,784 bytesscripts/quick_trainer_setup.pyruns12,985 bytesscripts/template_datamodule.pyruns9,354 bytesscripts/template_lightning_module.pyruns5,886 bytes
Read SKILL.md
# PyTorch Lightning
## Overview
PyTorch Lightning is a deep learning framework that organizes PyTorch code to eliminate boilerplate while maintaining full flexibility. Automate training workflows, multi-device orchestration, and implement best practices for neural network training and scaling across multiple GPUs/TPUs.
## When to Use This Skill
This skill should be used when:
- Building, training, or deploying neural networks using PyTorch Lightning
- Organizing PyTorch code into LightningModules
- Configuring Trainers for multi-GPU/TPU training
- Implementing data pipelines with LightningDataModules
- Working with callbacks, logging, and distributed training strategies (DDP, FSDP, DeepSpeed)pyzotero
When your agent uses it
Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
What it loads into context
Frontmatter
114 tokensAlways available to the agent
SKILL.md
1,075 tokensWhen the skill is activated
Reference documents
8,333 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Authentication Setup
- Installation
- Quick Start
- Core Concepts
- Reference Files
- Common Patterns
Files
SKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesSKILL.mdcore4,398 bytesreferences/authentication.mddoc2,250 bytesreferences/cli.mddoc2,293 bytesreferences/collections.mddoc2,526 bytesreferences/error-handling.mddoc2,617 bytesreferences/exports.mddoc2,603 bytesreferences/files-attachments.mddoc2,760 bytesreferences/full-text.mddoc1,695 bytesreferences/pagination.mddoc2,056 bytesreferences/read-api.mddoc2,972 bytesreferences/saved-searches.mddoc2,009 bytesreferences/search-params.mddoc3,047 bytesreferences/tags.mddoc2,083 bytesreferences/write-api.mddoc3,294 bytes
Read SKILL.md
# Pyzotero
Pyzotero is a Python wrapper for the [Zotero API v3](https://www.zotero.org/support/dev/web_api/v3/start). Use it to programmatically manage Zotero libraries: read items and collections, create and update references, upload attachments, manage tags, and export citations.
## Authentication Setup
**Required credentials** — get from https://www.zotero.org/settings/keys:
- **User ID**: shown as "Your userID for use in API calls"
- **API Key**: create at https://www.zotero.org/settings/keys/new
- **Library ID**: for group libraries, the integer after `/groups/` in the group URL
Store credentials in environment variables or a `.env` file:
```
ZOTERO_LIBRARY_ID=your_user_idralph-loop
When your agent uses it
Codex-compatible Ralph loop runner with dual engines (compat local state loop + optional open-ralph-wiggum backend).
What it loads into context
Frontmatter
33 tokensAlways available to the agent
SKILL.md
501 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Engine model
- Script
- Usage
- Vibe compatibility
- Notes
Scripts executed separately
scripts/ralph-loop.ps1
Files
SKILL.mdcore2,012 bytesSKILL.mdcore2,012 bytesscripts/ralph-loop.ps1runs15,087 bytes
Read SKILL.md
# ralph-loop
This is a Codex-oriented `ralph-loop` command with two execution engines.
## Engine model
- Keeps the same command name: `ralph-loop`.
- Keeps the same default state file format: `.claude/ralph-loop.local.md`.
- Default `compat` engine keeps local-state semantics and manual `--next`.
- Optional `open` engine delegates to external `open-ralph-wiggum` CLI for auto-iteration.
## Script
- Script path: `scripts/ralph-loop.ps1`rdkit
When your agent uses it
Core cheminformatics toolkit for SMILES/SDF/InChI parsing, descriptors (MW, LogP, TPSA), fingerprints, ECFP/Morgan fingerprints, substructure search, 2D/3D generation, similarity, reactions, and datamol-style molecule standardization when no separate wrapper skill is routed.
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
5,218 tokensWhen the skill is activated
Reference documents
11,215 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Capabilities
- Common Workflows
- Best Practices
- Common Pitfalls
- Resources
Scripts executed separately
scripts/molecular_properties.pyscripts/similarity_search.pyscripts/substructure_filter.py
Files
SKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesSKILL.mdcore19,829 bytesreferences/api_reference.mddoc16,789 bytesreferences/descriptors_reference.mddoc11,779 bytesreferences/smarts_patterns.mddoc8,143 bytesscripts/molecular_properties.pyruns7,361 bytesscripts/similarity_search.pyruns9,444 bytesscripts/substructure_filter.pyruns12,351 bytes
Read SKILL.md
# RDKit Cheminformatics Toolkit
## Overview
RDKit is a comprehensive cheminformatics library providing Python APIs for molecular analysis and manipulation. This skill provides guidance for reading/writing molecular structures, calculating descriptors, fingerprinting, substructure searching, chemical reactions, 2D/3D coordinate generation, and molecular visualization. Use this skill for drug discovery, computational chemistry, and cheminformatics research tasks.
## Core Capabilities
### 1. Molecular I/O and Creation
**Reading Molecules:**
Read molecular structures from various formats:
receiving-code-review
When your agent uses it
Review-feedback handling route for CodeRabbit, GitHub, PR, or human reviewer comments. Use before implementing suggestions to verify each finding. Do not use for a fresh code review, security audit, TDD, or final completion evidence.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
1,552 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- The Response Pattern
- Forbidden Responses
- Handling Unclear Feedback
- Source-Specific Handling
- YAGNI Check for "Professional" Features
- Implementation Order
- When To Push Back
- Acknowledging Correct Feedback
- Gracefully Correcting Your Pushback
- Common Mistakes
- Real Examples
- GitHub Thread Replies
- The Bottom Line
Files
SKILL.mdcore6,547 bytes
Read SKILL.md
# Code Review Reception
## Overview
Code review requires technical evaluation, not emotional performance.
**Core principle:** Verify before implementing. Ask before assuming. Technical correctness over social comfort.
## Routing Boundary
Use this skill only when feedback already exists and must be evaluated. A fresh request like "review this PR" belongs to `code-reviewer`; a request like "run OWASP security audit" belongs to `security-reviewer`.
## The Response Pattern
report-generator
When your agent uses it
高级报告生成专家，支持多格式输出、数据可视化和交互式报告生成。
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
4,176 tokensWhen the skill is activated
Reference documents
11,248 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 核心职责
- 工作流程
- 报告类型详解
- 可视化图表系统
- HTML 报告模板
- JSON 数据格式
- 推荐使用入口
- 数据存储
- 双语支持
- 相关资源
- 相关命令
Files
SKILL.mdcore13,779 bytesresources/html-templates.mddoc26,401 bytestemplates/chart-templates.mddoc15,283 bytes
Read SKILL.md
你是高级报告生成专家，专注于创建专业、美观、交互式的 SEO 和 GEO 分析报告。
## 核心职责
1. **多格式报告生成**
- Markdown 格式（文档、版本控制）
- HTML 格式（在线分享、交互式）
- PDF 格式（打印、归档）
- JSON 格式（API 集成、数据处理）
- Excel 格式（数据分析、表格）
2. **数据可视化**
- 折线图（趋势分析）
- 柱状图（对比分析）requesting-code-review
When your agent uses it
Prepare and request a code review after implementation or before merge by assembling scope, requirements, git range, and reviewer instructions.
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
727 tokensWhen the skill is activated
Reference documents
784 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- When to Request Review
- How to Request
- Example
- Integration with Workflows
- Red Flags
Files
SKILL.mdcore3,173 bytesSKILL.mdcore3,173 bytescode-reviewer.mddoc3,385 bytes
Read SKILL.md
# Requesting Code Review
Prepare a complete review request so the reviewer can evaluate the exact change against the intended requirements.
**Core principle:** Review early, review often.
## Routing Boundary
Use this skill when the user needs to prepare or request a code review.
This skill owns the request package: implementation summary, requirements reference, base/head git range, reviewer prompt, and response handling checklist.
Use `code-reviewer` for the actual review findings.
research-grants
When your agent uses it
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
7,399 tokensWhen the skill is activated
Reference documents
45,390 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Proposal Outputs
- Agency-Specific Overview
- Core Components of Research Proposals
- Review Criteria by Agency
- Writing Principles for Competitive Proposals
- Common Proposal Types
- Resubmission Strategies
- Common Mistakes to Avoid
- Workflow for Grant Development
- Integration with Other Skills
- Resources
- Templates and Assets
- Scripts and Tools
Files
SKILL.mdcore36,080 bytesSKILL.mdcore36,080 bytesassets/budget_justification_template.mddoc21,866 bytesassets/nih_specific_aims_template.mddoc11,120 bytesassets/nsf_project_summary_template.mddoc5,886 bytesreferences/README.mddoc9,414 bytesreferences/broader_impacts.mddoc23,284 bytesreferences/darpa_guidelines.mddoc20,501 bytesreferences/doe_guidelines.mddoc19,409 bytesreferences/nih_guidelines.mddoc30,192 bytesreferences/nsf_guidelines.mddoc21,683 bytesreferences/nstc_guidelines.mddoc26,945 bytesreferences/specific_aims_guide.mddoc21,040 bytes
Read SKILL.md
# Research Grant Writing
## Overview
Research grant writing is the process of developing competitive funding proposals for federal agencies and foundations. Master agency-specific requirements, review criteria, narrative structure, budget preparation, and compliance for NSF (National Science Foundation), NIH (National Institutes of Health), DOE (Department of Energy), DARPA (Defense Advanced Research Projects Agency), and Taiwan's NSTC (National Science and Technology Council) submissions.
**Critical Principle: Grants are persuasive documents that must simultaneously demonstrate scientific rigor, innovation, feasibility, and broader impact.** Each agency has distinct priorities, review criteria, formatting requirements, and strategic goals that must be addressed.
## When to Use This Skill
This skill should be used when:
- Writing research proposals for NSF, NIH, DOE, DARPA, or NSTC programs
- Preparing project descriptions, specific aims, or technical narratives
- Developing broader impacts or significance statementsresearch-lookup
When your agent uses it
Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Automatically selects the best model based on query complexity. Search academic papers, recent studies, technical documentation, and general research information with citations.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
4,102 tokensWhen the skill is activated
Reference documents
847 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- Automatic Model Selection
- Technical Integration
- Query Best Practices
- Integration with Scientific Writing
- Error Handling and Limitations
- Usage Examples
- Performance and Cost Considerations
- Security and Ethical Considerations
- Complementary Tools
- Summary
Scripts executed separately
examples.pylookup.pyresearch_lookup.pyscripts/research_lookup.py
Files
README.mddoc4,076 bytesSKILL.mdcore19,869 bytesSKILL.mdcore19,869 bytesSKILL.mdcore19,869 bytesSKILL.mdcore19,869 bytesSKILL.mdcore19,869 bytesSKILL.mdcore19,869 bytesexamples.pyruns5,672 byteslookup.pyruns2,561 bytesresearch_lookup.pyruns16,567 bytesscripts/research_lookup.pyruns16,530 bytes
Read SKILL.md
# Research Information Lookup
## Overview
This skill enables real-time research information lookup using Perplexity's Sonar models through OpenRouter. It intelligently selects between **Sonar Pro Search** (fast, efficient lookup) and **Sonar Reasoning Pro** (deep analytical reasoning) based on query complexity. The skill provides access to current academic literature, recent studies, technical documentation, and general research information with proper citations and source attribution.
## When to Use This Skill
Use this skill when you need:
- **Current Research Information**: Latest studies, papers, and findings in a specific field
- **Literature Verification**: Check facts, statistics, or claims against current research
- **Background Research**: Gather context and supporting evidence for scientific writing
- **Citation Sources**: Find relevant papers and studies to cite in manuscriptsrowan
When your agent uses it
Cloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Use when tasks involve quantum chemistry calculations, molecular property prediction, DFT or semiempirical methods, neural network potentials (AIMNet2), protein-ligand binding predictions, or automated computational chemistry pipelines. Provides cloud compute resources with no local setup required.
What it loads into context
Frontmatter
145 tokensAlways available to the agent
SKILL.md
3,153 tokensWhen the skill is activated
Reference documents
16,897 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- Installation and Authentication
- Core Workflows
- RDKit-Native API
- Workflow Management
- Computational Methods
- Reference Documentation
- Common Patterns
- Best Practices
- Error Handling
- Additional Resources
Files
SKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesSKILL.mdcore12,061 bytesreferences/api_reference.mddoc10,003 bytesreferences/molecule_handling.mddoc9,125 bytesreferences/proteins_and_organization.mddoc9,077 bytesreferences/rdkit_native.mddoc10,756 bytesreferences/results_interpretation.mddoc11,400 bytesreferences/workflow_types.mddoc11,699 bytes
Read SKILL.md
# Rowan: Cloud-Based Quantum Chemistry Platform
## Routing Boundary
Use this skill only for explicit Rowan context, including Rowan, rowan-python, labs.rowansci.com, the Rowan API, or a Rowan-specific chemistry workflow. Do not use it for generic chemistry, RDKit, PubChem, ChEMBL, docking, pKa, conformer search, quantum chemistry, molecular machine learning, Boltz, or Chai-1 unless explicit Rowan context is present.
## Overview
Rowan is a cloud-based computational chemistry platform that provides programmatic access to quantum chemistry workflows through a Python API. It enables automation of complex molecular simulations without requiring local computational resources or expertise in multiple quantum chemistry packages.
**Key Capabilities:**
- Molecular property prediction (pKa, redox potential, solubility, ADMET-Tox)
- Geometry optimization and conformer searching
- Protein-ligand docking with AutoDock Vinascanpy
When your agent uses it
Single-cell RNA-seq and retained scverse workflow owner. Load .h5ad/10X data, manage AnnData metadata, plan scVI/scANVI batch-correction workflows, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
2,975 tokensWhen the skill is activated
Reference documents
6,116 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- Standard Analysis Workflow
- Common Tasks
- Key Parameters to Adjust
- Common Pitfalls and Best Practices
- Bundled Resources
- Additional Resources
- Tips for Effective Analysis
Scripts executed separately
assets/analysis_template.pyscripts/qc_analysis.py
Files
SKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesSKILL.mdcore11,634 bytesassets/analysis_template.pyruns9,515 bytesreferences/api_reference.mddoc7,415 bytesreferences/plotting_guide.mddoc9,695 bytesreferences/standard_workflow.mddoc5,529 bytesscripts/qc_analysis.pyruns6,706 bytes
Read SKILL.md
# Scanpy: Single-Cell Analysis
## Overview
Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.
In the bundled Vibe-Skills routing surface, this skill also absorbs the former AnnData and scVI/scANVI route surfaces. Use it for h5ad container handling and scverse latent-model planning when those tasks appear inside a single-cell workflow.
## When to Use This Skill
This skill should be used when:
- Analyzing single-cell RNA-seq data (.h5ad, 10X, CSV formats)
- Performing quality control on scRNA-seq datasets
- Creating UMAP, t-SNE, or PCA visualizationsscholar-evaluation
When your agent uses it
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
What it loads into context
Frontmatter
59 tokensAlways available to the agent
SKILL.md
2,378 tokensWhen the skill is activated
Reference documents
4,081 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Evaluation Workflow
- Resources
- Best Practices
- Example Evaluation Workflow
- Integration with Scientific Writer
- Notes
- Citation
Scripts executed separately
scripts/calculate_scores.py
Files
SKILL.mdcore12,257 bytesSKILL.mdcore12,257 bytesSKILL.mdcore12,257 bytesreferences/evaluation_framework.mddoc19,950 bytesscripts/calculate_scores.pyruns11,551 bytes
Read SKILL.md
# Scholar Evaluation
## Overview
Apply the ScholarEval framework to systematically evaluate scholarly and research work. This skill provides structured evaluation methodology based on peer-reviewed research assessment criteria, enabling comprehensive analysis of academic papers, research proposals, literature reviews, and scholarly writing across multiple quality dimensions.
## When to Use This Skill
Use this skill when:
- Evaluating research papers for quality and rigor
- Assessing literature review comprehensiveness and quality
- Reviewing research methodology design
- Scoring data analysis approaches
- Evaluating scholarly writing and presentationscholarly-publishing
When your agent uses it
Use when planning an end-to-end scholarly publishing workflow, including manuscript source-of-truth, submission assets, revision/rebuttal files, camera-ready checks, reproducible build expectations, and publication package structure.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
1,862 tokensWhen the skill is activated
Reference documents
651 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 你会得到什么（输出契约）
- 何时使用（触发场景）
- 输入信息（最小问询）
- 工作流（可执行流程）
- 规范（Meta Rules）
- 案例库（GitHub 高信号仓库）
- 快速调用示例（给 VCO 路由用）
Files
SKILL.mdcore6,518 bytesreferences/case-library.mddoc2,101 bytestemplates/submission-manifest.ymlasset1,582 bytes
Read SKILL.md
# Scholarly Publishing (论文投稿全流程)
## 你会得到什么（输出契约）
当用户说“我要投稿/返修/相机就绪/需要 LaTeX 工程化/写 rebuttal/写 cover letter”时，本 skill 负责把目标拆成**可交付的出版资产包**：
- `manuscript/`：论文源文件（LaTeX / Word / Markdown 任一作为 *source-of-truth*）
- `figures/`：每张图的源代码/源数据/最终导出要求（PDF/EPS/SVG/TIFF）
- `supplement/`：补充材料（方法细节、附录、扩展实验、额外图表）
- `submission/`：投稿所需文件（cover letter、graphical abstract、highlights、checklist、打包 zip）
- `revision/`：返修资产（rebuttal、diff、逐条回应矩阵）
- `build/`：可复现构建产物（PDF、打包 zip、CI 日志）
> 目标不是“写一段文字/画一张图”，而是产出**能提交、能返修、能复用、能审计**的一套文件与规范。scientific-brainstorming
When your agent uses it
Open-ended scientific ideation partner. Use for research gaps, mechanism exploration, interdisciplinary connections, assumptions, possible research directions, and lightweight literature matrix or A+B paper-combination idea mapping. For structured testable hypotheses and validation plans, use hypothesis-generation instead.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
1,622 tokensWhen the skill is activated
Reference documents
2,461 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Principles
- Brainstorming Workflow
- Adaptive Techniques
- Resources
- Notes
Files
SKILL.mdcore8,426 bytesreferences/brainstorming_methods.mddoc12,065 bytes
Read SKILL.md
# Scientific Brainstorming
## Overview
Scientific brainstorming is a conversational process for generating novel research ideas. Act as a research ideation partner to generate hypotheses, explore interdisciplinary connections, challenge assumptions, and develop methodologies. Apply this skill for creative scientific problem-solving.
## When to Use This Skill
This skill should be used when:
- Generating novel research ideas or directions
- Exploring interdisciplinary connections and analogies
- Challenging assumptions in existing research frameworks
- Developing new methodological approaches
- Identifying research gaps or opportunitiesscientific-critical-thinking
When your agent uses it
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
What it loads into context
Frontmatter
90 tokensAlways available to the agent
SKILL.md
4,779 tokensWhen the skill is activated
Reference documents
17,282 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- Application Guidelines
- Reference Materials
- Remember
Files
SKILL.mdcore23,704 bytesSKILL.mdcore23,704 bytesreferences/common_biases.mddoc11,093 bytesreferences/evidence_hierarchy.mddoc13,444 bytesreferences/experimental_design.mddoc16,068 bytesreferences/logical_fallacies.mddoc18,014 bytesreferences/scientific_method.mddoc6,100 bytesreferences/statistical_pitfalls.mddoc15,726 bytes
Read SKILL.md
# Scientific Critical Thinking
## Overview
Critical thinking is a systematic process for evaluating scientific rigor. Assess methodology, experimental design, statistical validity, biases, confounding, and evidence quality using GRADE and Cochrane ROB frameworks. Apply this skill for critical analysis of scientific claims.
## When to Use This Skill
This skill should be used when:
- Evaluating research methodology and experimental design
- Assessing statistical validity and evidence quality
- Identifying biases and confounding in studies
- Reviewing scientific claims and conclusions
- Conducting systematic reviews or meta-analysesscientific-data-preprocessing
When your agent uses it
⚠<U+FE0F> CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠<U+FE0F> Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.
What it loads into context
Frontmatter
141 tokensAlways available to the agent
SKILL.md
4,886 tokensWhen the skill is activated
Reference documents
23,240 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Core Mission
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Examples
- References
- Maintenance
Files
README.mddoc8,249 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesSKILL.mdcore19,953 bytesUPDATE_LOG_V1.1.mddoc13,146 bytesreferences/ai-common-pitfalls.mddoc23,215 bytesreferences/decision-trees.mddoc14,225 bytesreferences/error-case-studies.mddoc12,657 bytesreferences/index.mddoc1,890 bytesreferences/validation-checklist.mddoc13,662 bytes
Read SKILL.md
# Scientific Data Preprocessing Skill
⚠<U+FE0F> **CRITICAL: USER'S HARD-WON EXPERIENCE - MANDATORY CONSULTATION** ⚠<U+FE0F>
This skill encapsulates painful lessons learned from real preprocessing disasters (88.9% error rate documented). **ALWAYS use this skill for planning, reflection, and validation when ANY data preprocessing is involved.**
**Why this skill is mandatory:**
- Based on actual project failures (V1.0, V2.0 case studies)
- Prevents data leakage that causes production disasters
- Catches semantic errors AI agents commonly make
- Saves weeks of debugging and model retraining
**When to invoke (DO NOT SKIP):**
- ✅ Before starting ANY data preprocessing taskscientific-reporting
When your agent uses it
Write research/technical reports with strong structure + figure standards. Supports Markdown/HTML/PDF outputs (Quarto optional), executive summary, methods, results, discussion, and reproducibility appendix.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
884 tokensWhen the skill is activated
Reference documents
170 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 你遇到的痛点（为什么需要这个 skill）
- 适用场景（关键词）
- 输入（最小信息）
- 输出（默认目录）
- 工作流（强制顺序）
- 质量门禁（报告交付前）
Files
SKILL.mdcore3,181 bytestemplates/report-skeleton.mddoc711 bytes
Read SKILL.md
# Scientific Reporting（科研/技术报告）
## 你遇到的痛点（为什么需要这个 skill）
很多“报告写作失败”不是写不出来，而是：
- 路由误入 `docs-media`（被 PDF/Word 关键词抢走）
- 报告没有结构（缺少 Executive Summary / 方法可复现 / 结果可追溯）
- 图表不达标（截图、低 DPI、字体不一致、颜色不友好）
这个 skill 的职责是：**把报告当成可交付工程**，并把图表与叙事纳入同一规范。
---
## 适用场景（关键词）scientific-schematics
When your agent uses it
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
What it loads into context
Frontmatter
95 tokensAlways available to the agent
SKILL.md
5,376 tokensWhen the skill is activated
Reference documents
7,465 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start: Generate Any Diagram
- When to Use This Skill
- How to Use This Skill
- Smart Iterative Refinement Workflow
- Advanced AI Generation Usage
- AI Generation Examples
- Command-Line Usage
- Best Practices Summary
- Troubleshooting Common Issues
- Resources and References
- Integration with Other Skills
- Quick Reference Checklist
- Environment Setup
- Getting Started
Scripts executed separately
scripts/example_usage.shscripts/generate_schematic.pyscripts/generate_schematic_ai.py
Files
SKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesSKILL.mdcore23,776 bytesreferences/QUICK_REFERENCE.mddoc4,790 bytesreferences/README.mddoc8,686 bytesreferences/best_practices.mddoc15,910 bytesscripts/example_usage.shruns3,052 bytesscripts/generate_schematic.pyruns5,016 bytesscripts/generate_schematic_ai.pyruns33,173 bytes
Read SKILL.md
# Scientific Schematics and Diagrams
## Overview
Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. **This skill uses Nano Banana Pro AI for diagram generation with Gemini 3 Pro quality review.**
**How it works:**
- Describe your diagram in natural language
- Nano Banana Pro generates publication-quality images automatically
- **Gemini 3 Pro reviews quality** against document-type thresholds
- **Smart iteration**: Only regenerates if quality is below threshold
- Publication-ready output in minutes
- No coding, templates, or manual drawing required
scientific-slides
When your agent uses it
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
What it loads into context
Frontmatter
92 tokensAlways available to the agent
SKILL.md
10,887 tokensWhen the skill is activated
Reference documents
39,628 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Slide Generation with Nano Banana Pro
- Nano Banana Pro Script Reference
- Prompt Writing for Slide Generation
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- Workflow for Presentation Development
- Integration with Other Skills
- Common Pitfalls to Avoid
- Tools and Scripts
- Reference Files
- Assets
- Quick Start Guide
- Summary: Key Principles
Scripts executed separately
../document-skills/pptx/scripts/thumbnail.pyscripts/generate_slide_image.pyscripts/generate_slide_image_ai.pyscripts/pdf_to_images.pyscripts/slides_to_pdf.pyscripts/validate_presentation.py
Files
../document-skills/pptx/scripts/thumbnail.pyruns15,484 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesSKILL.mdcore47,290 bytesassets/beamer_template_conference.texasset9,983 bytesassets/beamer_template_defense.texasset26,503 bytesassets/beamer_template_seminar.texasset23,247 bytesassets/powerpoint_design_guide.mddoc18,989 bytesassets/timing_guidelines.mddoc14,723 bytesreferences/beamer_guide.mddoc19,321 bytesreferences/data_visualization_slides.mddoc17,863 bytesreferences/presentation_structure.mddoc22,220 bytesreferences/slide_design_principles.mddoc23,878 bytesreferences/talk_types_guide.mddoc20,146 bytesreferences/visual_review_workflow.mddoc20,170 bytesscripts/generate_slide_image.pyruns5,309 bytesscripts/generate_slide_image_ai.pyruns29,060 bytesscripts/pdf_to_images.pyruns6,644 bytesscripts/slides_to_pdf.pyruns7,423 bytesscripts/validate_presentation.pyruns13,115 bytes
Read SKILL.md
# Scientific Slides
## Overview
Scientific presentations are a critical medium for communicating research, sharing findings, and engaging with academic and professional audiences. This skill provides comprehensive guidance for creating effective scientific presentations, from structure and content development to visual design and delivery preparation.
**Key Focus**: Oral presentations for conferences, seminars, defenses, and professional talks.
**CRITICAL DESIGN PHILOSOPHY**: Scientific presentations should be VISUALLY ENGAGING and RESEARCH-BACKED. Avoid dry, text-heavy slides at all costs. Great scientific presentations combine:
- **Compelling visuals**: High-quality figures, images, diagrams (not just bullet points)
- **Research context**: Proper citations from research-lookup establishing credibility
- **Minimal text**: Bullet points as prompts, YOU provide the explanation verbally
- **Professional design**: Modern color schemes, strong visual hierarchy, generous white space
- **Story-driven**: Clear narrative arc, not just data dumpsscientific-visualization
When your agent uses it
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
What it loads into context
Frontmatter
49 tokensAlways available to the agent
SKILL.md
6,444 tokensWhen the skill is activated
Reference documents
12,797 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start Guide
- Core Principles and Best Practices
- Common Tasks
- Statistical Rigor
- Working with Different Plotting Libraries
- Resources
- Workflow Summary
- Common Pitfalls to Avoid
- Final Checklist
Scripts executed separately
assets/color_palettes.pyscripts/figure_export.pyscripts/style_presets.py
Files
SKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesSKILL.mdcore25,298 bytesassets/color_palettes.pyruns5,754 bytesassets/nature.mplstyleasset1,449 bytesassets/presentation.mplstyleasset1,309 bytesassets/publication.mplstyleasset1,474 bytesreferences/color_palettes.mddoc9,861 bytesreferences/journal_requirements.mddoc9,533 bytesreferences/matplotlib_examples.mddoc18,103 bytesreferences/publication_guidelines.mddoc8,556 bytesscripts/figure_export.pyruns10,904 bytesscripts/style_presets.pyruns12,199 bytes
Read SKILL.md
# Scientific Visualization
## Overview
Scientific visualization transforms data into clear, accurate figures for publication. Create journal-ready plots with multi-panel layouts, error bars, significance markers, and colorblind-safe palettes. Export as PDF/EPS/TIFF using matplotlib, seaborn, and plotly for manuscripts.
## When to Use This Skill
This skill should be used when:
- Creating plots or visualizations for scientific manuscripts
- Preparing figures for journal submission (Nature, Science, Cell, PLOS, etc.)
- Ensuring figures are colorblind-friendly and accessible
- Making multi-panel figures with consistent styling
- Exporting figures at correct resolution and formatscientific-writing
When your agent uses it
Use when writing or revising scientific manuscript prose: IMRAD sections, abstracts, figure/table captions, citation-integrated paragraphs, reporting-guideline language, terminology, clarity, and journal-submission text.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
4,535 tokensWhen the skill is activated
Reference documents
29,132 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Figure And Table Prose Boundary
- Core Capabilities
- Workflow for Manuscript Development
- Boundary
- References
Files
SKILL.mdcore22,721 bytesSKILL.mdcore22,721 bytesreferences/citation_styles.mddoc23,705 bytesreferences/figures_tables.mddoc27,883 bytesreferences/imrad_structure.mddoc23,921 bytesreferences/reporting_guidelines.mddoc25,012 bytesreferences/writing_principles.mddoc27,593 bytes
Read SKILL.md
# Scientific Writing
## Overview
Scientific writing is a process for communicating research with precision and clarity. Write manuscripts using IMRAD structure, citation-integrated prose, figure/table captions, and reporting guidelines (CONSORT/STROBE/PRISMA). Apply this skill for research papers and journal submissions.
**Critical Principle: Always write in full paragraphs with flowing prose. Never submit bullet points in the final manuscript.** Use a two-stage process: first create section outlines with key points, then convert those outlines into complete paragraphs.
## When to Use This Skill
This skill should be used when:
- Writing or revising any section of a scientific manuscript (abstract, introduction, methods, results, discussion)
- Structuring a research paper using IMRAD or other standard formats
- Formatting citations and references in specific styles (APA, AMA, Vancouver, Chicago, IEEE)scikit-bio
When your agent uses it
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.
What it loads into context
Frontmatter
59 tokensAlways available to the agent
SKILL.md
3,412 tokensWhen the skill is activated
Reference documents
5,039 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Best Practices
- Reference Documentation
- Additional Resources
Files
SKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesSKILL.mdcore14,681 bytesreferences/api_reference.mddoc18,564 bytes
Read SKILL.md
# scikit-bio
## Overview
scikit-bio is a comprehensive Python library for working with biological data. Apply this skill for bioinformatics analyses spanning sequence manipulation, alignment, phylogenetics, microbial ecology, and multivariate statistics.
## When to Use This Skill
This skill should be used when the user:
- Works with biological sequences (DNA, RNA, protein)
- Needs to read/write biological file formats (FASTA, FASTQ, GenBank, Newick, BIOM, etc.)
- Performs sequence alignments or searches for motifs
- Constructs or analyzes phylogenetic trees
- Calculates diversity metrics (alpha/beta diversity, UniFrac distances)scikit-learn
When your agent uses it
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
3,475 tokensWhen the skill is activated
Reference documents
20,407 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Installation
- When to Use This Skill
- Quick Start
- Core Capabilities
- Example Scripts
- Reference Documentation
- Common Workflows
- Best Practices
- Troubleshooting Common Issues
- Additional Resources
Scripts executed separately
scripts/classification_pipeline.pyscripts/clustering_analysis.py
Files
SKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesSKILL.mdcore15,827 bytesreferences/model_evaluation.mddoc15,454 bytesreferences/pipelines_and_composition.mddoc14,770 bytesreferences/preprocessing.mddoc15,603 bytesreferences/quick_reference.mddoc11,508 bytesreferences/supervised_learning.mddoc11,011 bytesreferences/unsupervised_learning.mddoc14,440 bytesscripts/classification_pipeline.pyruns8,044 bytesscripts/clustering_analysis.pyruns11,396 bytes
Read SKILL.md
# Scikit-learn
## Overview
This skill provides comprehensive guidance for machine learning tasks using scikit-learn, the industry-standard Python library for classical machine learning. Use this skill for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building production-ready ML pipelines.
## Installation
```bash
# Install scikit-learn using uv
uv uv pip install scikit-learn
# Optional: Install visualization dependencies
uv uv pip install matplotlib seabornscikit-survival
When your agent uses it
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
3,586 tokensWhen the skill is activated
Reference documents
15,482 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Typical Workflows
- Integration with scikit-learn
- Best Practices
- Common Pitfalls to Avoid
- Reference Files
- Additional Resources
- Quick Reference: Key Imports
Files
SKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesSKILL.mdcore15,011 bytesreferences/competing-risks.mddoc11,986 bytesreferences/cox-models.mddoc5,238 bytesreferences/data-handling.mddoc12,094 bytesreferences/ensemble-models.mddoc9,529 bytesreferences/evaluation-metrics.mddoc10,850 bytesreferences/svm-models.mddoc11,096 bytes
Read SKILL.md
# scikit-survival: Survival Analysis in Python
## Overview
scikit-survival is a Python library for survival analysis built on top of scikit-learn. It provides specialized tools for time-to-event analysis, handling the unique challenge of censored data where some observations are only partially known.
Survival analysis aims to establish connections between covariates and the time of an event, accounting for censored records (particularly right-censored data from studies where participants don't experience events during observation periods).
## When to Use This Skill
Use this skill when:
- Performing survival analysis or time-to-event modeling
- Working with censored data (right-censored, left-censored, or interval-censored)
- Fitting Cox proportional hazards models (standard or penalized)scrapling
When your agent uses it
CLI-first web scraping & content extraction with optional MCP server. Use when you have target URLs and need clean, selector-based outputs (html/md/txt).
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,062 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Boundaries (vs Playwright / Search)
- Prerequisite check (required)
- Installation (recommended)
- Wrapper script (Windows convenience)
- Common CLI patterns
- MCP server relationship (optional)
- Safety & ops notes
Scripts executed separately
scripts/scrapling.ps1
Files
SKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesSKILL.mdcore4,358 bytesscripts/scrapling.ps1runs1,142 bytes
Read SKILL.md
# Scrapling Skill (VCO)
Scrapling is a Python-based web scraping / extraction toolkit that exposes:
- a **CLI** (`scrapling ...`) for fetching + extracting content into files
- an **optional MCP server** (`scrapling mcp`) so an agent can call structured scraping tools
This skill is **CLI-first**. Prefer it when you already have URLs and need reliable, repeatable extraction (CSS selector → file).
## When to use
Use `scrapling` when you need:
- Extract **specific parts** of a web page (CSS selector / XPath) into `.txt` / `.md` / `.html`
- Run **repeatable scraping jobs** (batch URLs with a small wrapper script)screenshot
When your agent uses it
Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,941 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Tool priority
- macOS permission preflight (reduce repeated prompts)
- macOS and Linux (Python helper)
- Windows (PowerShell helper)
- Direct OS commands (fallbacks)
- Error handling
Scripts executed separately
scripts/ensure_macos_permissions.shscripts/take_screenshot.ps1scripts/take_screenshot.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesSKILL.mdcore7,754 bytesagents/openai.yamlasset273 bytesassets/screenshot-small.svgasset1,019 bytesassets/screenshot.pngasset860 bytesscripts/ensure_macos_permissions.shruns1,702 bytesscripts/macos_display_info.swiftasset482 bytesscripts/macos_permissions.swiftasset929 bytesscripts/macos_window_info.swiftasset3,595 bytesscripts/take_screenshot.ps1runs4,947 bytesscripts/take_screenshot.pyruns19,659 bytes
Read SKILL.md
# Screenshot Capture
Follow these save-location rules every time:
1) If the user specifies a path, save there.
2) If the user asks for a screenshot without a path, save to the OS default screenshot location.
3) If Codex needs a screenshot for its own inspection, save to the temp directory.
## Tool priority
- Prefer tool-specific screenshot capabilities when available (for example: a Figma MCP/skill for Figma files, or Playwright/agent-browser tools for browsers and Electron apps).
- Use this skill when explicitly asked, for whole-system desktop captures, or when a tool-specific capture cannot get what you need.
- Otherwise, treat this skill as the default for desktop apps without a better-integrated capture tool.seaborn
When your agent uses it
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
5,008 tokensWhen the skill is activated
Reference documents
18,289 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Design Philosophy
- Quick Start
- Core Plotting Interfaces
- Plotting Functions by Category
- Multi-Plot Grids
- Figure-Level vs Axes-Level Functions
- Data Structure Requirements
- Color Palettes
- Theming and Aesthetics
- Best Practices
- Common Patterns
- Troubleshooting
- Resources
Files
SKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesSKILL.mdcore19,377 bytesreferences/examples.mddoc17,624 bytesreferences/function_reference.mddoc24,615 bytesreferences/objects_interface.mddoc20,801 bytes
Read SKILL.md
# Seaborn Statistical Visualization
## Overview
Seaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.
## Design Philosophy
Seaborn follows these core principles:
1. **Dataset-oriented**: Work directly with DataFrames and named variables rather than abstract coordinates
2. **Semantic mapping**: Automatically translate data values into visual properties (colors, sizes, styles)
3. **Statistical awareness**: Built-in aggregation, error estimation, and confidence intervals
4. **Aesthetic defaults**: Publication-ready themes and color palettes out of the boxsecurity-best-practices
When your agent uses it
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
What it loads into context
Frontmatter
79 tokensAlways available to the agent
SKILL.md
1,661 tokensWhen the skill is activated
Reference documents
90,699 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Workflow
- Workflow Decision Tree
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore8,612 bytesagents/openai.yamlasset237 bytesreferences/golang-general-backend-security.mddoc38,659 bytesreferences/javascript-express-web-server-security.mddoc49,357 bytesreferences/javascript-general-web-frontend-security.mddoc38,638 bytesreferences/javascript-jquery-web-frontend-security.mddoc33,581 bytesreferences/javascript-typescript-nextjs-web-server-security.mddoc43,423 bytesreferences/javascript-typescript-react-web-frontend-security.mddoc41,686 bytesreferences/javascript-typescript-vue-web-frontend-security.mddoc31,445 bytesreferences/python-django-web-server-security.mddoc38,661 bytesreferences/python-fastapi-web-server-security.mddoc44,926 bytesreferences/python-flask-web-server-security.mddoc31,748 bytes
Read SKILL.md
# Security Best Practices
## Overview
This skill provides a description of how to identify the language and frameworks used by the current context, and then to load information from this skill's references directory about the security best practices for this language and or frameworks.
This information, if present, can be used to write new secure by default code, or to passively detect major issues within existing code, or (if requested by the user) provide a vulnerability report and suggest fixes.
## Workflow
The initial step for this skill is to identify ALL languages and ALL frameworks which you are being asked to use or already exist in the scope of the project you are working in. Focus on the primary core frameworks. Often you will want to identify both frontend and backend languages and frameworks.
Then check this skill's references directory to see if there are any relevant documentation for the language and or frameworks. Make sure you read ALL reference files which relate to the specific framework or language. The format of the filenames is `<language>-<framework>-<stack>-security.md`. You should also check if there is a `<language>-general-<stack>-security.md` which is agnostic to the framework you may be using.
security-ownership-map
When your agent uses it
Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
2,079 tokensWhen the skill is activated
Reference documents
675 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Requirements
- Workflow
- Quick start
- Sensitivity rules
- Output artifacts
- LLM query helper
- Basic security queries
- Graph persistence
- Notes
Scripts executed separately
scripts/build_ownership_map.pyscripts/community_maintainers.pyscripts/query_ownership.pyscripts/run_ownership_map.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesSKILL.mdcore8,736 bytesagents/openai.yamlasset253 bytesreferences/neo4j-import.mddoc2,428 bytesscripts/build_ownership_map.pyruns34,330 bytesscripts/community_maintainers.pyruns18,122 bytesscripts/query_ownership.pyruns17,991 bytesscripts/run_ownership_map.pyruns5,890 bytes
Read SKILL.md
# Security Ownership Map
## Overview
Build a bipartite graph of people and files from git history, then compute ownership risk and export graph artifacts for Neo4j/Gephi. Also build a file co-change graph (Jaccard similarity on shared commits) to cluster files by how they move together while ignoring large, noisy commits.
## Requirements
- Python 3
- `networkx` (required; community detection is enabled by default)
Install with:
```bashsecurity-reviewer
When your agent uses it
Dedicated security-audit route for OWASP-style risks, secret leaks, auth flaws, injection, unsafe input handling, SSRF/XSS, and sensitive-data exposure. Use instead of code-reviewer when the prompt explicitly asks for security, vulnerability, threat, auth, or OWASP review.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
452 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Security Review Workflow
- Vibe Integration
Files
SKILL.mdcore2,092 bytes
Read SKILL.md
# security-reviewer (Codex Compatibility)
Use this skill after code changes that touch input handling, auth, APIs, data access, uploads, payments, or external integrations.
## Routing Boundary
Use this skill when security is the main question:
- OWASP/security audit/security review
- secret leak, token exposure, unsafe logging
- auth bypass, authorization gaps, session/token handling
- injection, XSS, SSRF, unsafe file upload or command execution
Do not use this as the default owner for ordinary maintainability review. If security is only one item in a general PR review, `code-reviewer` can flag it, but explicit security-audit wording should route here.
security-threat-model
When your agent uses it
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
1,108 tokensWhen the skill is activated
Reference documents
3,032 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick start
- Workflow
- Risk prioritization guidance (illustrative, not exhaustive)
- References
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore5,561 bytesagents/openai.yamlasset254 bytesreferences/prompt-template.mddoc12,642 bytesreferences/security-controls-and-assets.mddoc1,680 bytes
Read SKILL.md
# Threat Model Source Code Repo
Deliver an actionable AppSec-grade threat model that is specific to the repository or a project path, not a generic checklist. Anchor every architectural claim to evidence in the repo and keep assumptions explicit. Prioritizing realistic attacker goals and concrete impacts over generic checklists.
## Quick start
1) Collect (or infer) inputs:
- Repo root path and any in-scope paths.
- Intended usage, deployment model, internet exposure, and auth expectations (if known).
- Any existing repository summary or architecture spec.
- Use prompts in `references/prompt-template.md` to generate a repository summary.
- Follow the required output contract in `references/prompt-template.md`. Use it verbatim when possible.
## Workflowsenior-computer-vision
When your agent uses it
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
1,212 tokensWhen the skill is activated
Reference documents
880 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Core Expertise
- Tech Stack
- Reference Documentation
- Production Patterns
- Best Practices
- Performance Targets
- Security & Compliance
- Common Commands
- Resources
- Senior-Level Responsibilities
Scripts executed separately
scripts/dataset_pipeline_builder.pyscripts/inference_optimizer.pyscripts/vision_model_trainer.py
Files
SKILL.mdcore5,593 bytesSKILL.mdcore5,593 bytesSKILL.mdcore5,593 bytesSKILL.mdcore5,593 bytesSKILL.mdcore5,593 bytesSKILL.mdcore5,593 bytesreferences/computer_vision_architectures.mddoc1,447 bytesreferences/object_detection_optimization.mddoc1,447 bytesreferences/production_vision_systems.mddoc1,439 bytesscripts/dataset_pipeline_builder.pyruns2,817 bytesscripts/inference_optimizer.pyruns2,794 bytesscripts/vision_model_trainer.pyruns2,797 bytes
Read SKILL.md
# Senior Computer Vision Engineer
World-class senior computer vision engineer skill for production-grade AI/ML/Data systems.
## Quick Start
### Main Capabilities
```bash
# Core Tool 1
python scripts/vision_model_trainer.py --input data/ --output results/
# Core Tool 2
python scripts/inference_optimizer.py --target project/ --analyzesenior-data-scientist
When your agent uses it
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
1,213 tokensWhen the skill is activated
Reference documents
877 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Core Expertise
- Tech Stack
- Reference Documentation
- Production Patterns
- Best Practices
- Performance Targets
- Security & Compliance
- Common Commands
- Resources
- Senior-Level Responsibilities
Scripts executed separately
scripts/experiment_designer.pyscripts/feature_engineering_pipeline.pyscripts/model_evaluation_suite.py
Files
SKILL.mdcore5,630 bytesSKILL.mdcore5,630 bytesSKILL.mdcore5,630 bytesSKILL.mdcore5,630 bytesSKILL.mdcore5,630 bytesSKILL.mdcore5,630 bytesreferences/experiment_design_frameworks.mddoc1,435 bytesreferences/feature_engineering_patterns.mddoc1,435 bytesreferences/statistical_methods_advanced.mddoc1,435 bytesscripts/experiment_designer.pyruns2,784 bytesscripts/feature_engineering_pipeline.pyruns2,827 bytesscripts/model_evaluation_suite.pyruns2,797 bytes
Read SKILL.md
# Senior Data Scientist
World-class senior data scientist skill for production-grade AI/ML/Data systems.
## Quick Start
### Main Capabilities
```bash
# Core Tool 1
python scripts/experiment_designer.py --input data/ --output results/
# Core Tool 2
python scripts/feature_engineering_pipeline.py --target project/ --analyzesenior-ml-engineer
When your agent uses it
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
1,221 tokensWhen the skill is activated
Reference documents
886 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Core Expertise
- Tech Stack
- Reference Documentation
- Production Patterns
- Best Practices
- Performance Targets
- Security & Compliance
- Common Commands
- Resources
- Senior-Level Responsibilities
Scripts executed separately
scripts/ml_monitoring_suite.pyscripts/model_deployment_pipeline.pyscripts/rag_system_builder.py
Files
SKILL.mdcore5,506 bytesSKILL.mdcore5,506 bytesSKILL.mdcore5,506 bytesSKILL.mdcore5,506 bytesSKILL.mdcore5,506 bytesSKILL.mdcore5,506 bytesreferences/llm_integration_guide.mddoc1,421 bytesreferences/mlops_production_patterns.mddoc1,429 bytesreferences/rag_system_architecture.mddoc1,425 bytesscripts/ml_monitoring_suite.pyruns2,782 bytesscripts/model_deployment_pipeline.pyruns2,812 bytesscripts/rag_system_builder.pyruns2,777 bytes
Read SKILL.md
# Senior ML/AI Engineer
World-class senior ml/ai engineer skill for production-grade AI/ML/Data systems.
## Quick Start
### Main Capabilities
```bash
# Core Tool 1
python scripts/model_deployment_pipeline.py --input data/ --output results/
# Core Tool 2
python scripts/rag_system_builder.py --target project/ --analyzesenior-prompt-engineer
When your agent uses it
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
What it loads into context
Frontmatter
92 tokensAlways available to the agent
SKILL.md
1,216 tokensWhen the skill is activated
Reference documents
881 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Core Expertise
- Tech Stack
- Reference Documentation
- Production Patterns
- Best Practices
- Performance Targets
- Security & Compliance
- Common Commands
- Resources
- Senior-Level Responsibilities
Scripts executed separately
scripts/agent_orchestrator.pyscripts/prompt_optimizer.pyscripts/rag_evaluator.py
Files
SKILL.mdcore5,544 bytesSKILL.mdcore5,544 bytesSKILL.mdcore5,544 bytesSKILL.mdcore5,544 bytesSKILL.mdcore5,544 bytesSKILL.mdcore5,544 bytesreferences/agentic_system_design.mddoc1,422 bytesreferences/llm_evaluation_frameworks.mddoc1,430 bytesreferences/prompt_engineering_patterns.mddoc1,434 bytesscripts/agent_orchestrator.pyruns2,780 bytesscripts/prompt_optimizer.pyruns2,770 bytesscripts/rag_evaluator.pyruns2,755 bytes
Read SKILL.md
# Senior Prompt Engineer
World-class senior prompt engineer skill for production-grade AI/ML/Data systems.
## Quick Start
### Main Capabilities
```bash
# Core Tool 1
python scripts/prompt_optimizer.py --input data/ --output results/
# Core Tool 2
python scripts/rag_evaluator.py --target project/ --analyzesentry
When your agent uses it
Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
1,026 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick start
- Core tasks (use bundled script)
- Skill path (set once)
- API requirements
- Inputs and defaults
- Output formatting rules
- Golden test inputs
Scripts executed separately
scripts/sentry_api.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesSKILL.mdcore3,798 bytesagents/openai.yamlasset316 bytesassets/sentry-small.svgasset661 bytesassets/sentry.pngasset1,998 bytesscripts/sentry_api.pyruns7,289 bytes
Read SKILL.md
# Sentry (Read-only Observability)
## Quick start
- If not already authenticated, ask the user to provide a valid `SENTRY_AUTH_TOKEN` (read-only scopes such as `project:read`, `event:read`) or to log in and create one before running commands.
- Set `SENTRY_AUTH_TOKEN` as an env var.
- Optional defaults: `SENTRY_ORG`, `SENTRY_PROJECT`, `SENTRY_BASE_URL`.
- Defaults: org/project `{your-org}`/`{your-project}`, time range `24h`, environment `prod`, limit 20 (max 50).
- Always call the Sentry API (no heuristics, no caching).
If the token is missing, give the user these steps:
[Credential-related source omitted]
2. Create a token with read-only scopes such as `project:read`, `event:read`, and `org:read`.shap
When your agent uses it
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
What it loads into context
Frontmatter
112 tokensAlways available to the agent
SKILL.md
4,287 tokensWhen the skill is activated
Reference documents
15,605 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start Guide
- Core Workflows
- Key Concepts
- Common Patterns
- Performance Optimization
- Troubleshooting
- Integration with Other Tools
- Reference Documentation
- Usage Guidelines
- Best Practices Summary
- Installation
- Additional Resources
Files
SKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesSKILL.mdcore18,350 bytesreferences/explainers.mddoc12,907 bytesreferences/plots.mddoc16,552 bytesreferences/theory.mddoc17,030 bytesreferences/workflows.mddoc19,789 bytes
Read SKILL.md
# SHAP (SHapley Additive exPlanations)
## Overview
SHAP is a unified approach to explain machine learning model outputs using Shapley values from cooperative game theory. This skill provides comprehensive guidance for:
- Computing SHAP values for any model type
- Creating visualizations to understand feature importance
- Debugging and validating model behavior
- Analyzing fairness and bias
- Implementing explainable AI in production
SHAP works with all model types: tree-based models (XGBoost, LightGBM, CatBoost, Random Forest), deep learning models (TensorFlow, PyTorch, Keras), linear models, and black-box models.
similarity-search-patterns
When your agent uses it
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
What it loads into context
Frontmatter
33 tokensAlways available to the agent
SKILL.md
3,758 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Concepts
- Templates
- Best Practices
- Resources
Files
SKILL.mdcore17,977 bytesSKILL.mdcore17,977 bytesSKILL.mdcore17,977 bytesSKILL.mdcore17,977 bytesSKILL.mdcore17,977 bytes
Read SKILL.md
# Similarity Search Patterns
Patterns for implementing efficient similarity search in production systems.
## When to Use This Skill
- Building semantic search systems
- Implementing RAG retrieval
- Creating recommendation engines
- Optimizing search latency
- Scaling to millions of vectors
- Combining semantic and keyword search
## Core Conceptssimpy
When your agent uses it
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
2,832 tokensWhen the skill is activated
Reference documents
12,140 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- When to Use This Skill
- Quick Start
- Core Concepts
- Resources
- Common Simulation Patterns
- Workflow Guide
- Advanced Features
- Scripts and Templates
- Reference Documentation
- Best Practices
- Common Pitfalls
- Example Use Cases
Scripts executed separately
scripts/basic_simulation_template.pyscripts/resource_monitor.py
Files
SKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesSKILL.mdcore12,516 bytesreferences/events.mddoc8,579 bytesreferences/monitoring.mddoc12,923 bytesreferences/process-interaction.mddoc11,525 bytesreferences/real-time.mddoc10,728 bytesreferences/resources.mddoc7,327 bytesscripts/basic_simulation_template.pyruns5,558 bytesscripts/resource_monitor.pyruns11,680 bytes
Read SKILL.md
# SimPy - Discrete-Event Simulation
## Routing Boundary
Use this skill only for SimPy or explicit discrete-event simulation work involving SimPy environments, resources, processes, queues, and event scheduling. Do not use it for generic simulation, Monte Carlo work, agent-based modeling, physics simulation, animation, or SymPy symbolic math unless the user explicitly asks for SimPy.
## Overview
SimPy is a process-based discrete-event simulation framework based on standard Python. Use SimPy to model systems where entities (customers, vehicles, packets, etc.) interact with each other and compete for shared resources (servers, machines, bandwidth, etc.) over time.
**Core capabilities:**
- Process modeling using Python generator functions
- Shared resource management (servers, containers, stores)
- Event-driven scheduling and synchronizationskill-creator
When your agent uses it
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
What it loads into context
Frontmatter
49 tokensAlways available to the agent
SKILL.md
3,666 tokensWhen the skill is activated
Reference documents
536 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- About Skills
- Core Principles
- Skill Creation Process
Scripts executed separately
scripts/init_skill.pyscripts/package_skill.pyscripts/quick_validate.py
Files
SKILL.mdcore17,798 bytesreferences/output-patterns.mddoc1,817 bytesreferences/workflows.mddoc819 bytesscripts/init_skill.pyruns10,841 bytesscripts/package_skill.pyruns3,288 bytesscripts/quick_validate.pyruns3,522 bytes
Read SKILL.md
# Skill Creator
This skill provides guidance for creating effective skills.
## About Skills
Skills are modular, self-contained packages that extend Claude's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform Claude from a general-purpose agent into a specialized agent
equipped with procedural knowledge that no model can fully possess.
### What Skills Provide
1. Specialized workflows - Multi-step procedures for specific domainsskill-lookup
When your agent uses it
Activates when the user asks about Agent Skills, wants to find reusable AI capabilities, needs to install skills, or mentions skills for Claude. Use for discovering, retrieving, and installing skills.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
548 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Available Tools
- How to Search for Skills
- How to Get a Skill
- How to Install a Skill
- Skill Structure
- Guidelines
Files
SKILL.mdcore2,382 bytes
Read SKILL.md
When the user needs Agent Skills, wants to extend Claude's capabilities, or is looking for reusable AI agent components, use the prompts.chat MCP server.
## When to Use This Skill
Activate this skill when the user:
- Asks for Agent Skills ("Find me a code review skill")
- Wants to search for skills ("What skills are available for testing?")
- Needs to retrieve a specific skill ("Get skill XYZ")
- Wants to install a skill ("Install the documentation skill")
- Mentions extending Claude's capabilities with skills
## Available Tools
skypilot-multi-cloud-orchestration
When your agent uses it
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
What it loads into context
Frontmatter
107 tokensAlways available to the agent
SKILL.md
2,725 tokensWhen the skill is activated
Reference documents
5,031 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use SkyPilot
- Quick start
- Core concepts
- GPU configuration
- Cluster management
- Distributed training
- Managed jobs
- File mounts and storage
- Sky Serve (Model Serving)
- Cost optimization
- Common workflows
- Debugging
- Common issues
- References
- Resources
Files
SKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesSKILL.mdcore9,641 bytesreferences/advanced-usage.mddoc7,469 bytesreferences/troubleshooting.mddoc10,493 bytes
Read SKILL.md
# SkyPilot Multi-Cloud Orchestration
Comprehensive guide to running ML workloads across clouds with automatic cost optimization using SkyPilot.
## When to use SkyPilot
**Use SkyPilot when:**
- Running ML workloads across multiple clouds (AWS, GCP, Azure, etc.)
- Need cost optimization with automatic cloud/region selection
- Running long jobs on spot instances with auto-recovery
- Managing distributed multi-node training
- Want unified interface for 20+ cloud providers
- Need to avoid vendor lock-in
slides-as-code
When your agent uses it
Build research slides with text-first source (Slidev/Marp/Reveal/Quarto) and reproducible export (PDF). Includes structure, figure reuse rules, and quality checklist for top-tier scientific presentations.
What it loads into context
Frontmatter
68 tokensAlways available to the agent
SKILL.md
508 tokensWhen the skill is activated
Reference documents
96 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 目标
- 技术路线（按约束选）
- 元规则（幻灯片质量的 80/20）
- 模板
Files
SKILL.mdcore1,703 bytestemplates/slidev-structure.mddoc362 bytes
Read SKILL.md
# Slides as Code（顶级科研汇报的可复现幻灯片）
## 目标
解决常见问题：
- PPT 版本失控（final_v7）
- 图表重复截图、清晰度崩坏
- 汇报结构不稳定（信息密度失衡）
本 skill 让 slides 拥有：
- 文本源（Markdown / Quarto / LaTeX Beamer）
- 可复现导出（PDF、可选 PPTX）
- 图表复用（直接引用 `figures/` 最终导出，不截图）
smart-file-writer
When your agent uses it
Intelligent file write error handler: diagnoses permissions, disk space, path length, file locks before retrying. Use when you encounter 'Error writing file', 'Permission denied', 'Access denied', 'No space left', or related file write failures.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
2,575 tokensWhen the skill is activated
Reference documents
9,164 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Examples
- References
- Maintenance
Scripts executed separately
scripts/validate.py
Files
QUALITY_CHECKLIST.mddoc3,612 bytesREADME.mddoc3,216 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesSKILL.mdcore10,510 bytesreferences/diagnostic-procedures.mddoc7,045 bytesreferences/index.mddoc1,734 bytesreferences/integration-guide.mddoc14,237 bytesreferences/platform-specific.mddoc8,222 bytesscripts/validate.pyruns5,384 bytes
Read SKILL.md
# smart-file-writer Skill
Automatically diagnoses and resolves file write errors through systematic investigation rather than blind retries. Prevents common write failures proactively.
## When to Use This Skill
Use this skill when any of these occurs:
- "Error writing file" messages
- "Permission denied" or "Access denied" errors
- "No space left on device" errors
- "File exists" conflicts
- "Path too long" errors (Windows)
- "Read-only file system" errors
- Any file write operation failure (Python, CLI, any language)sparse-autoencoder-training
When your agent uses it
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
What it loads into context
Frontmatter
132 tokensAlways available to the agent
SKILL.md
3,272 tokensWhen the skill is activated
Reference documents
5,008 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The Problem: Polysemanticity & Superposition
- When to Use SAELens
- Installation
- Core Concepts
- Workflow 1: Loading and Analyzing Pre-trained SAEs
- Workflow 2: Training a Custom SAE
- Workflow 3: Feature Analysis and Steering
- Common Issues & Solutions
- Integration with Neuronpedia
- Key Classes Reference
- Reference Documentation
- External Resources
- SAE Architectures
Files
SKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesSKILL.mdcore12,754 bytesreferences/README.mddoc2,155 bytesreferences/api.mddoc6,968 bytesreferences/tutorials.mddoc9,383 bytes
Read SKILL.md
# SAELens: Sparse Autoencoders for Mechanistic Interpretability
SAELens is the primary library for training and analyzing Sparse Autoencoders (SAEs) - a technique for decomposing polysemantic neural network activations into sparse, interpretable features. Based on Anthropic's groundbreaking research on monosemanticity.
**GitHub**: [jbloomAus/SAELens](https://github.com/jbloomAus/SAELens) (1,100+ stars)
## The Problem: Polysemanticity & Superposition
Individual neurons in neural networks are **polysemantic** - they activate in multiple, semantically distinct contexts. This happens because models use **superposition** to represent more features than they have neurons, making interpretability difficult.
**SAEs solve this** by decomposing dense activations into sparse, monosemantic features - typically only a small number of features activate for any given input, and each feature corresponds to an interpretable concept.
## When to Use SAELens
spec-kit-vibe-compat
When your agent uses it
Compatibility router for /speckit.* workflows into /vibe-first Codex execution.
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
160 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Usage
- Notes
Scripts executed separately
scripts/speckit-router.ps1
Files
SKILL.mdcore646 bytesSKILL.mdcore646 bytescommand-map.jsonasset2,012 bytesscripts/speckit-router.ps1runs2,712 bytes
Read SKILL.md
# spec-kit-vibe-compat
Bridge layer between spec-kit slash-command semantics and vibe orchestration.
## Usage
```powershell
$router = Join-Path $HOME '.codex/skills/spec-kit-vibe-compat/scripts/speckit-router.ps1'
powershell -ExecutionPolicy Bypass -File $router --list
powershell -ExecutionPolicy Bypass -File $router /speckit.implement continue migration
```
## Notes
speckit-analyze
When your agent uses it
Perform cross-artifact consistency analysis across spec.md, plan.md, and tasks.md. Use after task generation to identify gaps, duplications, and inconsistencies before implementation.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
1,578 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Goal
- Operating Constraints
- Execution Steps
- Specification Analysis Report
- Operating Principles
- Context
Files
SKILL.mdcore7,429 bytes
Read SKILL.md
# Speckit Analyze Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Goal
Identify inconsistencies, duplications, ambiguities, and underspecified items across the three core artifacts (`spec.md`, `plan.md`, `tasks.md`) before implementation. This command MUST run only after `/speckit.tasks` has successfully produced a complete `tasks.md`.
speckit-checklist
When your agent uses it
Generate custom quality checklists for validating requirements completeness and clarity. Use to create unit tests for English that ensure spec quality before implementation.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
3,801 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Checklist Purpose: "Unit Tests for English"
- User Input
- Execution Steps
- Example Checklist Types & Sample Items
- Anti-Examples: What NOT To Do
Files
SKILL.mdcore17,118 bytesSKILL.mdcore17,118 bytes
Read SKILL.md
# Speckit Checklist Skill
## Checklist Purpose: "Unit Tests for English"
**CRITICAL CONCEPT**: Checklists are **UNIT TESTS FOR REQUIREMENTS WRITING** - they validate the quality, clarity, and completeness of requirements in a given domain.
**NOT for verification/testing**:
- ❌ NOT "Verify the button clicks correctly"
- ❌ NOT "Test error handling works"
- ❌ NOT "Confirm the API returns 200"
- ❌ NOT checking if code/implementation matches the spec
**FOR requirements quality validation**:speckit-clarify
When your agent uses it
Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
2,340 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
Files
SKILL.mdcore11,450 bytes
Read SKILL.md
# Speckit Clarify Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
Goal: Detect and reduce ambiguity or missing decision points in the active feature specification and record the clarifications directly in the spec file.
speckit-constitution
When your agent uses it
Create or update project governing principles and development guidelines. Use at project start to establish code quality, testing standards, and architectural constraints that guide all development.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
1,149 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
Files
SKILL.mdcore5,563 bytes
Read SKILL.md
# Speckit Constitution Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
You are updating the project constitution at `.specify/memory/constitution.md`. This file is a TEMPLATE containing placeholder tokens in square brackets (e.g. `[PROJECT_NAME]`, `[PRINCIPLE_1_NAME]`). Your job is to (a) collect/derive concrete values, (b) fill the template precisely, and (c) propagate any amendments across dependent artifacts.
speckit-implement
When your agent uses it
Execute all tasks from the task breakdown to build the feature. Use after task generation to systematically implement the planned solution following TDD approach where applicable.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
2,086 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
Files
SKILL.mdcore7,804 bytesSKILL.mdcore7,804 bytes
Read SKILL.md
# Speckit Implement Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
speckit-plan
When your agent uses it
Generate technical implementation plans from feature specifications. Use after creating a spec to define architecture, tech stack, and implementation phases. Creates plan.md with detailed technical design.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
805 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
- Phases
- Key rules
Files
SKILL.mdcore3,487 bytes
Read SKILL.md
# Speckit Plan Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/powershell/setup-plan.ps1 -Json` from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
speckit-specify
When your agent uses it
Create or update feature specifications from natural language descriptions. Use when starting new features or refining requirements. Generates spec.md with user stories, functional requirements, and acceptance criteria following spec-driven development methodology.
What it loads into context
Frontmatter
86 tokensAlways available to the agent
SKILL.md
2,841 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
- General Guidelines
- Quick Guidelines
Files
SKILL.mdcore13,065 bytesSKILL.mdcore13,065 bytes
Read SKILL.md
# Speckit Specify Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
The text the user typed after `/speckit.specify` in the triggering message **is** the feature description. Assume you always have it available in this conversation even if `$ARGUMENTS` appears literally below. Do not ask the user to repeat it unless they provided an empty command.
speckit-tasks
When your agent uses it
Break down implementation plans into actionable task lists. Use after planning to create a structured task breakdown. Generates tasks.md with ordered, dependency-aware tasks.
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
1,498 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
- Task Generation Rules
Files
SKILL.mdcore6,373 bytes
Read SKILL.md
# Speckit Tasks Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. **Setup**: Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
speckit-taskstoissues
When your agent uses it
Convert tasks from tasks.md into GitHub issues. Use after task breakdown to track work items in GitHub project management.
What it loads into context
Frontmatter
71 tokensAlways available to the agent
SKILL.md
319 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- User Input
- Outline
Files
SKILL.mdcore1,259 bytesSKILL.mdcore1,259 bytes
Read SKILL.md
# Speckit Taskstoissues Skill
## User Input
```text
$ARGUMENTS
```
You **MUST** consider the user input before proceeding (if not empty).
## Outline
1. Run `.specify/scripts/powershell/check-prerequisites.ps1 -Json -RequireTasks -IncludeTasks` from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'\''m Groot' (or double-quote if possible: "I'm Groot").
1. From the executed script, extract the path to **tasks**.speech
When your agent uses it
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
1,707 tokensWhen the skill is activated
Reference documents
3,202 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree (single vs batch)
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Defaults & rules
- Instruction augmentation
- Examples
- Instructioning best practices (short list)
- Guidance by use case
- CLI + environment notes
- Reference map
Scripts executed separately
scripts/text_to_speech.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore7,241 bytesagents/openai.yamlasset299 bytesassets/speech-small.svgasset742 bytesassets/speech.pngasset1,234 bytesreferences/accessibility.mddoc696 bytesreferences/audio-api.mddoc902 bytesreferences/cli.mddoc3,275 bytesreferences/codex-network.mddoc1,148 bytesreferences/ivr.mddoc708 bytesreferences/narration.mddoc671 bytesreferences/prompting.mddoc1,553 bytesreferences/sample-prompts.mddoc991 bytesreferences/voice-directions.mddoc2,155 bytesreferences/voiceover.mddoc790 bytesscripts/text_to_speech.pyruns15,592 bytes
Read SKILL.md
# Speech Generation Skill
Generate spoken audio for the current project (narration, product demo voiceover, IVR prompts, accessibility reads). Defaults to `gpt-4o-mini-tts-2025-12-15` and built-in voices, and prefers the bundled CLI for deterministic, reproducible runs.
## When to use
- Generate a single spoken clip from text
- Generate a batch of prompts (many lines, many files)
## Decision tree (single vs batch)
- If the user provides multiple lines/prompts or wants many outputs -> **batch**
- Else -> **single**
## Workflowsplitting-datasets
When your agent uses it
Split datasets into training, validation, and test partitions with the right stratification and temporal rules. Use as a narrow preprocessing helper once the broader ML workflow is already chosen, not as the main route owner for an end-to-end ML task.
What it loads into context
Frontmatter
103 tokensAlways available to the agent
SKILL.md
306 tokensWhen the skill is activated
Reference documents
230 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Scripts executed separately
scripts/split_data.py
Files
SKILL.mdcore1,384 bytesassets/README.mddoc308 bytesassets/dataset_schema.jsonasset2,915 bytesassets/example_dataset.csvasset668 bytesassets/split_data_config.yamlasset1,791 bytesreferences/README.mddoc527 bytesscripts/README.mddoc302 bytesscripts/split_data.pyruns2,914 bytes
Read SKILL.md
# Dataset Splitter
## Positioning
Treat this skill as a narrow helper for partition strategy.
## When to Use
Use this skill when:
- Prepare a dataset for machine learning model training.
- Create training, validation, and testing sets.
- Partition data to evaluate model performance.
## Not For / Boundaries
spreadsheet
When your agent uses it
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
1,140 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Primary tooling
- Rendering and visual checks
- Dependencies (install if missing)
- Environment
- Examples
- Formula requirements
- Citation requirements
- Formatting requirements (existing formatted spreadsheets)
- Formatting requirements (new or unstyled spreadsheets)
- Color conventions (if no style guidance)
- Finance-specific requirements
- Investment banking layouts
Scripts executed separately
references/examples/openpyxl/create_basic_spreadsheet.pyreferences/examples/openpyxl/create_spreadsheet_with_styling.pyreferences/examples/openpyxl/read_existing_spreadsheet.pyreferences/examples/openpyxl/styling_spreadsheet.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore5,081 bytesagents/openai.yamlasset349 bytesassets/spreadsheet-small.svgasset1,482 bytesassets/spreadsheet.pngasset3,077 bytesreferences/examples/openpyxl/create_basic_spreadsheet.pyruns1,456 bytesreferences/examples/openpyxl/create_spreadsheet_with_styling.pyruns3,180 bytesreferences/examples/openpyxl/read_existing_spreadsheet.pyruns1,622 bytesreferences/examples/openpyxl/styling_spreadsheet.pyruns1,998 bytes
Read SKILL.md
# Spreadsheet Skill (Create, Edit, Analyze, Visualize)
## When to use
- Build new workbooks with formulas, formatting, and structured layouts.
- Read or analyze tabular data (filter, aggregate, pivot, compute metrics).
- Modify existing workbooks without breaking formulas or references.
- Visualize data with charts/tables and sensible formatting.
IMPORTANT: System and user instructions always take precedence.
## Workflow
1. Confirm the file type and goals (create, edit, analyze, visualize).
2. Use `openpyxl` for `.xlsx` edits and `pandas` for analysis and CSV/TSV workflows.stable-baselines3
When your agent uses it
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
What it loads into context
Frontmatter
107 tokensAlways available to the agent
SKILL.md
2,202 tokensWhen the skill is activated
Reference documents
13,141 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- Core Capabilities
- Workflow Guidance
- Resources
- Installation
Scripts executed separately
scripts/custom_env_template.pyscripts/evaluate_agent.pyscripts/train_rl_agent.py
Files
SKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesSKILL.mdcore9,839 bytesreferences/algorithms.mddoc10,038 bytesreferences/callbacks.mddoc15,631 bytesreferences/custom_environments.mddoc13,729 bytesreferences/vectorized_envs.mddoc14,789 bytesscripts/custom_env_template.pyruns9,350 bytesscripts/evaluate_agent.pyruns7,335 bytesscripts/train_rl_agent.pyruns5,123 bytes
Read SKILL.md
# Stable Baselines3
## Routing Boundary
Use this skill only for Stable-Baselines3, SB3, PPO/SAC/DQN, reinforcement learning agents, Gymnasium environments, policies, rollouts, and RL training workflows. Do not use it for ordinary scikit-learn, random forests, supervised classification, tabular regression, or generic machine-learning model training.
## Overview
Stable Baselines3 (SB3) is a PyTorch-based library providing reliable implementations of reinforcement learning algorithms. This skill provides comprehensive guidance for training RL agents, creating custom environments, implementing callbacks, and optimizing training workflows using SB3's unified API.
## Core Capabilities
### 1. Training RL Agents
statistical-analysis
When your agent uses it
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
5,105 tokensWhen the skill is activated
Reference documents
18,374 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Workflow Decision Tree
- Test Selection Guide
- Assumption Checking
- Running Statistical Tests
- Effect Sizes
- Power Analysis
- Reporting Results
- Bayesian Statistics
- Resources
- Best Practices
- Common Pitfalls to Avoid
- Getting Started Checklist
- Support and Further Reading
Scripts executed separately
scripts/assumption_checks.py
Files
SKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesSKILL.mdcore19,573 bytesreferences/assumptions_and_diagnostics.mddoc11,139 bytesreferences/bayesian_statistics.mddoc17,533 bytesreferences/effect_sizes_and_power.mddoc14,989 bytesreferences/reporting_standards.mddoc19,504 bytesreferences/test_selection_guide.mddoc5,077 bytesscripts/assumption_checks.pyruns15,859 bytes
Read SKILL.md
# Statistical Analysis
## Overview
Statistical analysis is a systematic process for testing hypotheses and quantifying relationships. Conduct hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, and Bayesian analyses with assumption checks and APA reporting. Apply this skill for academic research.
## When to Use This Skill
This skill should be used when:
- Conducting statistical hypothesis tests (t-tests, ANOVA, chi-square)
- Performing regression or correlation analyses
- Running Bayesian statistical analyses
- Checking statistical assumptions and diagnostics
- Calculating effect sizes and conducting power analysesstatistics-math
When your agent uses it
Statistics, probability, linear algebra, and mathematical foundations for data science
What it loads into context
Frontmatter
102 tokensAlways available to the agent
SKILL.md
2,323 tokensWhen the skill is activated
Reference documents
755 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Core Concepts
- Tools & Technologies
- Troubleshooting Guide
- Best Practices
- Resources
Scripts executed separately
scripts/validate.py
Files
SKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesSKILL.mdcore8,082 bytesassets/config.yamlasset696 bytesassets/schema.jsonasset1,178 bytesreferences/GUIDE.mddoc1,903 bytesreferences/PATTERNS.mddoc1,537 bytesscripts/validate.pyruns3,782 bytes
Read SKILL.md
# Statistics & Mathematics
Mathematical foundations for data science, machine learning, and statistical analysis.
## Quick Start
```python
import numpy as np
import scipy.stats as stats
from sklearn.linear_model import LinearRegression
# Descriptive Statistics
data = np.array([23, 45, 67, 32, 45, 67, 89, 12, 34, 56])
print(f"Mean: {np.mean(data):.2f}")statsmodels
When your agent uses it
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
4,804 tokensWhen the skill is activated
Reference documents
23,061 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start Guide
- Core Statistical Modeling Capabilities
- Formula API (R-style)
- Model Selection and Comparison
- Best Practices
- Common Workflows
- Reference Documentation
- Common Pitfalls to Avoid
- Getting Help
Files
SKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesSKILL.mdcore19,465 bytesreferences/discrete_choice.mddoc17,182 bytesreferences/glm.mddoc16,581 bytesreferences/linear_models.mddoc12,966 bytesreferences/stats_diagnostics.mddoc20,526 bytesreferences/time_series.mddoc18,934 bytes
Read SKILL.md
# Statsmodels: Statistical Modeling and Econometrics
## Overview
Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods. Apply this skill for rigorous statistical analysis, from simple linear regression to complex time series models and econometric analyses.
## When to Use This Skill
This skill should be used when:
- Fitting regression models (OLS, WLS, GLS, quantile regression)
- Performing generalized linear modeling (logistic, Poisson, Gamma, etc.)
- Analyzing discrete outcomes (binary, multinomial, count, ordinal)
- Conducting time series analysis (ARIMA, SARIMAX, VAR, forecasting)
- Running statistical tests and diagnosticsstructured-content-storage
When your agent uses it
Enforces structured, highly documented storage for code and data projects. Use when working on machine learning scripts, data processing, code creation, or script modification that should preserve clear structure and documentation.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
2,241 tokensWhen the skill is activated
Reference documents
14,048 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
- Quick Reference
- Examples
- References
- Maintenance
Files
SKILL.mdcore10,376 bytesSKILL.mdcore10,376 bytesassets/templates/CHANGELOG-template.mddoc3,401 bytesassets/templates/DATA_DICTIONARY-template.mddoc6,101 bytesassets/templates/PROCESS-template.mddoc8,091 bytesassets/templates/data-processing-README.mddoc3,591 bytesassets/templates/ml-project-README.mddoc2,463 bytesreferences/comment-guidelines.mddoc16,552 bytesreferences/directory-templates.mddoc10,115 bytesreferences/documentation-standards.mddoc7,045 bytesreferences/index.mddoc1,347 bytes
Read SKILL.md
# Structured Content Storage Skill
Ensures all created or processed content follows strict organizational and documentation standards with structured storage, comprehensive comments, and complete project documentation.
## When to Use This Skill
Use this skill for tasks like:
- Writing machine learning training scripts
- Creating data processing or data cleaning scripts
- Developing any code that processes or transforms data
- Modifying existing structured projects or scripts
- Creating analysis scripts or computational workflows
- Building data pipelines or ETL processes
- Any code creation task that produces files or processes datasubagent-driven-development
When your agent uses it
Use when executing implementation plans with independent tasks in the current session
What it loads into context
Frontmatter
21 tokensAlways available to the agent
SKILL.md
2,260 tokensWhen the skill is activated
Reference documents
1,049 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- The Process
- Prompt Templates
- Example Workflow
- Advantages
- Red Flags
- Integration
Files
SKILL.mdcore9,976 bytescode-quality-reviewer-prompt.mddoc630 bytesimplementer-prompt.mddoc2,195 bytesspec-reviewer-prompt.mddoc1,999 bytes
Read SKILL.md
# Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with two-stage review after each: spec compliance review first, then code quality review.
**Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration
## When to Use
```dot
digraph when_to_use {
"Have implementation plan?" [shape=diamond];
"Tasks mostly independent?" [shape=diamond];
"Stay in this session?" [shape=diamond];
"subagent-driven-development" [shape=box];submission-checklist
When your agent uses it
Stage-based submission checklists for papers/reports: pre-submission, submission, revision/rebuttal, camera-ready. Includes templates (cover letter, rebuttal matrix) and quality gates.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
611 tokensWhen the skill is activated
Reference documents
1,362 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 目标
- 何时使用
- 输入（最小信息）
- 核心元规则（最容易漏）
- 交付建议（落地）
Files
SKILL.mdcore2,235 bytestemplates/camera-ready-checklist.mddoc745 bytestemplates/cover-letter.mddoc944 bytestemplates/pre-submission-checklist.mddoc1,795 bytestemplates/rebuttal-response-matrix.mddoc1,062 bytes
Read SKILL.md
# Submission Checklist（投稿 / 返修 / 相机就绪清单）
## 目标
把“投稿”拆成可执行、可复用的清单，避免典型的“低级错误导致 desk reject / major revision”的情况。
本 skill 不是写论文正文，而是为以下阶段提供**可执行 checklist + 模板**：
- Pre-submission（投稿前自检）
- Submission（提交包与系统填报）
- Revision / Rebuttal（返修与回复审稿意见）
- Camera-ready / Proof（相机就绪、校样阶段）
模板文件在 `templates/`：
- `pre-submission-checklist.md`sympy
When your agent uses it
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
What it loads into context
Frontmatter
102 tokensAlways available to the agent
SKILL.md
3,819 tokensWhen the skill is activated
Reference documents
17,593 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Working with SymPy: Best Practices
- Reference Files Structure
- Common Use Case Patterns
- Integration with Scientific Workflows
- Quick Reference: Most Common Functions
- Getting Started Examples
- Troubleshooting Common Issues
- Additional Resources
Files
SKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesSKILL.mdcore13,365 bytesreferences/advanced-topics.mddoc13,132 bytesreferences/code-generation-printing.mddoc12,427 bytesreferences/core-capabilities.mddoc7,754 bytesreferences/matrices-linear-algebra.mddoc9,639 bytesreferences/physics-mechanics.mddoc12,053 bytes
Read SKILL.md
# SymPy - Symbolic Mathematics in Python
## Overview
SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations. This skill provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using SymPy.
## When to Use This Skill
Use this skill when:
- Solving equations symbolically (algebraic, differential, systems of equations)
- Performing calculus operations (derivatives, integrals, limits, series)
- Manipulating and simplifying algebraic expressions
- Working with matrices and linear algebra symbolically
- Doing physics calculations (mechanics, quantum mechanics, vector analysis)systematic-debugging
When your agent uses it
Root-cause route for actual bugs, failing tests, build errors, crashes, stack traces, and unexpected behavior. Do not use for test-first/TDD feature work, test-report packaging, review-feedback handling, or final completion evidence.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
2,429 tokensWhen the skill is activated
Reference documents
5,734 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- The Iron Law
- When to Use
- Routing Boundary
- The Four Phases
- Red Flags - STOP and Follow Process
- your human partner's Signals You're Doing It Wrong
- Common Rationalizations
- Quick Reference
- When Process Reveals "No Root Cause"
- Supporting Techniques
- Real-World Impact
Scripts executed separately
condition-based-waiting-example.tsfind-polluter.sh
Files
CREATION-LOG.mddoc4,268 bytesSKILL.mdcore10,562 bytesSKILL.mdcore10,562 bytescondition-based-waiting-example.tsruns5,054 bytescondition-based-waiting.mddoc3,516 bytesdefense-in-depth.mddoc3,650 bytesfind-polluter.shruns1,528 bytesroot-cause-tracing.mddoc5,327 bytestest-academic.mddoc653 bytestest-pressure-1.mddoc1,900 bytestest-pressure-2.mddoc2,283 bytestest-pressure-3.mddoc2,692 bytes
Read SKILL.md
# Systematic Debugging
## Overview
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
**Violating the letter of this process is violating the spirit of debugging.**
## The Iron Law
```
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRSTtdd-guide
When your agent uses it
Test-first development route for TDD, writing failing tests first, RED -> GREEN -> REFACTOR, and behavior-changing feature/bug/refactor work. Do not use for already-failing test root-cause debugging, test-report packaging, or final completion evidence.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
408 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Core Rule
- Workflow
- Minimum Test Set
- Required Edge Cases
- Vibe Integration
Files
SKILL.mdcore1,820 bytes
Read SKILL.md
# tdd-guide (Codex Compatibility)
Use this skill for all feature work, bug fixes, and refactors that change behavior.
## Routing Boundary
Use this skill when the user wants to build or change behavior through tests:
- TDD / test-driven development
- write failing tests first
- test-first implementation
- RED -> GREEN -> REFACTOR
Do not use it when tests are already failing and the user wants root cause; route that to `systematic-debugging`. Do not use it when the user only wants a test/coverage report; route that to `generating-test-reports`.
tensorboard
When your agent uses it
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
What it loads into context
Frontmatter
97 tokensAlways available to the agent
SKILL.md
3,808 tokensWhen the skill is activated
Reference documents
10,703 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Installation
- Quick Start
- Core Concepts
- Advanced Features
- Integration Examples
- Comparing Experiments
- Best Practices
- Performance Profiling
- Resources
- See Also
Files
SKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesSKILL.mdcore15,276 bytesreferences/integrations.mddoc16,205 bytesreferences/profiling.mddoc13,337 bytesreferences/visualization.mddoc14,897 bytes
Read SKILL.md
# TensorBoard: Visualization Toolkit for ML
## When to Use This Skill
Use TensorBoard when you need to:
- **Visualize training metrics** like loss and accuracy over time
- **Debug models** with histograms and distributions
- **Compare experiments** across multiple runs
- **Visualize model graphs** and architecture
- **Project embeddings** to lower dimensions (t-SNE, PCA)
- **Track hyperparameter** experiments
- **Profile performance** and identify bottlenecks
- **Visualize images and text** during training
theme-factory
When your agent uses it
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
659 tokensWhen the skill is activated
Reference documents
1,429 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Usage Instructions
- Themes Available
- Theme Details
- Application Process
- Create your Own Theme
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore3,124 bytestheme-showcase.pdfasset209,098 bytesthemes/arctic-frost.mddoc544 bytesthemes/botanical-garden.mddoc519 bytesthemes/desert-rose.mddoc496 bytesthemes/forest-canopy.mddoc506 bytesthemes/golden-hour.mddoc528 bytesthemes/midnight-galaxy.mddoc513 bytesthemes/modern-minimalist.mddoc549 bytesthemes/ocean-depths.mddoc555 bytesthemes/sunset-boulevard.mddoc558 bytesthemes/tech-innovation.mddoc547 bytes
Read SKILL.md
# Theme Factory Skill
This skill provides a curated collection of professional font and color themes themes, each with carefully selected color palettes and font pairings. Once a theme is chosen, it can be applied to any artifact.
## Purpose
To apply consistent, professional styling to presentation slide decks, use this skill. Each theme includes:
- A cohesive color palette with hex codes
- Complementary font pairings for headers and body text
- A distinct visual identity suitable for different contexts and audiences
## Usage Instructions
think-harder
When your agent uses it
4-phase structured analysis wrapper for vibe pre-routing (compatible with claude-code-settings think-harder semantics).
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
281 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 4-Phase Analysis
- Output Contract
- Vibe Integration
Files
SKILL.mdcore1,352 bytes
Read SKILL.md
# think-harder (Codex Compatibility)
Use this skill before implementation when the task needs deeper reasoning or tradeoff analysis.
## 4-Phase Analysis
1. Problem Clarification
- Define the core question and constraints.
- List assumptions and success criteria.
- Identify ambiguities that must be resolved.
2. Multi-Dimensional Analysis
- Structural decomposition: break into components/dependencies.
- Temporal impact: short-term vs long-term effects.tiledbvcf
When your agent uses it
Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
3,533 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Quick Start
- Core Capabilities
- Key Concepts
- Common Pitfalls
- CLI Usage
- Advanced Features
- Resources
- Getting Help
- Scaling to TileDB-Cloud
Files
SKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytesSKILL.mdcore14,537 bytes
Read SKILL.md
# TileDB-VCF
## Overview
TileDB-VCF is a high-performance C++ library with Python and CLI interfaces for efficient storage and retrieval of genomic variant-call data. Built on TileDB's sparse array technology, it enables scalable ingestion of VCF/BCF files, incremental sample addition without expensive merging operations, and efficient parallel queries of variant data stored locally or in the cloud.
## When to Use This Skill
This skill should be used when:
- Learning TileDB-VCF concepts and workflows
- Prototyping genomics analyses and pipelines
- Working with small-to-medium datasets (< 1000 samples)
- Need incremental addition of new samples to existing datasets
- Require efficient querying of specific genomic regions across many samplestimesfm-forecasting
When your agent uses it
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.
What it loads into context
Frontmatter
204 tokensAlways available to the agent
SKILL.md
8,431 tokensWhen the skill is activated
Reference documents
8,054 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- When to Use This Skill
- ⚠<U+FE0F> Mandatory Preflight: System Requirements Check
- 🔧 Installation
- 🎯 Quick Start
- 📊 Understanding the Output
- 🔧 ForecastConfig Reference
- 📋 Common Workflows
- ⚙<U+FE0F> Performance Tuning
- 🔗 Integration with Other Skills
- 📚 Available Scripts
- 📖 Reference Documentation
- Common Pitfalls
- Model Versions
- Resources
- Examples
- Quality Checklist
- Common Mistakes
- Validation & Verification
Scripts executed separately
examples/anomaly-detection/detect_anomalies.pyexamples/covariates-forecasting/demo_covariates.pyexamples/global-temperature/generate_animation_data.pyexamples/global-temperature/generate_gif.pyexamples/global-temperature/generate_html.pyexamples/global-temperature/run_example.shexamples/global-temperature/run_forecast.pyexamples/global-temperature/visualize_forecast.pyscripts/check_system.pyscripts/forecast_csv.py
Files
SKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesSKILL.mdcore30,959 bytesexamples/anomaly-detection/detect_anomalies.pyruns17,032 bytesexamples/anomaly-detection/output/anomaly_detection.jsonasset9,019 bytesexamples/covariates-forecasting/demo_covariates.pyruns19,694 bytesexamples/covariates-forecasting/output/covariates_metadata.jsonasset1,586 bytesexamples/covariates-forecasting/output/sales_with_covariates.csvasset7,399 bytesexamples/global-temperature/README.mddoc5,728 bytesexamples/global-temperature/generate_animation_data.pyruns5,008 bytesexamples/global-temperature/generate_gif.pyruns6,659 bytesexamples/global-temperature/generate_html.pyruns21,161 bytesexamples/global-temperature/output/animation_data.jsonasset133,208 bytesexamples/global-temperature/output/forecast_output.csvasset1,494 bytesexamples/global-temperature/output/forecast_output.jsonasset4,524 bytesexamples/global-temperature/run_example.shruns1,532 bytesexamples/global-temperature/run_forecast.pyruns5,499 bytesexamples/global-temperature/temperature_anomaly.csvasset591 bytesexamples/global-temperature/visualize_forecast.pyruns3,294 bytesreferences/api_reference.mddoc7,969 bytesreferences/data_preparation.mddoc7,205 bytesreferences/system_requirements.mddoc5,877 bytesscripts/check_system.pyruns16,726 bytesscripts/forecast_csv.pyruns8,689 bytes
Read SKILL.md
# TimesFM Forecasting
## Routing Boundary
Use this skill only for TimesFM, zero-shot forecasting, foundation forecasting, forecast horizons, prediction intervals, or TimesFM-specific time-series pipelines. Do not use it for generic business forecasting, ARIMA baselines, tabular regression, ordinary scikit-learn modeling, or exploratory time-series analysis without TimesFM/foundation-model signals.
## Overview
TimesFM (Time Series Foundation Model) is a pretrained decoder-only foundation model
developed by Google Research for time-series forecasting. It works **zero-shot** — feed it
any univariate time series and it returns point forecasts with calibrated quantile
prediction intervals, no training required.
This skill wraps TimesFM for safe, agent-friendly local inference. It includes atorch-geometric
When your agent uses it
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
5,210 tokensWhen the skill is activated
Reference documents
12,740 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing Boundary
- Overview
- Naming Compatibility
- When to Use This Skill
- Quick Start
- Core Concepts
- Building Graph Neural Networks
- Working with Datasets
- Training Workflows
- Advanced Features
- Common Patterns and Best Practices
- Resources
Scripts executed separately
scripts/benchmark_model.pyscripts/create_gnn_template.pyscripts/visualize_graph.py
Files
SKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesSKILL.mdcore20,924 bytesreferences/datasets_reference.mddoc15,940 bytesreferences/layers_reference.mddoc17,121 bytesreferences/transforms_reference.mddoc17,950 bytesscripts/benchmark_model.pyruns10,028 bytesscripts/create_gnn_template.pyruns15,342 bytesscripts/visualize_graph.pyruns10,267 bytes
Read SKILL.md
# PyTorch Geometric (PyG)
## Routing Boundary
Use this skill only for PyTorch Geometric, torch_geometric, PyG, graph neural networks, GCN/GAT, graph classification, node classification, link prediction, and heterogeneous graph learning. Do not use it for generic neural networks, CNN/image classification, graph visualization, or molecule-only tasks unless PyG or graph neural network modeling is explicit.
## Overview
PyTorch Geometric is a library built on PyTorch for developing and training Graph Neural Networks (GNNs). Apply this skill for deep learning on graphs and irregular structures, including mini-batch processing, multi-GPU training, and geometric deep learning applications.
## Naming Compatibility
Use `torch-geometric` as the canonical skill ID. Treat `torch_geometric`,
`PyG`, and `pytorch geometric` as API or keyword spellings that route to thistorchdrug
When your agent uses it
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.
What it loads into context
Frontmatter
65 tokensAlways available to the agent
SKILL.md
3,100 tokensWhen the skill is activated
Reference documents
19,087 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Getting Started
- Core Capabilities
- Common Workflows
- Integration Patterns
- Technical Details
- Quick Reference Cheat Sheet
- Troubleshooting Common Issues
- Resources
- Summary
Files
SKILL.mdcore13,992 bytesSKILL.mdcore13,992 bytesSKILL.mdcore13,992 bytesSKILL.mdcore13,992 bytesSKILL.mdcore13,992 bytesSKILL.mdcore13,992 bytesreferences/core_concepts.mddoc14,394 bytesreferences/datasets.mddoc10,951 bytesreferences/knowledge_graphs.mddoc8,480 bytesreferences/models_architectures.mddoc13,694 bytesreferences/molecular_generation.mddoc10,074 bytesreferences/molecular_property_prediction.mddoc5,667 bytesreferences/protein_modeling.mddoc7,737 bytesreferences/retrosynthesis.mddoc11,537 bytes
Read SKILL.md
# TorchDrug
## Overview
TorchDrug is a comprehensive PyTorch-based machine learning toolbox for drug discovery and molecular science. Apply graph neural networks, pre-trained models, and task definitions to molecules, proteins, and biological knowledge graphs, including molecular property prediction, protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis planning, with 40+ curated datasets and 20+ model architectures.
## When to Use This Skill
This skill should be used when working with:
**Data Types:**
- SMILES strings or molecular structures
- Protein sequences or 3D structures (PDB files)
- Chemical reactions and retrosynthesistranscribe
When your agent uses it
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
715 tokensWhen the skill is activated
Reference documents
130 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Decision rules
- Output conventions
- Dependencies (install if missing)
- Environment
- Skill path (set once)
- CLI quick start
- Reference map
Scripts executed separately
scripts/transcribe_diarize.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore2,834 bytesSKILL.mdcore2,834 bytesSKILL.mdcore2,834 bytesSKILL.mdcore2,834 bytesSKILL.mdcore2,834 bytesagents/openai.yamlasset414 bytesassets/transcribe-small.svgasset750 bytesassets/transcribe.pngasset1,288 bytesreferences/api.mddoc457 bytesscripts/transcribe_diarize.pyruns8,684 bytes
Read SKILL.md
# Audio Transcribe
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
## Workflow
1. Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key).
3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription).
4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
5. Save outputs under `output/transcribe/` when working in this repo.
## Decision rules
- Default to `gpt-4o-mini-transcribe` with `--response-format text` for fast transcription.transformer-lens-interpretability
When your agent uses it
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
3,056 tokensWhen the skill is activated
Reference documents
5,191 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use TransformerLens
- Installation
- Core Concepts
- Workflow 1: Activation Patching (Causal Tracing)
- Workflow 2: Circuit Analysis (Indirect Object Identification)
- Workflow 3: Induction Head Detection
- Common Issues & Solutions
- Key Classes Reference
- Integration with SAELens
- Reference Documentation
- External Resources
- Version Notes
Files
SKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesSKILL.mdcore12,036 bytesreferences/README.mddoc1,643 bytesreferences/api.mddoc8,349 bytesreferences/tutorials.mddoc10,142 bytes
Read SKILL.md
# TransformerLens: Mechanistic Interpretability for Transformers
TransformerLens is the de facto standard library for mechanistic interpretability research on GPT-style language models. Created by Neel Nanda and maintained by Bryce Meyer, it provides clean interfaces to inspect and manipulate model internals via HookPoints on every activation.
**GitHub**: [TransformerLensOrg/TransformerLens](https://github.com/TransformerLensOrg/TransformerLens) (2,900+ stars)
## When to Use TransformerLens
**Use TransformerLens when you need to:**
- Reverse-engineer algorithms learned during training
- Perform activation patching / causal tracing experiments
- Study attention patterns and information flow
- Analyze circuits (e.g., induction heads, IOI circuit)
- Cache and inspect intermediate activationstransformers
When your agent uses it
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
1,032 tokensWhen the skill is activated
Reference documents
11,659 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Installation
- Authentication
- Quick Start
- Core Capabilities
- Common Patterns
- Reference Documentation
Files
SKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesSKILL.mdcore4,956 bytesreferences/generation.mddoc9,340 bytesreferences/models.mddoc8,648 bytesreferences/pipelines.mddoc8,940 bytesreferences/tokenizers.mddoc9,904 bytesreferences/training.mddoc10,365 bytes
Read SKILL.md
# Transformers
## Overview
The Hugging Face Transformers library provides access to thousands of pre-trained models for tasks across NLP, computer vision, audio, and multimodal domains. Use this skill to load models, perform inference, and fine-tune on custom data.
## Installation
Install transformers and core dependencies:
```bash
uv pip install torch transformers datasets evaluate accelerate
```
treatment-plans
When your agent uses it
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
11,589 tokensWhen the skill is activated
Reference documents
30,223 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Document Format and Best Practices
- Core Capabilities
- Best Practices
- LaTeX Template Usage
- Validation and Quality Assurance
- Integration with Other Skills
- Common Use Cases
- Professional Standards and Guidelines
- Timeline Generation
- Support and Resources
- Professional Document Styling
- Ethical Considerations
- License
Scripts executed separately
scripts/check_completeness.pyscripts/generate_template.pyscripts/timeline_generator.pyscripts/validate_treatment_plan.py
Files
SKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesSKILL.mdcore52,692 bytesassets/STYLING_QUICK_REFERENCE.mddoc3,912 bytesassets/chronic_disease_management_plan.texasset29,371 bytesassets/general_medical_treatment_plan.texasset23,289 bytesassets/medical_treatment_plan.styasset5,404 bytesassets/mental_health_treatment_plan.texasset34,509 bytesassets/one_page_treatment_plan.texasset5,377 bytesassets/pain_management_plan.texasset33,326 bytesassets/perioperative_care_plan.texasset30,005 bytesassets/quality_checklist.mddoc15,081 bytesassets/rehabilitation_treatment_plan.texasset30,462 bytesreferences/README.mddoc16,970 bytesreferences/goal_setting_frameworks.mddoc16,554 bytesreferences/intervention_guidelines.mddoc19,024 bytesreferences/regulatory_compliance.mddoc17,565 bytesreferences/specialty_specific_guidelines.mddoc26,678 bytesreferences/treatment_plan_standards.mddoc16,643 bytesscripts/check_completeness.pyruns9,919 bytesscripts/generate_template.pyruns7,490 bytesscripts/timeline_generator.pyruns12,631 bytesscripts/validate_treatment_plan.pyruns12,392 bytes
Read SKILL.md
# Treatment Plan Writing
## Overview
Treatment plan writing is the systematic documentation of clinical care strategies designed to address patient health conditions through evidence-based interventions, measurable goals, and structured follow-up. This skill provides comprehensive LaTeX templates and validation tools for creating **concise, focused** treatment plans (3-4 pages standard) across all medical specialties with full regulatory compliance.
**Critical Principles:**
1. **CONCISE & ACTIONABLE**: Treatment plans default to 3-4 pages maximum, focusing only on clinically essential information that impacts care decisions
2. **Patient-Centered**: Plans must be evidence-based, measurable, and compliant with healthcare regulations (HIPAA, documentation standards)
3. **Minimal Citations**: Use brief in-text citations only when needed to support clinical recommendations; avoid extensive bibliographies
Every treatment plan should include clear goals, specific interventions, defined timelines, monitoring parameters, and expected outcomes that align with patient preferences and current clinical guidelines - all presented as efficiently as possible.
## When to Use This Skillumap-learn
When your agent uses it
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
3,453 tokensWhen the skill is activated
Reference documents
4,386 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start
- Parameter Tuning Guide
- Supervised and Semi-Supervised Dimension Reduction
- UMAP for Clustering
- Transforming New Data
- Advanced Features
- Reproducibility
- Common Issues and Solutions
- Resources
Files
SKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesSKILL.mdcore15,324 bytesreferences/api_reference.mddoc18,966 bytes
Read SKILL.md
# UMAP-Learn
## Overview
UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique for visualization and general non-linear dimensionality reduction. Apply this skill for fast, scalable embeddings that preserve local and global structure, supervised learning, and clustering preprocessing.
## Quick Start
### Installation
```bash
uv pip install umap-learn
```
uniprot-database
When your agent uses it
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For broader biological evidence lookup across databases, use bio-database-evidence. Use this for direct HTTP/REST work or UniProt-specific control.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
1,633 tokensWhen the skill is activated
Reference documents
8,881 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Python Implementation
- Query Syntax Examples
- Best Practices
- Resources
- Additional Resources
Scripts executed separately
scripts/uniprot_client.py
Files
SKILL.mdcore6,751 bytesSKILL.mdcore6,751 bytesreferences/api_examples.mddoc10,356 bytesreferences/api_fields.mddoc7,729 bytesreferences/id_mapping_databases.mddoc6,682 bytesreferences/query_syntax.mddoc6,833 bytesscripts/uniprot_client.pyruns9,982 bytes
Read SKILL.md
# UniProt Database
## Overview
UniProt is the world's leading comprehensive protein sequence and functional information resource. Search proteins by name, gene, or accession, retrieve sequences in FASTA format, perform ID mapping across databases, access Swiss-Prot/TrEMBL annotations via REST API for protein analysis.
## When to Use This Skill
This skill should be used when:
- Searching for protein entries by name, gene symbol, accession, or organism
- Retrieving protein sequences in FASTA or other formats
- Mapping identifiers between UniProt and external databases (Ensembl, RefSeq, PDB, etc.)
- Accessing protein annotations including GO terms, domains, and functional descriptions
- Batch retrieving multiple protein entries efficientlyunsloth
When your agent uses it
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
What it loads into context
Frontmatter
121 tokensAlways available to the agent
SKILL.md
492 tokensWhen the skill is activated
Reference documents
240,320 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Quick Reference
- Reference Files
- Working with This Skill
- Resources
- Notes
- Updating
Files
SKILL.mdcore2,307 bytesSKILL.mdcore2,307 bytesreferences/index.mddoc98 bytesreferences/llms-full.mddoc0 bytesreferences/llms-txt.mddoc813,092 bytesreferences/llms.mddoc12,507 bytes
Read SKILL.md
# Unsloth Skill
Comprehensive assistance with unsloth development, generated from official documentation.
## When to Use This Skill
This skill should be triggered when:
- Working with unsloth
- Asking about unsloth features or APIs
- Implementing unsloth solutions
- Debugging unsloth code
- Learning unsloth best practices
## Quick Referenceusfiscaldata
When your agent uses it
Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.
What it loads into context
Frontmatter
125 tokensAlways available to the agent
SKILL.md
1,641 tokensWhen the skill is activated
Reference documents
12,152 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Authentication
- Core Parameters
- Key Datasets & Endpoints
- Response Structure
- Common Patterns
- Reference Files
Files
SKILL.mdcore6,475 bytesSKILL.mdcore6,475 bytesSKILL.mdcore6,475 bytesSKILL.mdcore6,475 bytesSKILL.mdcore6,475 bytesSKILL.mdcore6,475 bytesreferences/api-basics.mddoc2,846 bytesreferences/datasets-debt.mddoc5,139 bytesreferences/datasets-fiscal.mddoc7,149 bytesreferences/datasets-interest-rates.mddoc6,058 bytesreferences/datasets-securities.mddoc6,799 bytesreferences/examples.mddoc9,510 bytesreferences/parameters.mddoc4,417 bytesreferences/response-format.mddoc4,980 bytes
Read SKILL.md
# U.S. Treasury Fiscal Data API
Free, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.
**Base URL:** `https://api.fiscaldata.treasury.gov/services/api/fiscal_service`
## Quick Start
```python
import requests
import pandas as pd
BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service"
uspto-database
When your agent uses it
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
What it loads into context
Frontmatter
59 tokensAlways available to the agent
SKILL.md
4,546 tokensWhen the skill is activated
Reference documents
8,223 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- USPTO API Ecosystem
- Quick Start
- Task 1: Searching Patents
- Task 2: Retrieving Patent Examination Data
- Task 3: Searching and Monitoring Trademarks
- Task 4: Tracking Assignments and Ownership
- Task 5: Accessing Additional USPTO Data
- Complete Analysis Example
- Best Practices
- Important Notes
- Resources
Scripts executed separately
scripts/patent_search.pyscripts/peds_client.pyscripts/trademark_client.py
Files
SKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesSKILL.mdcore18,718 bytesreferences/additional_apis.mddoc9,773 bytesreferences/patentsearch_api.mddoc7,435 bytesreferences/peds_api.mddoc6,546 bytesreferences/trademark_api.mddoc9,754 bytesscripts/patent_search.pyruns9,023 bytesscripts/peds_client.pyruns9,602 bytesscripts/trademark_client.pyruns10,564 bytes
Read SKILL.md
# USPTO Database
## Overview
USPTO provides specialized APIs for patent and trademark data. Search patents by keywords/inventors/assignees, retrieve examination history via PEDS, track assignments, analyze citations and office actions, access TSDR for trademarks, for IP analysis and prior art searches.
## When to Use This Skill
This skill should be used when:
- **Patent Search**: Finding patents by keywords, inventors, assignees, classifications, or dates
- **Patent Details**: Retrieving full patent data including claims, abstracts, citations
- **Trademark Search**: Looking up trademarks by serial or registration number
- **Trademark Status**: Checking trademark status, ownership, and prosecution historyux-researcher-designer
When your agent uses it
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
184 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Core Capabilities
- Key Scripts
Scripts executed separately
scripts/persona_generator.py
Files
SKILL.mdcore950 bytesscripts/persona_generator.pyruns20,849 bytes
Read SKILL.md
# UX Researcher & Designer
Comprehensive toolkit for user-centered research and experience design.
## Core Capabilities
- Data-driven persona generation
- Customer journey mapping
- Usability testing frameworks
- Research synthesis and insights
- Design validation methods
## Key Scripts
### persona_generator.pyvaex
When your agent uses it
Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.
What it loads into context
Frontmatter
120 tokensAlways available to the agent
SKILL.md
1,509 tokensWhen the skill is activated
Reference documents
21,124 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Start Pattern
- Working with References
- Best Practices
- Common Patterns
- Resources
Files
SKILL.mdcore6,595 bytesSKILL.mdcore6,595 bytesSKILL.mdcore6,595 bytesSKILL.mdcore6,595 bytesSKILL.mdcore6,595 bytesreferences/core_dataframes.mddoc7,878 bytesreferences/data_processing.mddoc12,451 bytesreferences/io_operations.mddoc14,989 bytesreferences/machine_learning.mddoc15,941 bytesreferences/performance.mddoc13,705 bytesreferences/visualization.mddoc13,188 bytes
Read SKILL.md
# Vaex
## Overview
Vaex is a high-performance Python library designed for lazy, out-of-core DataFrames to process and visualize tabular datasets that are too large to fit into RAM. Vaex can process over a billion rows per second, enabling interactive data exploration and analysis on datasets with billions of rows.
## When to Use This Skill
Use Vaex when:
- Processing tabular datasets larger than available RAM (gigabytes to terabytes)
- Performing fast statistical aggregations on massive datasets
- Creating visualizations and heatmaps of large datasets
- Building machine learning pipelines on big data
- Converting between data formats (CSV, HDF5, Arrow, Parquet)venue-templates
When your agent uses it
Use when preparing manuscripts, conference papers, or academic posters that need venue-specific templates, LaTeX style files, author guidelines, page limits, anonymity rules, camera-ready formatting, or submission compliance checks.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
3,694 tokensWhen the skill is activated
Reference documents
19,220 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Boundary
- Core Capabilities
- Workflow: Finding and Using Templates
- Template Categories
- Helper Scripts
- Best Practices
- Common Formatting Requirements
- Resources
- Example Usage
- Updates and Maintenance
- Summary
Scripts executed separately
scripts/customize_template.pyscripts/query_template.pyscripts/validate_format.py
Files
SKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesSKILL.mdcore15,772 bytesassets/grants/nih_specific_aims.texasset9,082 bytesassets/grants/nsf_proposal_template.texasset13,157 bytesassets/journals/nature_article.texasset6,242 bytesassets/journals/neurips_article.texasset8,925 bytesassets/journals/plos_one.texasset11,713 bytesassets/posters/beamerposter_academic.texasset8,495 bytesreferences/conferences_formatting.mddoc17,164 bytesreferences/grants_requirements.mddoc22,873 bytesreferences/journals_formatting.mddoc17,649 bytesreferences/posters_guidelines.mddoc17,113 bytesscripts/customize_template.pyruns6,875 bytesscripts/query_template.pyruns8,959 bytesscripts/validate_format.pyruns8,766 bytes
Read SKILL.md
# Venue Templates
## Overview
Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues, academic conferences, and research posters. This skill provides ready-to-use templates and detailed specifications for academic publication submissions.
Use this skill when preparing manuscripts for journal submission, conference papers, or research posters and need venue-specific formatting requirements and templates.
## When to Use This Skill
This skill should be used when:
- Preparing a manuscript for submission to a specific journal (Nature, Science, PLOS, IEEE, etc.)
- Writing a conference paper with specific formatting requirements (NeurIPS, ICML, CHI, etc.)
- Creating an academic research poster for conferencesvercel-deploy
When your agent uses it
Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
606 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Quick Start
- Fallback (No Auth)
- Production Deploys
- Output
- Troubleshooting
Scripts executed separately
scripts/deploy.sh
Files
LICENSE.txtdoc1,063 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesSKILL.mdcore2,653 bytesagents/openai.yamlasset306 bytesassets/vercel-small.svgasset243 bytesassets/vercel.pngasset788 bytesscripts/deploy.shruns8,877 bytes
Read SKILL.md
# Vercel Deploy
Deploy any project to Vercel instantly. **Always deploy as preview** (not production) unless the user explicitly asks for production.
## Prerequisites
- Check whether the Vercel CLI is installed **without** escalated permissions (for example, `command -v vercel`).
- Only escalate the actual deploy command if sandboxing blocks the deployment network calls (`sandbox_permissions=require_escalated`).
- The deployment might take a few minutes. Use appropriate timeout values.
## Quick Start
1. Check whether the Vercel CLI is installed (no escalation for this check):
verification-before-completion
When your agent uses it
Completion-evidence route used before claiming work is complete, fixed, passing, committed, or PR-ready. Requires fresh verification output before success claims. Do not use for root-cause debugging, TDD implementation, test-report packaging, or review-feedback triage.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
1,053 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Routing Boundary
- The Iron Law
- The Gate Function
- Common Failures
- Red Flags - STOP
- Rationalization Prevention
- Key Patterns
- Why This Matters
- When To Apply
- The Bottom Line
Files
SKILL.mdcore4,535 bytes
Read SKILL.md
# Verification Before Completion
## Overview
Claiming work is complete without verification is dishonesty, not efficiency.
**Core principle:** Evidence before claims, always.
## Routing Boundary
Use this skill at the end of work, when the question is "can we honestly claim this is done?" Use `systematic-debugging` for unexplained failures, `tdd-guide` for test-first implementation, and `generating-test-reports` when the deliverable is a readable test report.
**Violating the letter of this rule is violating the spirit of this rule.**
Verification & Quality Assurance
When your agent uses it
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
What it loads into context
Frontmatter
82 tokensAlways available to the agent
SKILL.md
4,010 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- What This Skill Does
- Prerequisites
- Quick Start
- Complete Guide
Files
SKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytesSKILL.mdcore16,032 bytes
Read SKILL.md
# Verification & Quality Assurance Skill
## What This Skill Does
This skill provides a comprehensive verification and quality assurance system that ensures code quality and correctness through:
- **Truth Scoring**: Real-time reliability metrics (0.0-1.0 scale) for code, agents, and tasks
- **Verification Checks**: Automated code correctness, security, and best practices validation
- **Automatic Rollback**: Instant reversion of changes that fail verification (default threshold: 0.95)
- **Quality Metrics**: Statistical analysis with trends, confidence intervals, and improvement tracking
- **CI/CD Integration**: Export capabilities for continuous integration pipelines
- **Real-time Monitoring**: Live dashboards and watch modes for ongoing verification
## Prerequisitesvideo-studio
When your agent uses it
Use when the user asks to create or edit videos end-to-end (script→video, auto-cut/jumpcut, captions/subtitles, polishing for Shorts/Reels/TikTok). Current implemented backend: local FFmpeg (probe/render/jumpcut/burn-subtitles/polish). Planned/optional backends: Remotion (motion graphics templates), VectCutAPI (CapCut/剪映 timeline editing), and video-audio-mcp (MCP tool wrapper) when available. Produces a finished video artifact (MP4 by default) from assets + copy + a design/storyboard plan.
What it loads into context
Frontmatter
132 tokensAlways available to the agent
SKILL.md
1,550 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 何时使用
- 背后能力（融合方案）
- 先跑一次环境探测（强烈推荐）
- 产物约定（建议）
- 最小闭环：用 spec 直接生成视频（FFmpeg backend）
- “打磨”步骤（推荐作为最后一步）
- 自动剪辑：JumpCut（去静音/去停顿）
- 字幕烧录（SRT → MP4）
- 需要 AI 生成素材时（可选）
- 质量门禁（交付前自检）
- 边界
Scripts executed separately
scripts/video_studio.py
Files
SKILL.mdcore5,162 bytesSKILL.mdcore5,162 bytesSKILL.mdcore5,162 bytesSKILL.mdcore5,162 bytesSKILL.mdcore5,162 bytesSKILL.mdcore5,162 bytesreferences/sample_spec.jsonasset1,264 bytesscripts/video_studio.pyruns27,869 bytes
Read SKILL.md
# Video Studio (自动视频制作 / 剪辑 / 打磨)
目标：把「素材（视频/音频/图片）+ 文案 + 编排/设计方案」自动变成可发布的成片，并在最后做一轮“打磨”（节奏、转场、字幕、音量、编码）。
## 何时使用
- 你要“从 0 生成一个视频”（口播/科普/产品介绍/短视频）
- 你要“自动剪辑已有视频/音频”（去静音、裁切、拼接、转场、加字幕、加 Logo/BGM）
- 你要“适配平台规格”（9:16 / 1:1 / 16:9、码率、分辨率、时长上限）
- 你要“自动抛光”（音量标准化、fade in/out、H.264/yuv420p、帧率、字幕烧录）
## 背后能力（融合方案）
本 skill 不绑定单一引擎，而是按可用性选择 backend：
1. **FFmpeg（基线后端，必备）**visualization-best-practices
When your agent uses it
Review chart choice, labeling, accessibility, and storytelling quality for existing visualizations. Use as an explicit/manual helper for critique and cleanup, not as the main owner for scientific figure production or general chart generation.
What it loads into context
Frontmatter
95 tokensAlways available to the agent
SKILL.md
293 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Positioning
- When to Use
- Not For / Boundaries
- Typical Outputs
- Related Skills
Files
SKILL.mdcore1,374 bytes
Read SKILL.md
# Visualization Best Practices
## Positioning
Treat this skill as an explicit/manual review helper.
## When to Use
Use this skill when:
- Reviewing whether an existing chart communicates clearly
- Fixing labels, legends, scales, color choices, or accessibility issues
- Deciding how to simplify a crowded dashboard or figure draft
## Not For / Boundariesvscode-release-notes-writer
When your agent uses it
Guidelines for writing and reviewing Insiders and Stable release notes for Visual Studio Code.
What it loads into context
Frontmatter
27 tokensAlways available to the agent
SKILL.md
1,142 tokensWhen the skill is activated
Reference documents
2,526 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- General writing guidelines for release notes
- Insiders Release Notes
- Stable Release Notes
Files
SKILL.mdcore5,617 bytesexamples/v1_109.mddoc3,887 bytesimages/vscode-insiders-banner-medium.pngasset130 bytesimages/vscode-insiders-header.webpasset135,567 bytestemplate-release-note-endgame.mddoc3,972 bytestemplate-release-note-insiders.mddoc1,899 bytes
Read SKILL.md
# Visual Studio Code Release Note Writer Guidelines
This skill is designed to help you write release notes for Visual Studio Code Insiders and Stable releases. It provides structured guidelines and examples to ensure consistency and clarity in the release notes.
There are two main types of release notes you can generate using this skill:
1. **Insiders Release Notes**: These notes cover the latest features and updates in the Insiders build of VS Code. They are updated frequently as new features are added. Their format includes sections grouped by the date of the updates. The content is generated based on closed GitHub issues and PRs for a specific milestone.
2. **Stable Release Notes**: These notes summarize the key features and improvements in a stable release of VS Code. They follow a more structured format with predefined sections for different feature areas. The release is intially created using a template and then updated by the engineering team.
Your task is help generate these release notes based on the provided guidelines, examples, and templates.
## General writing guidelines for release notes
Follow the guidelines in this order of priority:webthinker-deep-research
When your agent uses it
Deep web research for VCO: multi-hop search+browse+extract with an auditable action trace and a structured report (WebThinker-style).
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
1,038 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Non-goals (avoid redundancy)
- Output contract (must)
- Runtime (Upstream vendoring)
- Modes
- Action trace format (trace.jsonl)
- Quality gates
Scripts executed separately
scripts/init_webthinker_run.py
Files
SKILL.mdcore4,083 bytesSKILL.mdcore4,083 bytesSKILL.mdcore4,083 bytesSKILL.mdcore4,083 bytesSKILL.mdcore4,083 bytesscripts/init_webthinker_run.pyruns2,269 bytes
Read SKILL.md
# WebThinker Deep Research (VCO)
## When to use
Use this skill when the task requires **deep web research** (not just one-shot search), for example:
- Multi-hop questions (“find → open → follow links → verify”)
- “Deep research report” / “调研报告” / “竞品调研” / “技术调研”
- Need an **auditable trace** of web actions and sources
- Need to merge findings into a structured deliverable (report / brief / spec)
## Non-goals (avoid redundancy)
- For **quick citations** or “give me 3 sources”, prefer `research-lookup`.weights-and-biases
When your agent uses it
Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform
What it loads into context
Frontmatter
111 tokensAlways available to the agent
SKILL.md
3,272 tokensWhen the skill is activated
Reference documents
12,074 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Installation
- Quick Start
- Core Concepts
- Hyperparameter Sweeps
- Artifacts
- Integration Examples
- Visualization & Analysis
- Best Practices
- Team Collaboration
- Pricing
- Resources
- See Also
Files
SKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesSKILL.mdcore12,454 bytesreferences/artifacts.mddoc13,425 bytesreferences/integrations.mddoc16,219 bytesreferences/sweeps.mddoc17,675 bytes
Read SKILL.md
# Weights & Biases: ML Experiment Tracking & MLOps
## When to Use This Skill
Use Weights & Biases (W&B) when you need to:
- **Track ML experiments** with automatic metric logging
- **Visualize training** in real-time dashboards
- **Compare runs** across hyperparameters and configurations
- **Optimize hyperparameters** with automated sweeps
- **Manage model registry** with versioning and lineage
- **Collaborate on ML projects** with team workspaces
- **Track artifacts** (datasets, models, code) with lineage
**Users**: 200,000+ ML practitioners | **GitHub Stars**: 10.5k+ | **Integrations**: 100+windows-hook-debugging
When your agent uses it
Windows环境下Claude Code插件Hook执行错误的诊断与修复。当遇到hook error、cannot execute binary file、.sh regex误匹配、WSL/Git Bash冲突时使用。
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
307 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Not For / Boundaries
Files
SKILL.mdcore1,158 bytesSKILL.mdcore1,158 bytes
Read SKILL.md
# Windows Hook Debugging Skill
诊断和修复 Windows 环境下 Claude Code 插件 Hook 执行失败的问题。
## When to Use This Skill
触发条件（满足任一即可）：
- Claude Code 启动时出现 `SessionStart hook error` 或 `Stop hook error`
- 错误信息包含 `cannot execute binary file`
- 错误信息包含 `/d/` 或 `/c/` 风格的路径（MSYS2/Git Bash 路径格式）
- 错误信息包含 `bash: node: No such file or directory`
- 错误信息包含 WSL 相关乱码或 `wsl:` 前缀
- Hook 命令中包含 `.sh` 参数导致 Windows 下被错误处理
writing-docs
When your agent uses it
Guides for writing and editing Remotion documentation. Use when adding docs pages, editing MDX files in packages/docs, or writing documentation content.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
760 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Adding a new page
- Language guidelines
- Code snippets
- Special components
- Generating preview cards
- Verifying docs compile
Files
SKILL.mdcore3,147 bytesSKILL.mdcore3,147 bytesSKILL.mdcore3,147 bytes
Read SKILL.md
# Writing Remotion Documentation
Documentation lives in `packages/docs/docs` as `.mdx` files.
## Adding a new page
1. Create a new `.mdx` file in `packages/docs/docs`
2. Add the document to `packages/docs/sidebars.ts`
3. Write the content following guidelines below
4. Run `bun render-cards.ts` in `packages/docs` to generate social preview cards
**One API per page**: Each function or API should have its own dedicated documentation page. Do not combine multiple APIs (e.g., `getEncodableVideoCodecs()` and `getEncodableAudioCodecs()`) on a single page. This is the established pattern throughout the codebase.
**Public API only**: Documentation is for public APIs only. Do not mention, reference, or compare against internal/private APIs or implementation details. Users should only see what is exported and intended for public use.writing-plans
When your agent uses it
Use when you have a spec or requirements for a multi-step task, before touching code
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
795 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Bite-Sized Task Granularity
- Plan Document Header
- Task Structure
- Remember
- Execution Handoff
Files
SKILL.mdcore3,266 bytesSKILL.mdcore3,266 bytesSKILL.mdcore3,266 bytesSKILL.mdcore3,266 bytes
Read SKILL.md
# Writing Plans
## Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
**Announce at start:** "I'm using the writing-plans skill to create the implementation plan."
**Context:** This should be run in a dedicated worktree (created by brainstorming skill).
**Save plans to:** `docs/plans/YYYY-MM-DD-<feature-name>.md`
xan
When your agent uses it
High-performance CSV processing with xan CLI for large tabular datasets, streaming transformations, and low-memory pipelines.
What it loads into context
Frontmatter
27 tokensAlways available to the agent
SKILL.md
313 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Boundaries
- Script
Scripts executed separately
scripts/xan.ps1
Files
SKILL.mdcore1,251 bytesSKILL.mdcore1,251 bytesscripts/xan.ps1runs497 bytes
Read SKILL.md
# xan
Use this skill when tabular work involves large CSV-like files and shell-oriented data pipelines.
## When to Use
- CSV/TSV files are large (size or rows) and Python/pandas style processing is too heavy.
- You need fast CLI operations such as `filter`, `sort`, `dedup`, `groupby`, `frequency`, `join`.
- You want low-memory streaming workflows in terminal pipelines.
## Boundaries
- Not for workbook semantics (`.xlsx` formula/layout preservation) — use `xlsx` or `excel-analysis`.
- Not for ML model training pipelines — use `data-ml` skills.xlsx
When your agent uses it
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
2,867 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- All Excel files
- Financial models
- Overview
- Visual Enhancement with Scientific Schematics
- Important Requirements
- Reading and analyzing data
- Excel File Workflows
- CRITICAL: Use Formulas, Not Hardcoded Values
- Common Workflow
- Recalculating formulas
- Formula Verification Checklist
- Best Practices
- Code Style Guidelines
Scripts executed separately
recalc.py
Files
LICENSE.txtdoc1,467 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesSKILL.mdcore11,837 bytesrecalc.pyruns6,408 bytes
Read SKILL.md
# Requirements for Outputs
## All Excel files
### Zero Formula Errors
- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
### Preserve Existing Templates (when updating templates)
- Study and EXACTLY match existing format, style, and conventions when modifying files
- Never impose standardized formatting on files with established patterns
- Existing template conventions ALWAYS override these guidelines
## Financial models
yeet
When your agent uses it
Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
418 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Naming conventions
- Workflow
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore1,695 bytesagents/openai.yamlasset273 bytesassets/yeet-small.svgasset967 bytesassets/yeet.pngasset1,262 bytes
Read SKILL.md
## Prerequisites
- Require GitHub CLI `gh`. Check `gh --version`. If missing, ask the user to install `gh` and stop.
- Require authenticated `gh` session. Run `gh auth status`. If not authenticated, ask the user to run `gh auth login` (and re-run `gh auth status`) before continuing.
## Naming conventions
- Branch: `codex/{description}` when starting from main/master/default.
- Commit: `{description}` (terse).
- PR title: `[codex] {description}` summarizing the full diff.
## Workflow
- If on main/master/default, create a branch: `git checkout -b "codex/{description}"`zarr-python
When your agent uses it
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
5,568 tokensWhen the skill is activated
Reference documents
3,802 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Quick Start
- Core Operations
- Chunking Strategies
- Compression
- Storage Backends
- Groups and Hierarchies
- Attributes and Metadata
- Integration with NumPy, Dask, and Xarray
- Parallel Computing and Synchronization
- Consolidated Metadata
- Performance Optimization
- Common Patterns and Best Practices
- Common Issues and Solutions
- Additional Resources
Files
SKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesSKILL.mdcore20,046 bytesreferences/api_reference.mddoc12,538 bytes
Read SKILL.md
# Zarr Python
## Overview
Zarr is a Python library for storing large N-dimensional arrays with chunking and compression. Apply this skill for efficient parallel I/O, cloud-native workflows, and seamless integration with NumPy, Dask, and Xarray.
## Quick Start
### Installation
```bash
uv pip install zarr
```
Skills included
- vibe
- skill-creator
- skill-installer
- LQF_Machine_Learning_Expert_Guide
- adaptyv
- aeon
- algorithmic-art
- alpha-vantage
- architecture-patterns
- astropy
- autonomous-builder
- bio-database-evidence
- biopython
- brainstorming
- cancel-ralph
- chembl-database
- citation-management
- claude-skills
- clinical-decision-support
- clinical-reports
- clinicaltrials-database
- clinpgx-database
- code-reviewer
- coding-tutor
- commit-with-reflection
- comprehensive-research-agent
- content-research-writer
- context-fundamentals
- context-hunter
- create-plan
- creating-data-visualizations
- cs-foundations
- dask
- data-artist
- data-quality-frameworks
- data-storytelling
- datacommons-client
- datavis
- denario
- designing-experiments
- deslop
- detecting-data-anomalies
- detecting-performance-regressions
- dialectic
- digital-brain
- dnanexus-integration
- doc
- docs-review
- docs-write
- document-skills
- docx
- pptx
- documentation-lookup
- docx
- docx-comment-reply
- edgartools
- embedding-strategies
- ena-database
- Error Resolver
- etetoolkit
- evals-context
- evaluating-code-models
- evaluating-llms-harness
- evaluating-machine-learning-models
- explaining-machine-learning-models
- exploratory-data-analysis
- fda-database
- figma-implement-design
- file-organizer
- flashrag-evidence
- fluidsim
- fred-economic-data
- G2 Legend Expert
- generate-image
- generating-test-reports
- geo-database
- geomaster
- geopandas
- get-available-resources
- gh-address-comments
- gh-fix-ci
- gradient-methods
- gtars
- hedgefundmonitor
- histolab
- hive-mind-advanced
- hypothesis-generation
- hypothesis-testing
- imagegen
- imaging-data-commons
- infographics
- iso-13485-certification
- jupyter-notebook
- knowledge-steward
- lamindb
- latchbio-integration
- latex-posters
- latex-submission-pipeline
- literature-review
- local-vco-roles
- manuscript-as-code
- markdown-mermaid-writing
- market-research-reports
- markitdown
- matchms
- math
- math-model-selector
- math-tools
- mathematical-logic-expert
- matlab
- matplotlib
- MCP Integration
- medchem
- metabolomics-workbench-database
- metric-calculator
- ml-data-leakage-guard
- ml-pipeline-workflow
- netlify-deploy
- networkx
- neurokit2
- neuropixels-analysis
- node-zombie-guardian
- nowait-reasoning-optimizer
- omero-integration
- openai-docs
- openai-knowledge
- openalex-database
- paper-2-web
- pathml
- peer-review
- performance-testing
- performing-causal-analysis
- perplexity-search
- planning-with-files
- playwright
- plotly
- polars
- pptx-posters
- preprocessing-data-with-automated-pipelines
- prompt-lookup
- property-based-testing
- propositional-logic
- providing-performance-optimization-advice
- prowler-docs
- pubmed-database
- pufferlib
- pydeseq2
- pydicom
- pyhealth
- pymatgen
- pymc-bayesian-modeling
- pymc-bayesian-modeling
- pymoo
- pyopenms
- pytorch-lightning
- pyzotero
- ralph-loop
- rdkit
- receiving-code-review
- report-generator
- requesting-code-review
- research-grants
- research-lookup
- rowan
- scanpy
- scholar-evaluation
- scholarly-publishing
- scientific-brainstorming
- scientific-critical-thinking
- scientific-data-preprocessing
- scientific-reporting
- scientific-schematics
- scientific-slides
- scientific-visualization
- scientific-writing
- scikit-bio
- scikit-learn
- scikit-survival
- scrapling
- screenshot
- seaborn
- security-best-practices
- security-ownership-map
- security-reviewer
- security-threat-model
- senior-computer-vision
- senior-data-scientist
- senior-ml-engineer
- senior-prompt-engineer
- sentry
- shap
- similarity-search-patterns
- simpy
- skill-creator
- skill-lookup
- skypilot-multi-cloud-orchestration
- slides-as-code
- smart-file-writer
- sparse-autoencoder-training
- spec-kit-vibe-compat
- speckit-analyze
- speckit-checklist
- speckit-clarify
- speckit-constitution
- speckit-implement
- speckit-plan
- speckit-specify
- speckit-tasks
- speckit-taskstoissues
- speech
- splitting-datasets
- spreadsheet
- stable-baselines3
- statistical-analysis
- statistics-math
- statsmodels
- structured-content-storage
- subagent-driven-development
- submission-checklist
- sympy
- systematic-debugging
- tdd-guide
- tensorboard
- theme-factory
- think-harder
- tiledbvcf
- timesfm-forecasting
- torch-geometric
- torchdrug
- transcribe
- transformer-lens-interpretability
- transformers
- treatment-plans
- umap-learn
- uniprot-database
- unsloth
- usfiscaldata
- uspto-database
- ux-researcher-designer
- vaex
- venue-templates
- vercel-deploy
- verification-before-completion
- Verification & Quality Assurance
- video-studio
- visualization-best-practices
- vscode-release-notes-writer
- webthinker-deep-research
- weights-and-biases
- windows-hook-debugging
- writing-docs
- writing-plans
- xan
- xlsx
- yeet
- zarr-python
Repository facts
- License
- Apache-2.0
- Created
- Feb 22, 2026
- Last pushed
- Nov 4, 2026
- Forks
- 344
- Open issues
- 39
- Project activity
- Active
Rank over the last 12 weeks
Now #334 · best #287 · down 38 in 30 days
- #325 on Nov 2
- #327 on Nov 3
- #328 on Nov 4
- #330 on Nov 5
- #332 on Nov 6
- #334 since Nov 7
78 earlier periods
- #303 on Aug 2
- #305 from Aug 8 to Aug 9
- #312 on Aug 10
- #310 on Aug 11
- #307 on Aug 12
- #311 on Aug 13
- #307 on Aug 14
- #301 on Aug 15
- #303 on Aug 16
- #300 on Aug 17
- #306 on Aug 18
- #304 on Aug 19
- #299 on Aug 20
- #301 on Aug 21
- #296 on Aug 22
- #302 on Aug 23
- #301 on Aug 24
- #302 on Aug 25
- #301 on Aug 26
- #298 on Aug 27
- #300 on Aug 28
- #297 on Aug 29
- #290 on Aug 30
- #296 on Aug 31
- #298 on Sep 1
- #297 on Sep 2
- #304 on Sep 3
- #296 on Sep 4
- #292 on Sep 5
- #293 on Sep 6
- #300 on Sep 7
- #298 on Sep 8
- #296 from Sep 9 to Sep 10
- #292 on Sep 11
- #296 on Sep 12
- #295 on Sep 13
- #299 on Sep 14
- #300 on Sep 15
- #296 on Sep 16
- #293 on Sep 17
- #295 on Sep 18
- #290 on Sep 19
- #295 on Sep 20
- #292 on Sep 21
- #295 from Sep 22 to Sep 24
- #292 on Sep 25
- #287 on Sep 26
- #292 on Sep 27
- #297 from Sep 28 to Sep 29
- #295 on Sep 30
- #292 on Oct 1
- #296 on Oct 2
- #290 on Oct 3
- #288 on Oct 4
- #295 on Oct 5
- #294 on Oct 6
- #295 on Oct 7
- #296 on Oct 8
- #300 on Oct 9
- #294 on Oct 10
- #293 on Oct 11
- #299 on Oct 12
- #297 on Oct 13
- #299 on Oct 14
- #298 on Oct 15
- #299 from Oct 16 to Oct 17
- #300 on Oct 18
- #304 from Oct 19 to Oct 20
- #305 on Oct 21
- #308 on Oct 22
- #305 on Oct 23
- #308 on Oct 24
- #312 on Oct 25
- #315 on Oct 28
- #317 on Oct 29
- #322 on Oct 30
- #324 on Oct 31
- #323 on Nov 1
Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 4, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 4,027 notes
SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedSKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddocs/assets/install-cta-cn-dark.svg:9Analysis incomplete: physical or joined line exceeds character limitdocs/assets/install-cta-cn-dark.svg:10Analysis incomplete: physical or joined line exceeds character limitdocs/assets/install-cta-cn-light.svg:9Analysis incomplete: physical or joined line exceeds character limitdocs/assets/install-cta-cn-light.svg:10Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:8Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:9Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:10Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:11Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:12Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:15Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:18Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:16Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:19Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:17Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:20Analysis incomplete: physical or joined line exceeds character limitdocs/assets/readme-chapter-01-cn-dark.svg:21Analysis incomplete: physical or joined line exceeds character limit
- 48 broad permissionsin 48 files: LQF_Machine_Learning_Expert_Guide/SKILL.md:1 autonomous-builder/SKILL.md:1 citation-management/SKILL.md:1 and 45 more
- 137 dangerous shell commandsin 57 files: unsloth/references/llms-txt.md:188 autonomous-builder/references/multi-layer-security.md:200 error-resolver/patterns/docker.md:123 and 54 more
- 7,155 network referencesin 700 files: unsloth/references/llms-txt.md:35 config/upstream-lock.json:5 metabolomics-workbench-database/references/api_reference.md:7 and 697 more
- 22 obfuscation signalsin 11 files: infographics/scripts/generate_infographic_ai.py:652 scientific-schematics/scripts/generate_schematic_ai.py:277 scientific-slides/scripts/generate_slide_image_ai.py:277 and 8 more
- 12 instruction override signalsin 4 files: autonomous-builder/assets/auto-continue.ps1:220 autonomous-builder/SKILL.md:424 autonomous-builder/assets/auto-continue.sh:202 and 1 more
- 1,019 executable scriptsin 1,018 files: pptx/scripts/thumbnail.py:1 _python_source_roots.py:1 apps/vgo-cli/src/vgo_cli/__init__.py:1 and 1,015 more
- 1,167 references to secretsin 247 files: fda-database/references/devices.md:53 tests/runtime_neutral/test_router_ai_connectivity_probe.py:54 scientific-schematics/scripts/generate_schematic_ai.py:12 and 244 more
- No requests to vote in Hot
Show all 9,560 signals by file
.github/workflows/vco-release-proof.yml
- Access to secretsline 44
[Credential-related source omitted]
.gitignore
- Access to secretsline 59
[Credential-related source omitted]
LICENSE
README.md
- Network accessline 23
<a href="https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest"> - Network accessline 56
**vibeskills v4.1.0** was benchmarked on **SkillsBench** (https://www.skillsbench.ai/) using **DeepSeekV4Flash-VE** and **OpenHands** as the baseline evaluation setup. Compared with the baseline without vibeskills, vibeskills increased the - Network accessline 61
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 62
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 69
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 70
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 84
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/blob/main/studies/full-skills-comparison/README.md">Study, public data, and reproduction</a> · - Network accessline 85
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/blob/main/studies/full-skills-comparison/README.md">Study, public data, and reproduction</a> · - Network accessline 450
Maintainers can use the [pre-release checks](https://github.com/foryourhealth111-pixel/Vibe-Skills/actions/workflows/vco-gates.yml). Start with - Network accessline 451
[pre-release checks](https://github.com/foryourhealth111-pixel/Vibe-Skills/actions/workflows/vco-gates.yml). Start with - Network accessline 492
<tr><td align="center">Install, update, uninstall</td><td align="center"><strong><a href="./docs/install/README.en.md">Simple install</a></strong></td></tr> <tr><td align="center">First use</td><td align="center"><strong><a href="./docs - Network accessline 493
<tr><td align="center">First use</td><td align="center"><strong><a href="./docs/quick-start.en.md">Quick start</a></strong></td></tr> <tr><td align="center">Current release</td><td align="center"><strong><a href="https://github.com/fory - Network accessline 494
<tr><td align="center">Current release</td><td align="center"><strong><a href="https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest">GitHub release metadata</a></strong></td></tr> - Network accessline 511
Questions, corrections, and well-scoped contributions are welcome through [GitHub Issues](https://github.com/foryourhealth111-pixel/Vibe-Skills/issues) and pull requests. - Network accessline 512
[GitHub Issues](https://github.com/foryourhealth111-pixel/Vibe-Skills/issues) - Network accessline 515
VibeSkills discussions and community practice can also continue on [LINUX DO](https://linux.do/). It is a place to exchange technical questions, - Network accessline 516
[LINUX DO](https://linux.do/). It is a place to exchange technical questions, - Network accessline 520
The [VibeSkills 3.1.0 community practice cases](https://linux.do/t/topic/2061161) - Network accessline 523
Community contributors include [xiaozhongyaonvli](https://github.com/xiaozhongyaonvli) and - Network accessline 524
[xiaozhongyaonvli](https://github.com/xiaozhongyaonvli) and - Network accessline 525
[ruirui2345](https://github.com/ruirui2345).
README.zh.md
- Network accessline 23
<a href="https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest"> - Network accessline 57
vibeskills的4.1.0版本在Skillsbench (https://www.skillsbench.ai/) 上使用DeepSeekV4Flash-VE和Openhands进行基线测试。相比未使用vibeskills组的情况，vibeskills将平均 Verifier Reward 提升 21.12 个百分点，同时将Token消耗降低29.6%、工具调用减少33.1%。 - Network accessline 61
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 62
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 69
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 70
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/tree/main/studies/full-skills-comparison"> - Network accessline 79
<p align="center"> <a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/blob/main/studies/full-skills-comparison/README.zh-CN.md">完整研究、公开数据与复现方法</a> · - Network accessline 80
<a href="https://github.com/foryourhealth111-pixel/vibeskills-benchmark/blob/main/studies/full-skills-comparison/README.zh-CN.md">完整研究、公开数据与复现方法</a> · - Network accessline 427
维护项目时，可以查看 [CI 检查结果](https://github.com/foryourhealth111-pixel/Vibe-Skills/actions/workflows/vco-gates.yml) 和本地 `check.ps1` 输出。 - Network accessline 468
<tr><td align="center">安装、更新、卸载</td><td align="center"><strong><a href="./docs/install/README.md">简明安装指南</a></strong></td></tr> <tr><td align="center">第一次使用</td><td align="center"><strong><a href="./docs/quick-start.md">快速开始</a></strong - Network accessline 469
<tr><td align="center">第一次使用</td><td align="center"><strong><a href="./docs/quick-start.md">快速开始</a></strong></td></tr> <tr><td align="center">当前发布版本</td><td align="center"><strong><a href="https://github.com/foryourhealth111-pixel/Vibe - Network accessline 470
<tr><td align="center">当前发布版本</td><td align="center"><strong><a href="https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest">GitHub Release 元数据</a></strong></td></tr> - Network accessline 487
问题、纠错和范围清晰的贡献都可以通过 [GitHub Issues](https://github.com/foryourhealth111-pixel/Vibe-Skills/issues) - Network accessline 488
[GitHub Issues](https://github.com/foryourhealth111-pixel/Vibe-Skills/issues) - Network accessline 491
VibeSkills 的使用讨论和社区实践也可以在 [LINUX DO](https://linux.do/) 继续交流。 - Network accessline 495
想看已经公开分享过的实践，可以从 [VibeSkills 3.1.0 社区实践案例](https://linux.do/t/topic/2061161) 开始。 - Network accessline 496
[VibeSkills 3.1.0 社区实践案例](https://linux.do/t/topic/2061161) 开始。 - Network accessline 498
社区贡献者包括 [xiaozhongyaonvli](https://github.com/xiaozhongyaonvli) 和 - Network accessline 499
[xiaozhongyaonvli](https://github.com/xiaozhongyaonvli) 和 - Network accessline 500
[ruirui2345](https://github.com/ruirui2345)。
_python_source_roots.py
- Executable scriptline 1
Executable file
adapters/claude-code/settings-map.json
- Access to secretsline 13
[Credential-related source omitted]
adapters/codex/settings-map.json
- Access to secretsline 11
[Credential-related source omitted]
apps/vgo-cli/src/vgo_cli/__init__.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/commands.py
apps/vgo-cli/src/vgo_cli/core_bridge.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/errors.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/external.py
apps/vgo-cli/src/vgo_cli/hosts.py
apps/vgo-cli/src/vgo_cli/install_gates.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/install_support.py
apps/vgo-cli/src/vgo_cli/installer_bridge.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/main.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/output.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/process.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/repo.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/skill_surface.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/upgrade_service.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/upgrade_state.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/version_reminder.py
- Executable scriptline 1
Executable file
apps/vgo-cli/src/vgo_cli/workspace.py
- Executable scriptline 1
Executable file
bundled/skills/.system/skill-creator/assets/skill-creator-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" viewBox="0 0 20 20">
bundled/skills/.system/skill-creator/license.txt
bundled/skills/.system/skill-creator/references/openai_yaml.md
bundled/skills/.system/skill-creator/scripts/generate_openai_yaml.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/.system/skill-creator/scripts/init_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/.system/skill-creator/scripts/quick_validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/.system/skill-installer/LICENSE.txt
bundled/skills/.system/skill-installer/SKILL.md
- Network accessline 10
Helps install skills. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimen - Network accessline 38
- Example (experimental list): `scripts/list-skills.py --path skills/.experimental` - `scripts/install-skill-from-github.py --repo <owner>/<repo> --path <path/to/skill> [<path/to/skill> ...]` - `scripts/install-skill-from-github.py --url ht - Network accessline 39
- `scripts/install-skill-from-github.py --repo <owner>/<repo> --path <path/to/skill> [<path/to/skill> ...]` - `scripts/install-skill-from-github.py --url https://github.com/<owner>/<repo>/tree/<ref>/<path>` - Example (experimental skill): ` - Network accessline 40
- `scripts/install-skill-from-github.py --url https://github.com/<owner>/<repo>/tree/<ref>/<path>` - Network accessline 54
- Curated listing is fetched from `https://github.com/openai/skills/tree/main/skills/.curated` via the GitHub API. If it is unavailable, explain the error and exit. - Private GitHub repos can be accessed via existing git credentials or opti - Network accessline 55
- Private GitHub repos can be accessed via existing git credentials or optional `GITHUB_TOKEN`/`GH_TOKEN` for download. - Git fallback tries HTTPS first, then SSH. - The skills at https://github.com/openai/skills/tree/main/skills/.system ar - Network accessline 56
- Git fallback tries HTTPS first, then SSH. - The skills at https://github.com/openai/skills/tree/main/skills/.system are preinstalled, so no need to help users install those. If they ask, just explain this. If they insist, you can download - Network accessline 57
- The skills at https://github.com/openai/skills/tree/main/skills/.system are preinstalled, so no need to help users install those. If they ask, just explain this. If they insist, you can download and overwrite.
bundled/skills/.system/skill-installer/assets/skill-installer-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/.system/skill-installer/scripts/github_utils.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 12
[Credential-related source omitted] - Network accessline 13
[Credential-related source omitted] - Network accessline 14
headers["Authorization"] = f"token {token}" req = urllib.request.Request(url, headers=headers) with urllib.request.urlopen(req) as resp: - Network accessline 15
req = urllib.request.Request(url, headers=headers) - Network accessline 16
with urllib.request.urlopen(req) as resp: - Network accessline 20
def github_api_contents_url(repo: str, path: str, ref: str) -> str: return f"https://api.github.com/repos/{repo}/contents/{path}?ref={ref}" - Network accessline 21
return f"https://api.github.com/repos/{repo}/contents/{path}?ref={ref}"
bundled/skills/.system/skill-installer/scripts/install-skill-from-github.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 46
[Credential-related source omitted] - Network accessline 80
def _download_repo_zip(owner: str, repo: str, ref: str, dest_dir: str) -> str: zip_url = f"https://codeload.github.com/{owner}/{repo}/zip/{ref}" - Network accessline 81
zip_url = f"https://codeload.github.com/{owner}/{repo}/zip/{ref}" - Network accessline 179
def _build_repo_url(owner: str, repo: str) -> str: return f"https://github.com/{owner}/{repo}.git" - Network accessline 180
return f"https://github.com/{owner}/{repo}.git" - Network accessline 248
parser = argparse.ArgumentParser(description="Install a skill from GitHub.") parser.add_argument("--repo", help="owner/repo") parser.add_argument("--url", help="https://github.com/owner/repo[/tree/ref/path]") - Network accessline 249
parser.add_argument("--repo", help="owner/repo") parser.add_argument("--url", help="https://github.com/owner/repo[/tree/ref/path]") parser.add_argument( - Network accessline 250
parser.add_argument("--url", help="https://github.com/owner/repo[/tree/ref/path]")
bundled/skills/.system/skill-installer/scripts/list-skills.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 35
[Credential-related source omitted] - Network accessline 56
raise ListError( "Skills path not found: " f"https://github.com/{repo}/tree/{ref}/{path}" - Network accessline 57
"Skills path not found: " f"https://github.com/{repo}/tree/{ref}/{path}" ) from exc - Network accessline 58
f"https://github.com/{repo}/tree/{ref}/{path}" ) from exc raise ListError(f"Failed to fetch skills: HTTP {exc.code}") from exc
bundled/skills/LQF_Machine_Learning_Expert_Guide/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/LQF_Machine_Learning_Expert_Guide/references/index.md
bundled/skills/adaptyv/SKILL.md
- Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 27
[Credential-related source omitted] - Network accessline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Network accessline 50
base_url = "https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws" - Access to secretsline 53
[Credential-related source omitted] - Network accessline 57
# Submit experiment response = requests.post( - Network accessline 58
response = requests.post( - Network accessline 62
"sequences": ">protein1\nMKVLWALLGLLGAA...", "experiment_type": "binding", "webhook_url": "https://your-webhook.com/callback" - Network accessline 63
"experiment_type": "binding", "webhook_url": "https://your-webhook.com/callback" } - Network accessline 64
"webhook_url": "https://your-webhook.com/callback"
bundled/skills/adaptyv/reference/api_reference.md
- Network accessline 6
https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws - Access to secretsline 14
[Credential-related source omitted] - Access to secretsline 23
[Credential-related source omitted] - Network accessline 41
"experiment_type": "binding|expression|thermostability|enzyme_activity", "target_id": "optional_target_identifier", "webhook_url": "https://your-webhook.com/callback", - Network accessline 42
"target_id": "optional_target_identifier", "webhook_url": "https://your-webhook.com/callback", "metadata": { - Network accessline 43
"webhook_url": "https://your-webhook.com/callback", - Network accessline 145
], "download_urls": { "raw_data": "https://...", - Network accessline 146
"download_urls": { "raw_data": "https://...", "analysis_package": "https://...", - Network accessline 147
"raw_data": "https://...", - Network accessline 148
"analysis_package": "https://...", - Network accessline 149
"report": "https://..." - Network accessline 305
For API issues or questions: - Email: support@adaptyvbio.com - Documentation updates: https://docs.adaptyvbio.com - Network accessline 306
- Email: support@adaptyvbio.com - Documentation updates: https://docs.adaptyvbio.com - Report bugs with experiment IDs and request details - Network accessline 307
- Documentation updates: https://docs.adaptyvbio.com
bundled/skills/adaptyv/reference/examples.md
- Network accessline 15
[Credential-related source omitted] - Access to secretsline 16
[Credential-related source omitted] - Network accessline 17
BASE_URL = "https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws" - Access to secretsline 21
[Credential-related source omitted] - Network accessline 26
"""Verify API connection and credentials""" try: response = requests.get(f"{BASE_URL}/organization/credits", headers=HEADERS) - Network accessline 27
try: response = requests.get(f"{BASE_URL}/organization/credits", headers=HEADERS) response.raise_for_status() - Network accessline 28
response = requests.get(f"{BASE_URL}/organization/credits", headers=HEADERS) - Access to secretsline 42
[Credential-related source omitted] - Network accessline 79
response = requests.post( - Network accessline 129
response = requests.post( - Network accessline 185
response = requests.post( - Network accessline 200
# Example webhook_url = "https://your-server.com/adaptyv-webhook" - Network accessline 201
webhook_url = "https://your-server.com/adaptyv-webhook" - Network accessline 221
response = requests.get( - Network accessline 263
response = requests.get( - Network accessline 337
# Get results response = requests.get( - Network accessline 338
response = requests.get( - Network accessline 479
response = requests.get( - Network accessline 528
response = requests.post( - Network accessline 775
for attempt in range(max_retries): try: response = requests.request(method, url, **kwargs) - Network accessline 776
try: response = requests.request(method, url, **kwargs) response.raise_for_status() - Network accessline 777
response = requests.request(method, url, **kwargs)
bundled/skills/adaptyv/reference/experiments.md
bundled/skills/adaptyv/reference/protein_optimization.md
- Network accessline 75
def predict_solubility_netsolp(sequence): """Predict protein solubility using NetSolP web service""" url = "https://services.healthtech.dtu.dk/services/NetSolP-1.0/api/predict" - Network accessline 77
url = "https://services.healthtech.dtu.dk/services/NetSolP-1.0/api/predict" - Network accessline 84
response = requests.post(url, data=data) - Network accessline 597
# Submit to Adaptyv import requests response = requests.post( - Network accessline 598
import requests response = requests.post( "https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws/experiments", - Network accessline 599
response = requests.post( - Network accessline 600
"https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws/experiments", - Access to secretsline 601
[Credential-related source omitted]
bundled/skills/aeon/SKILL.md
- Network accessline 365
- Documentation: https://www.aeon-toolkit.org/ - Network accessline 366
- GitHub: https://github.com/aeon-toolkit/aeon - Network accessline 367
- Examples: https://www.aeon-toolkit.org/en/stable/examples.html - Network accessline 368
- API Reference: https://www.aeon-toolkit.org/en/stable/api_reference.html
bundled/skills/aeon/references/networks.md
- Access to secretsline 182
[Credential-related source omitted]
bundled/skills/algorithmic-art/LICENSE.txt
bundled/skills/algorithmic-art/SKILL.md
- Network accessline 278
<head> <!-- p5.js from CDN - always available --> <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script> - Network accessline 279
<!-- p5.js from CDN - always available --> <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script> <style> - Network accessline 280
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script>
bundled/skills/algorithmic-art/templates/generator_template.js
- Executable scriptline 1
Executable file
bundled/skills/algorithmic-art/templates/viewer.html
- Network accessline 21
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Generative Art Viewer</title> <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script> - Network accessline 22
<title>Generative Art Viewer</title> <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script> <link rel="preconnect" href="https://fonts.googleapis.com"> - Network accessline 23
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.7.0/p5.min.js"></script> - Network accessline 24
<link rel="preconnect" href="https://fonts.googleapis.com"> - Network accessline 25
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> - Network accessline 26
<link href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;500;600&family=Lora:wght@400;500&display=swap" rel="stylesheet">
bundled/skills/alpha-vantage/SKILL.md
- Network accessline 15
1. Get a free key at https://www.alphavantage.co/support/#api-key (premium plans available for higher rate limits) - Access to secretsline 19
[Credential-related source omitted] - Network accessline 33
[Credential-related source omitted] - Network accessline 40
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Network accessline 41
BASE_URL = "https://www.alphavantage.co/query" - Network accessline 43
[Credential-related source omitted] - Network accessline 44
[Credential-related source omitted] - Access to secretsline 44
[Credential-related source omitted]
bundled/skills/alpha-vantage/references/fundamentals.md
- Network accessline 186
# Returns CSV format - use requests directly import requests, csv, io, os resp = requests.get( - Network accessline 187
import requests, csv, io, os resp = requests.get( "https://www.alphavantage.co/query", - Network accessline 188
resp = requests.get( - Network accessline 189
"https://www.alphavantage.co/query", - Access to secretsline 190
[Credential-related source omitted] - Network accessline 202
# Returns CSV resp = requests.get( - Network accessline 203
resp = requests.get( - Network accessline 204
"https://www.alphavantage.co/query", - Access to secretsline 205
[Credential-related source omitted] - Network accessline 215
# Returns CSV resp = requests.get( - Network accessline 216
resp = requests.get( - Network accessline 217
"https://www.alphavantage.co/query", - Access to secretsline 218
[Credential-related source omitted]
bundled/skills/alpha-vantage/references/time-series.md
- Network accessline 3
Base URL: `https://www.alphavantage.co/query`
bundled/skills/architecture-patterns/SKILL.md
bundled/skills/astropy/SKILL.md
bundled/skills/astropy/references/wcs_and_other_modules.md
bundled/skills/autonomous-builder/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 363
1. mcp__puppeteer_navigate → "https://myapp.com" - Instruction override signalline 424
# Start/resume Claude session with permission bypass for unattended operation # WARNING: --dangerously-skip-permissions bypasses all user confirmations - Instruction override signalline 425
# WARNING: --dangerously-skip-permissions bypasses all user confirmations - Instruction override signalline 427
claude --skill autonomous-builder --project "$PROJECT_DIR" --dangerously-skip-permissions - Instruction override signalline 437
**⚠<U+FE0F> Security Warning:** `--dangerously-skip-permissions` bypasses ALL user confirmations. Use only in trusted, isolated environments. Ensure workspace isolation and safety protocols are properly configured. - Dangerous shell operationline 716
| Destructive operations | `rm -rf`, `format`, `DROP DATABASE` | STOP, show impact, get approval | - Dangerous shell operationline 973
sudo apt install gh
bundled/skills/autonomous-builder/assets/auto-continue.ps1
- Executable scriptline 1
Executable file - Instruction override signalline 220
# Run Claude with auto-continue # Note: --dangerously-skip-permissions enables unattended operation - Instruction override signalline 221
# Note: --dangerously-skip-permissions enables unattended operation - Instruction override signalline 223
try { $process = Start-Process -FilePath "claude" ` -ArgumentList "--skill", "autonomous-builder", "--project", $ProjectDir, "--dangerously-skip-permissions" ` - Instruction override signalline 224
$process = Start-Process -FilePath "claude" -ArgumentList "--skill", "autonomous-builder", "--project", $ProjectDir, "--dangerously-skip-permissions" - Instruction override signalline 225
-ArgumentList "--skill", "autonomous-builder", "--project", $ProjectDir, "--dangerously-skip-permissions" `
bundled/skills/autonomous-builder/assets/auto-continue.sh
bundled/skills/autonomous-builder/references/github-integration.md
- Dangerous shell operationline 28
sudo apt install gh - Dangerous shell operationline 31
sudo dnf install gh - Network accessline 48
1. **Repository URL Prompt**: - You'll be prompted: "GitHub repository URL (leave empty to skip):" - Provide URL in format: `https://github.com/owner/repo` - Network accessline 49
- You'll be prompted: "GitHub repository URL (leave empty to skip):" - Provide URL in format: `https://github.com/owner/repo` - Or leave empty to skip GitHub integration - Network accessline 50
- Provide URL in format: `https://github.com/owner/repo` - Dangerous shell operationline 385
rm .builder/state.json.tmp - Network accessline 402
# Option 2: Via GitHub web UI, then: git remote add origin https://github.com/owner/repo.git - Network accessline 403
git remote add origin https://github.com/owner/repo.git - Network accessline 451
def extract_repo_info(url): """Extract owner and repo name from GitHub URL""" # https://github.com/owner/repo or git@github.com:owner/repo.git - Network accessline 452
"""Extract owner and repo name from GitHub URL""" # https://github.com/owner/repo or git@github.com:owner/repo.git if url.startswith('https://'): - Network accessline 453
# https://github.com/owner/repo or git@github.com:owner/repo.git - Network accessline 522
# Store issue number feature['github_issue'] = int(issue_number) feature['github_issue_url'] = f"https://github.com/{owner}/{repo_name}/issues/{issue_number}" - Network accessline 523
feature['github_issue'] = int(issue_number) feature['github_issue_url'] = f"https://github.com/{owner}/{repo_name}/issues/{issue_number}" feature['github_issue_state'] = 'open' - Network accessline 524
feature['github_issue_url'] = f"https://github.com/{owner}/{repo_name}/issues/{issue_number}" - Network accessline 544
if len(sys.argv) != 2: print("Usage: python migrate_to_github.py <github-repo-url>") print("Example: python migrate_to_github.py https://github.com/owner/repo") - Network accessline 545
print("Usage: python migrate_to_github.py <github-repo-url>") print("Example: python migrate_to_github.py https://github.com/owner/repo") sys.exit(1) - Network accessline 546
print("Example: python migrate_to_github.py https://github.com/owner/repo") - Network accessline 584
"github": { "enabled": true, "repository_url": "https://github.com/owner/repo", - Network accessline 585
"enabled": true, "repository_url": "https://github.com/owner/repo", "repository_owner": "owner", - Network accessline 586
"repository_url": "https://github.com/owner/repo", - Network accessline 626
"name": "Feature Name", "github_issue": 123, "github_issue_url": "https://github.com/owner/repo/issues/123", - Network accessline 627
"github_issue": 123, "github_issue_url": "https://github.com/owner/repo/issues/123", "github_issue_state": "closed", - Network accessline 628
"github_issue_url": "https://github.com/owner/repo/issues/123", - Network accessline 699
- [GitHub CLI Documentation](https://cli.github.com/manual/) - Network accessline 700
- [Git Tagging](https://git-scm.com/book/en/v2/Git-Basics-Tagging) - Network accessline 701
- [Conventional Commits](https://www.conventionalcommits.org/) - Network accessline 702
- [GitHub Issues](https://docs.github.com/en/issues) - Network accessline 703
- [GitHub Releases](https://docs.github.com/en/repositories/releasing-projects-on-github)
bundled/skills/autonomous-builder/references/mcp-auto-integration.md
- Network accessline 134
1. NAVIGATE to target URL Tool: mcp__puppeteer_navigate Args: {"url": "https://example.com"} - Network accessline 136
Args: {"url": "https://example.com"} - Network accessline 318
{ "tool": "mcp__puppeteer_navigate", "args": {"url": "https://example.com"}, - Network accessline 319
"tool": "mcp__puppeteer_navigate", "args": {"url": "https://example.com"}, "timestamp": "2026-02-13T10:30:00Z", - Network accessline 320
"args": {"url": "https://example.com"}, - Network accessline 449
1. Navigate to API endpoint or frontend mcp__puppeteer_navigate → "https://api.example.com/docs" - Network accessline 450
mcp__puppeteer_navigate → "https://api.example.com/docs" - Network accessline 452
2. Execute API call in console mcp__puppeteer_evaluate → ` fetch('/api/users', {method: 'GET'}) - Network accessline 453
mcp__puppeteer_evaluate → ` fetch('/api/users', {method: 'GET'}) .then(r => r.json()) - Network accessline 454
fetch('/api/users', {method: 'GET'})
bundled/skills/autonomous-builder/references/mcp-integration.md
- Network accessline 21
## E2E Login Test 1. Navigate: mcp__puppeteer_navigate("http://localhost:3000/login") - Network accessline 22
1. Navigate: mcp__puppeteer_navigate("http://localhost:3000/login") - Network accessline 207
// 1. Navigate to registration page await mcp__puppeteer_navigate("http://localhost:3000/register"); - Network accessline 208
await mcp__puppeteer_navigate("http://localhost:3000/register"); - Network accessline 230
// Create await mcp__puppeteer_navigate("http://localhost:3000/items/new"); - Network accessline 231
await mcp__puppeteer_navigate("http://localhost:3000/items/new"); - Network accessline 236
// Read await mcp__puppeteer_navigate("http://localhost:3000/items"); - Network accessline 237
await mcp__puppeteer_navigate("http://localhost:3000/items");
bundled/skills/autonomous-builder/references/multi-layer-security.md
- Access to secretsline 74
[Credential-related source omitted] - Access to secretsline 133
[Credential-related source omitted] - Dangerous shell operationline 200
"""Validate rm command safety.""" - Dangerous shell operationline 203
r"rm\s+-rf\s+/", # rm -rf / - Dangerous shell operationline 204
r"rm\s+-rf\s+~", # rm -rf ~ - Dangerous shell operationline 205
r"rm\s+-rf\s+\.\.", # rm -rf .. - Dangerous shell operationline 206
r"rm\s+-rf\s+\*", # rm -rf * - Dangerous shell operationline 207
[Credential-related source omitted] - Access to secretsline 207
[Credential-related source omitted] - Dangerous shell operationline 208
r"rm\s+.*\.gnupg", # rm ~/.gnupg - Dangerous shell operationline 213
return False, f"Dangerous rm pattern detected: {pattern}" - Dangerous shell operationline 216
return True, "rm command validated" - Network accessline 255
def validate_curl_command(command: str) -> Tuple[bool, str]: """Validate curl for security.""" - Network accessline 256
"""Validate curl for security.""" - Access to secretsline 260
[Credential-related source omitted] - Network accessline 266
for pattern in blocked_patterns: if re.search(pattern, command): return False, f"Blocked curl pattern: {pattern}" - Network accessline 268
return False, f"Blocked curl pattern: {pattern}" - Network accessline 270
return True, "curl validated" - Access to secretsline 384
[Credential-related source omitted] - Dangerous shell operationline 444
"patterns": ["rm -rf", "DROP", "DELETE", "TRUNCATE"], - Instruction override signalline 473
In autonomous mode (--dangerously-skip-permissions), this is bypassed. - Dangerous shell operationline 501
"input": {"command": "rm -rf /"}, - Dangerous shell operationline 502
"reason": "Dangerous rm pattern detected",
bundled/skills/autonomous-builder/references/safety-protocols.md
bundled/skills/biopython/SKILL.md
- Access to secretsline 58
[Credential-related source omitted] - Network accessline 408
- **Official Documentation**: https://biopython.org/docs/latest/ - Network accessline 409
- **Tutorial**: https://biopython.org/docs/latest/Tutorial/ - Network accessline 410
- **Cookbook**: https://biopython.org/docs/latest/Tutorial/ (advanced examples) - Network accessline 411
- **GitHub**: https://github.com/biopython/biopython
bundled/skills/biopython/references/databases.md
bundled/skills/cancel-ralph/scripts/cancel-ralph.ps1
- Executable scriptline 1
Executable file
bundled/skills/chembl-database/SKILL.md
- Network accessline 382
- ChEMBL website: https://www.ebi.ac.uk/chembl/ - Network accessline 383
- API documentation: https://www.ebi.ac.uk/chembl/api/data/docs - Network accessline 384
- Python client GitHub: https://github.com/chembl/chembl_webresource_client - Network accessline 385
- Interface documentation: https://chembl.gitbook.io/chembl-interface-documentation/ - Network accessline 386
- Example notebooks: https://github.com/chembl/notebooks
bundled/skills/chembl-database/references/api_reference.md
- Network accessline 269
- Official API documentation: https://www.ebi.ac.uk/chembl/api/data/docs - Network accessline 270
- Python client GitHub: https://github.com/chembl/chembl_webresource_client - Network accessline 271
- ChEMBL interface docs: https://chembl.gitbook.io/chembl-interface-documentation/ - Network accessline 272
- Example notebooks: https://github.com/chembl/notebooks
bundled/skills/chembl-database/scripts/example_queries.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/citation-management/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 142
# Extract from URL python scripts/extract_metadata.py --url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 143
python scripts/extract_metadata.py --url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 480
1. **Find MeSH terms** at https://meshb.nlm.nih.gov/search - Network accessline 604
# From URL python scripts/extract_metadata.py \ --url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 605
python scripts/extract_metadata.py --url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 606
--url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 997
**Search Engines**: - Google Scholar: https://scholar.google.com/ - Network accessline 998
- Google Scholar: https://scholar.google.com/ - Network accessline 999
- PubMed: https://pubmed.ncbi.nlm.nih.gov/ - Network accessline 1000
- PubMed Advanced Search: https://pubmed.ncbi.nlm.nih.gov/advanced/ - Network accessline 1002
**Metadata APIs**: - CrossRef API: https://api.crossref.org/ - Network accessline 1003
- CrossRef API: https://api.crossref.org/ - Network accessline 1004
- PubMed E-utilities: https://www.ncbi.nlm.nih.gov/books/NBK25501/ - Network accessline 1005
- arXiv API: https://arxiv.org/help/api/ - Network accessline 1006
- DataCite API: https://api.datacite.org/ - Network accessline 1008
**Tools and Validators**: - MeSH Browser: https://meshb.nlm.nih.gov/search - Network accessline 1009
- MeSH Browser: https://meshb.nlm.nih.gov/search - Network accessline 1010
- DOI Resolver: https://doi.org/ - Network accessline 1011
- BibTeX Format: http://www.bibtex.org/Format/ - Network accessline 1013
**Citation Styles**: - BibTeX documentation: http://www.bibtex.org/ - Network accessline 1014
- BibTeX documentation: http://www.bibtex.org/ - Network accessline 1015
- LaTeX bibliography management: https://www.overleaf.com/learn/latex/Bibliography_management
bundled/skills/citation-management/assets/bibtex_template.bib
- Network accessline 85
pages = {5998--6008}, address = {Long Beach, CA}, url = {https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html} - Network accessline 86
address = {Long Beach, CA}, url = {https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html} } - Network accessline 87
url = {https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html} - Network accessline 185
year = {2021}, howpublished = {Database}, url = {https://alphafold.ebi.ac.uk/}, - Network accessline 186
howpublished = {Database}, url = {https://alphafold.ebi.ac.uk/}, doi = {10.1093/nar/gkab1061}, - Network accessline 187
url = {https://alphafold.ebi.ac.uk/}, - Network accessline 199
year = {2010}, howpublished = {Software}, url = {https://pandas.pydata.org/}, - Network accessline 200
howpublished = {Software}, url = {https://pandas.pydata.org/}, note = {Python Data Analysis Library} - Network accessline 201
url = {https://pandas.pydata.org/}, - Network accessline 212
year = {2024}, howpublished = {Website}, url = {https://pubmed.ncbi.nlm.nih.gov/}, - Network accessline 213
howpublished = {Website}, url = {https://pubmed.ncbi.nlm.nih.gov/}, note = {Accessed: 2024-01-15} - Network accessline 214
url = {https://pubmed.ncbi.nlm.nih.gov/},
bundled/skills/citation-management/assets/citation_checklist.md
- Network accessline 26
- [ ] All DOIs are properly formatted (10.XXXX/...) - [ ] DOIs resolve correctly to the article - [ ] No DOI prefix in the BibTeX field (no "doi:" or "https://doi.org/") - Network accessline 27
- [ ] DOIs resolve correctly to the article - [ ] No DOI prefix in the BibTeX field (no "doi:" or "https://doi.org/") - [ ] Metadata from CrossRef matches your BibTeX entry - Network accessline 28
- [ ] No DOI prefix in the BibTeX field (no "doi:" or "https://doi.org/") - Network accessline 146
- [ ] Ampersands in author lists (Smith & Jones → Smith and Jones) - [ ] Unprotected acronyms in titles (DNA → {DNA}) - [ ] DOI includes URL prefix (https://doi.org/10.xxx → 10.xxx) - Network accessline 148
- [ ] DOI includes URL prefix (https://doi.org/10.xxx → 10.xxx) - Network accessline 251
# Find correct DOI # Option 1: Search CrossRef # https://www.crossref.org/ - Network accessline 253
# https://www.crossref.org/
bundled/skills/citation-management/references/bibtex_formatting.md
- Network accessline 315
year = {2024}, howpublished = {GitHub}, url = {https://github.com/user/repo}, - Network accessline 316
howpublished = {GitHub}, url = {https://github.com/user/repo}, note = {Version 2.0} - Network accessline 317
url = {https://github.com/user/repo}, - Network accessline 388
author = {{Organization Name}}, title = {Page Title}, url = {https://example.com/page}, - Network accessline 389
title = {Page Title}, url = {https://example.com/page}, year = {2024}, - Network accessline 390
url = {https://example.com/page}, - Network accessline 589
doi = {https://doi.org/10.1038/s41586-021-03819-2} % Don't include URL - Network accessline 600
url = {https://www.example.com/article} - Network accessline 610
% Don't include both if DOI URL is same as url doi = {10.1038/nature12345} url = {https://doi.org/10.1038/nature12345} % Redundant! - Network accessline 612
url = {https://doi.org/10.1038/nature12345} % Redundant! - Network accessline 805
doi = {https://doi.org/10.1038/nature12345} - Network accessline 883
year = {2021}, howpublished = {Database}, url = {https://alphafold.ebi.ac.uk/}, - Network accessline 884
howpublished = {Database}, url = {https://alphafold.ebi.ac.uk/}, doi = {10.1093/nar/gkab1061} - Network accessline 885
url = {https://alphafold.ebi.ac.uk/},
bundled/skills/citation-management/references/citation_validation.md
- Network accessline 37
**DOI resolution**: - DOI should resolve via https://doi.org/ - Network accessline 38
- DOI should resolve via https://doi.org/ - Network accessline 50
**Manual check**: 1. Copy DOI from BibTeX 2. Visit https://doi.org/10.1038/nature12345 - Network accessline 51
1. Copy DOI from BibTeX 2. Visit https://doi.org/10.1038/nature12345 3. Verify it redirects to correct article - Network accessline 52
2. Visit https://doi.org/10.1038/nature12345 - Network accessline 294
url = {https://www.nature.com/articles/nature12345} - Network accessline 295
url = {https://arxiv.org/abs/2103.14030} - Network accessline 300
url = {http://...} % HTTP instead of HTTPS
bundled/skills/citation-management/references/metadata_extraction.md
- Network accessline 121
**Base URL**: `https://api.crossref.org/works/` - Network accessline 132
GET https://api.crossref.org/works/10.1038/s41586-021-03819-2 - Network accessline 195
**Base URL**: `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/` - Network accessline 206
GET https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi? - Access to secretsline 210
[Credential-related source omitted] - Network accessline 282
**Base URL**: `http://export.arxiv.org/api/query` - Network accessline 290
GET http://export.arxiv.org/api/query?id_list=2103.14030 - Network accessline 296
<entry> <id>http://arxiv.org/abs/2103.14030v2</id> - Network accessline 297
<id>http://arxiv.org/abs/2103.14030v2</id> - Network accessline 303
<summary>Abstract text here...</summary> <arxiv:doi>10.1038/s41586-021-03819-2</arxiv:doi> <category term="q-bio.BM" scheme="http://arxiv.org/schemas/atom"/> - Network accessline 304
<arxiv:doi>10.1038/s41586-021-03819-2</arxiv:doi> <category term="q-bio.BM" scheme="http://arxiv.org/schemas/atom"/> <category term="cs.LG" scheme="http://arxiv.org/schemas/atom"/> - Network accessline 305
<category term="q-bio.BM" scheme="http://arxiv.org/schemas/atom"/> - Network accessline 306
<category term="cs.LG" scheme="http://arxiv.org/schemas/atom"/> - Network accessline 334
**Base URL**: `https://api.datacite.org/dois/` - Network accessline 340
GET https://api.datacite.org/dois/10.5281/zenodo.1234567 - Network accessline 515
year = {2021}, howpublished = {Software}, url = {https://alphafold.ebi.ac.uk/}, - Network accessline 516
howpublished = {Software}, url = {https://alphafold.ebi.ac.uk/}, doi = {10.5281/zenodo.5123456} - Network accessline 517
url = {https://alphafold.ebi.ac.uk/}, - Network accessline 593
python scripts/extract_metadata.py \ --url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 594
--url "https://www.nature.com/articles/s41586-021-03819-2" - Network accessline 606
# DOI URLs https://doi.org/10.1038/nature12345 - Network accessline 607
https://doi.org/10.1038/nature12345 - Network accessline 608
https://dx.doi.org/10.1126/science.abc123 - Network accessline 609
https://www.nature.com/articles/s41586-021-03819-2 - Network accessline 611
# PubMed URLs https://pubmed.ncbi.nlm.nih.gov/34265844/ - Network accessline 612
https://pubmed.ncbi.nlm.nih.gov/34265844/ - Network accessline 613
https://www.ncbi.nlm.nih.gov/pubmed/34265844 - Network accessline 615
# arXiv URLs https://arxiv.org/abs/2103.14030 - Network accessline 616
https://arxiv.org/abs/2103.14030 - Network accessline 617
https://arxiv.org/pdf/2103.14030.pdf - Network accessline 628
# 34265844 # 2103.14030 # https://doi.org/10.1126/science.abc123 - Network accessline 630
# https://doi.org/10.1126/science.abc123 - Network accessline 727
volume = {123}, pages = {45--67}, url = {https://stable-url-here}, - Network accessline 728
pages = {45--67}, url = {https://stable-url-here}, note = {PMID: 12345678} - Network accessline 729
url = {https://stable-url-here},
bundled/skills/citation-management/references/pubmed_search.md
- Network accessline 58
**MeSH Browser**: https://meshb.nlm.nih.gov/search - Network accessline 261
**Access**: https://pubmed.ncbi.nlm.nih.gov/advanced/ - Network accessline 348
**Base URL**: `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/` - Network accessline 362
**Get API key**: https://www.ncbi.nlm.nih.gov/account/ - Access to secretsline 376
[Credential-related source omitted] - Network accessline 380
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi? - Access to secretsline 385
[Credential-related source omitted] - Access to secretsline 410
[Credential-related source omitted] - Network accessline 414
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi? - Access to secretsline 418
[Credential-related source omitted] - Network accessline 438
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi? - Access to secretsline 442
[Credential-related source omitted] - Network accessline 453
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi? - Network accessline 486
**Get API key**: 1. Create NCBI account: https://www.ncbi.nlm.nih.gov/account/ - Network accessline 487
1. Create NCBI account: https://www.ncbi.nlm.nih.gov/account/ - Access to secretsline 494
[Credential-related source omitted] - Access to secretsline 500
[Credential-related source omitted] - Access to secretsline 504
[Credential-related source omitted]
bundled/skills/citation-management/scripts/doi_to_bibtex.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 17
def __init__(self): self.session = requests.Session() - Network accessline 18
self.session = requests.Session() - Network accessline 34
doi = doi.strip() if doi.startswith('https://doi.org/'): - Network accessline 35
if doi.startswith('https://doi.org/'): - Network accessline 36
doi = doi.replace('https://doi.org/', '') - Network accessline 37
elif doi.startswith('http://doi.org/'): - Network accessline 38
doi = doi.replace('http://doi.org/', '') - Network accessline 43
url = f'https://doi.org/{doi}'
bundled/skills/citation-management/scripts/extract_metadata.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 28
self.session = requests.Session() - Network accessline 108
url = f'https://api.crossref.org/works/{doi}' - Network accessline 127
'pages': message.get('page', ''), 'publisher': message.get('publisher', ''), 'url': f'https://doi.org/{doi}' - Network accessline 128
'publisher': message.get('publisher', ''), 'url': f'https://doi.org/{doi}' } - Network accessline 129
'url': f'https://doi.org/{doi}' - Network accessline 151
url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi' - Access to secretsline 162
[Credential-related source omitted] - Access to secretsline 163
[Credential-related source omitted] - Access to secretsline 164
[Credential-related source omitted] - Network accessline 223
url = 'http://export.arxiv.org/api/query' - Network accessline 234
root = ET.fromstring(response.content) ns = {'atom': 'http://www.w3.org/2005/Atom', 'arxiv': 'http://arxiv.org/schemas/atom'} - Network accessline 235
ns = {'atom': 'http://www.w3.org/2005/Atom', 'arxiv': 'http://arxiv.org/schemas/atom'} - Network accessline 269
'journal_ref': journal_ref, 'abstract': entry.findtext('atom:summary', '', ns).strip().replace('\n', ' '), 'url': f'https://arxiv.org/abs/{arxiv_id}' - Network accessline 270
'abstract': entry.findtext('atom:summary', '', ns).strip().replace('\n', ' '), 'url': f'https://arxiv.org/abs/{arxiv_id}' } - Network accessline 271
'url': f'https://arxiv.org/abs/{arxiv_id}'
bundled/skills/citation-management/scripts/format_bibtex.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 147
if 'doi' in fields: doi = fields['doi'] doi = doi.replace('https://doi.org/', '') - Network accessline 148
doi = fields['doi'] doi = doi.replace('https://doi.org/', '') doi = doi.replace('http://doi.org/', '') - Network accessline 149
doi = doi.replace('https://doi.org/', '') - Network accessline 150
doi = doi.replace('http://doi.org/', '')
bundled/skills/citation-management/scripts/search_google_scholar.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/citation-management/scripts/search_pubmed.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 20
[Credential-related source omitted] - Access to secretsline 25
[Credential-related source omitted] - Network accessline 28
[Credential-related source omitted] - Access to secretsline 28
[Credential-related source omitted] - Network accessline 29
self.email = email or os.getenv('NCBI_EMAIL', '') self.base_url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/' self.session = requests.Session() - Network accessline 30
self.base_url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/' - Network accessline 31
self.session = requests.Session() - Access to secretsline 34
[Credential-related source omitted] - Access to secretsline 79
[Credential-related source omitted] - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 129
[Credential-related source omitted] - Access to secretsline 130
[Credential-related source omitted] - Access to secretsline 329
[Credential-related source omitted] - Access to secretsline 360
[Credential-related source omitted]
bundled/skills/citation-management/scripts/validate_citations.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 18
def __init__(self): self.session = requests.Session() - Network accessline 19
self.session = requests.Session() - Network accessline 211
try: url = f'https://doi.org/{doi}' - Network accessline 212
url = f'https://doi.org/{doi}' - Network accessline 217
crossref_url = f'https://api.crossref.org/works/{doi}'
bundled/skills/claude-skills/SKILL.md
- Network accessline 233
External (official): - https://support.claude.com/en/articles/12512176-what-are-skills - Network accessline 234
- https://support.claude.com/en/articles/12512176-what-are-skills - Network accessline 235
- https://support.claude.com/en/articles/12512180-using-skills-in-claude - Network accessline 236
- https://support.claude.com/en/articles/12512198-creating-custom-skills - Network accessline 237
- https://docs.claude.com/en/api/skills-guide
bundled/skills/claude-skills/references/README.md
- Network accessline 4
For more information, check out: - [What are skills?](https://support.claude.com/en/articles/12512176-what-are-skills) - Network accessline 5
- [What are skills?](https://support.claude.com/en/articles/12512176-what-are-skills) - Network accessline 6
- [Using skills in Claude](https://support.claude.com/en/articles/12512180-using-skills-in-claude) - Network accessline 7
- [How to create custom skills](https://support.claude.com/en/articles/12512198-creating-custom-skills) - Network accessline 8
- [Equipping agents for the real world with Agent Skills](https://anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills) - Network accessline 16
The example skills in this repo are open source (Apache 2.0). We've also included the document creation & editing skills that power [Claude's document capabilities](https://www.anthropic.com/news/create-files) under the hood in the [`skills - Network accessline 84
To use any skill from this repository or upload custom skills, follow the instructions in [Using skills in Claude](https://support.claude.com/en/articles/12512180-using-skills-in-claude#h_a4222fa77b). - Network accessline 88
You can use Anthropic's pre-built skills, and upload custom skills, via the Claude API. See the [Skills API Quickstart](https://docs.claude.com/en/api/skills-guide#creating-a-skill) for more. - Network accessline 117
The markdown content below contains the instructions, examples, and guidelines that Claude will follow. For more details, see [How to create custom skills](https://support.claude.com/en/articles/12512198-creating-custom-skills). - Network accessline 123
- **Notion** - [Notion Skills for Claude](https://www.notion.so/notiondevs/Notion-Skills-for-Claude-28da4445d27180c7af1df7d8615723d0)
bundled/skills/claude-skills/references/index.md
- Network accessline 21
- What are skills? https://support.claude.com/en/articles/12512176-what-are-skills - Network accessline 22
- Using skills in Claude https://support.claude.com/en/articles/12512180-using-skills-in-claude - Network accessline 23
- Creating custom skills https://support.claude.com/en/articles/12512198-creating-custom-skills - Network accessline 24
- Skills API Quickstart https://docs.claude.com/en/api/skills-guide - Network accessline 25
- Anthropic Skills GitHub https://github.com/anthropics/skills - Network accessline 26
- Engineering blog: Agent Skills https://anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills
bundled/skills/claude-skills/scripts/create-skill.sh
- Executable scriptline 1
#!/usr/bin/env bash
bundled/skills/claude-skills/scripts/validate-skill.sh
bundled/skills/clinical-decision-support/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/clinical-decision-support/scripts/biomarker_classifier.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-decision-support/scripts/build_decision_tree.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-decision-support/scripts/create_cohort_tables.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-decision-support/scripts/generate_survival_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-decision-support/scripts/validate_cds_document.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/clinical-reports/references/README.md
- Network accessline 210
### External Standards - CARE Guidelines: https://www.care-statement.org/ - Network accessline 211
- CARE Guidelines: https://www.care-statement.org/ - Network accessline 212
- ICH-E3 Guideline: https://database.ich.org/sites/default/files/E3_Guideline.pdf - Network accessline 213
- CONSORT Statement: http://www.consort-statement.org/ - Network accessline 214
- HIPAA: https://www.hhs.gov/hipaa/ - Network accessline 215
- ACR Practice Parameters: https://www.acr.org/Clinical-Resources/Practice-Parameters-and-Technical-Standards - Network accessline 216
- CAP Cancer Protocols: https://www.cap.org/protocols-and-guidelines
bundled/skills/clinical-reports/references/case_report_guidelines.md
- Network accessline 562
- CARE website: https://www.care-statement.org/
bundled/skills/clinical-reports/references/patient_documentation.md
- Network accessline 461
Vitals: T 98.2°F, BP 142/88, HR 105, RR 24, SpO2 88% on room air → 95% on 2L NC Height: 5'10", Weight: 195 lbs (baseline 187 lbs), BMI 28
bundled/skills/clinical-reports/scripts/check_deidentification.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/compliance_checker.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/extract_clinical_data.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/format_adverse_events.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/generate_report_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/terminology_validator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/validate_case_report.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinical-reports/scripts/validate_trial_report.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/clinicaltrials-database/SKILL.md
- Network accessline 44
url = "https://clinicaltrials.gov/api/v2/studies" - Network accessline 51
response = requests.get(url, params=params) - Network accessline 64
nct_id = "NCT04852770" url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}" - Network accessline 65
url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}" - Network accessline 67
response = requests.get(url) - Network accessline 433
def search_with_rate_limit(params): try: response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 434
try: response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) response.raise_for_status() - Network accessline 435
response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 465
try: response = requests.get(url, params=params, timeout=30) - Network accessline 466
response = requests.get(url, params=params, timeout=30) - Network accessline 494
- **Base URL**: `https://clinicaltrials.gov/api/v2` - **Authentication**: Not required (public API) - **Rate Limit**: ~50 requests/minute per IP
bundled/skills/clinicaltrials-database/references/api_reference.md
- Network accessline 7
**Base URL:** `https://clinicaltrials.gov/api/v2` - Network accessline 69
curl "https://clinicaltrials.gov/api/v2/studies?query.cond=lung+cancer&filter.overallStatus=RECRUITING&pageSize=10&format=json" - Network accessline 107
curl "https://clinicaltrials.gov/api/v2/studies/NCT04852770?format=json" - Network accessline 160
url = "https://clinicaltrials.gov/api/v2/studies" - Network accessline 168
response = requests.get(url, params=params) - Network accessline 189
response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 203
response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 211
nct_id = "NCT04852770" url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}" - Network accessline 212
url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}" - Network accessline 214
response = requests.get(url) - Network accessline 238
response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 262
response = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params) - Network accessline 298
for attempt in range(max_retries): try: response = requests.get( - Network accessline 299
try: response = requests.get( "https://clinicaltrials.gov/api/v2/studies", - Network accessline 300
response = requests.get( - Network accessline 301
"https://clinicaltrials.gov/api/v2/studies", - Network accessline 358
For detailed migration guidance, see: https://clinicaltrials.gov/data-api/about-api/api-migration
bundled/skills/clinicaltrials-database/scripts/query_clinicaltrials.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 9
API Documentation: https://clinicaltrials.gov/data-api/api - Network accessline 19
BASE_URL = "https://clinicaltrials.gov/api/v2" - Network accessline 86
url = f"{BASE_URL}/studies" response = requests.get(url, params=params) - Network accessline 87
response = requests.get(url, params=params) - Network accessline 110
response = requests.get(url, params=params)
bundled/skills/clinpgx-database/SKILL.md
- Network accessline 43
BASE_URL = "https://api.clinpgx.org/v1/" - Network accessline 65
# Get gene details response = requests.get("https://api.clinpgx.org/v1/gene/CYP2D6") - Network accessline 66
response = requests.get("https://api.clinpgx.org/v1/gene/CYP2D6") - Network accessline 69
# Search for genes by name response = requests.get("https://api.clinpgx.org/v1/gene", - Network accessline 70
response = requests.get("https://api.clinpgx.org/v1/gene", - Network accessline 87
# Get drug details response = requests.get("https://api.clinpgx.org/v1/chemical/PA448515") # Warfarin - Network accessline 88
response = requests.get("https://api.clinpgx.org/v1/chemical/PA448515") # Warfarin - Network accessline 91
# Search drugs by name response = requests.get("https://api.clinpgx.org/v1/chemical", - Network accessline 92
response = requests.get("https://api.clinpgx.org/v1/chemical", - Network accessline 111
# Get gene-drug pair information response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 112
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 116
# Get all pairs for a gene response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 117
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 133
# Get CPIC guideline response = requests.get("https://api.clinpgx.org/v1/guideline/PA166104939") - Network accessline 134
response = requests.get("https://api.clinpgx.org/v1/guideline/PA166104939") - Network accessline 137
# List all CPIC guidelines response = requests.get("https://api.clinpgx.org/v1/guideline", - Network accessline 138
response = requests.get("https://api.clinpgx.org/v1/guideline", - Network accessline 163
# Get allele information response = requests.get("https://api.clinpgx.org/v1/allele/CYP2D6*4") - Network accessline 164
response = requests.get("https://api.clinpgx.org/v1/allele/CYP2D6*4") - Network accessline 167
# Get all alleles for a gene response = requests.get("https://api.clinpgx.org/v1/allele", - Network accessline 168
response = requests.get("https://api.clinpgx.org/v1/allele", - Network accessline 191
# Get variant information response = requests.get("https://api.clinpgx.org/v1/variant/rs4244285") - Network accessline 192
response = requests.get("https://api.clinpgx.org/v1/variant/rs4244285") - Network accessline 195
# Search variants by position (if supported) response = requests.get("https://api.clinpgx.org/v1/variant", - Network accessline 196
response = requests.get("https://api.clinpgx.org/v1/variant", - Network accessline 214
# Get clinical annotations response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 215
response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 219
# Filter by evidence level response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 220
response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 238
# Get drug labels with PGx information response = requests.get("https://api.clinpgx.org/v1/drugLabel", - Network accessline 239
response = requests.get("https://api.clinpgx.org/v1/drugLabel", - Network accessline 243
# Filter by regulatory source response = requests.get("https://api.clinpgx.org/v1/drugLabel", - Network accessline 244
response = requests.get("https://api.clinpgx.org/v1/drugLabel", - Network accessline 261
# Get pathway information response = requests.get("https://api.clinpgx.org/v1/pathway/PA146123006") # Warfarin pathway - Network accessline 262
response = requests.get("https://api.clinpgx.org/v1/pathway/PA146123006") # Warfarin pathway - Network accessline 265
# Search pathways by drug response = requests.get("https://api.clinpgx.org/v1/pathway", - Network accessline 266
response = requests.get("https://api.clinpgx.org/v1/pathway", - Network accessline 284
# Example: Patient is CYP2C19 *1/*2 (intermediate metabolizer) response = requests.get("https://api.clinpgx.org/v1/allele/CYP2C19*2") - Network accessline 285
response = requests.get("https://api.clinpgx.org/v1/allele/CYP2C19*2") - Network accessline 291
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 298
response = requests.get("https://api.clinpgx.org/v1/guideline", - Network accessline 306
response = requests.get("https://api.clinpgx.org/v1/drugLabel", - Network accessline 320
all_interactions = {} for gene in pgx_panel: response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 321
for gene in pgx_panel: response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", params={"gene": gene}) - Network accessline 322
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 341
response = requests.get("https://api.clinpgx.org/v1/chemical", - Network accessline 348
response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 367
response = requests.get("https://api.clinpgx.org/v1/allele", - Network accessline 396
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 403
response = requests.get("https://api.clinpgx.org/v1/clinicalAnnotation", - Network accessline 427
def rate_limited_request(url, params=None, delay=0.5): """Make API request with rate limiting (2 req/sec max)""" response = requests.get(url, params=params) - Network accessline 428
"""Make API request with rate limiting (2 req/sec max)""" response = requests.get(url, params=params) time.sleep(delay) # Wait 0.5 seconds between requests - Network accessline 429
response = requests.get(url, params=params) - Network accessline 435
for gene in genes: response = rate_limited_request( "https://api.clinpgx.org/v1/gene/" + gene - Network accessline 436
response = rate_limited_request( "https://api.clinpgx.org/v1/gene/" + gene ) - Network accessline 437
"https://api.clinpgx.org/v1/gene/" + gene - Network accessline 447
for attempt in range(max_retries): try: response = requests.get(url, params=params, timeout=10) - Network accessline 449
response = requests.get(url, params=params, timeout=10) - Network accessline 491
'cyp2d6_cache.json', rate_limited_request, "https://api.clinpgx.org/v1/gene/CYP2D6" - Network accessline 492
rate_limited_request, "https://api.clinpgx.org/v1/gene/CYP2D6" ) - Network accessline 493
"https://api.clinpgx.org/v1/gene/CYP2D6" - Network accessline 508
**Access**: Available at https://www.clinpgx.org/pharmacogenomic-decision-support - Network accessline 573
- ClinPGx continuously updates with new evidence and guidelines - Check publication dates for clinical annotations - Monitor ClinPGx Blog (https://blog.clinpgx.org/) for announcements - Network accessline 574
- Check publication dates for clinical annotations - Monitor ClinPGx Blog (https://blog.clinpgx.org/) for announcements - CPIC guidelines updated as new evidence emerges - Network accessline 575
- Monitor ClinPGx Blog (https://blog.clinpgx.org/) for announcements - Network accessline 594
# Get all CPIC guideline pairs response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 595
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 608
for med in medications: for gene in patient_genes: response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 609
for gene in patient_genes: response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", params={"gene": gene, "drug": med}) - Network accessline 610
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 620
# Check for HLA-B*57:01 before abacavir trial response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 621
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 629
- **ClinPGx website**: https://www.clinpgx.org/ - Network accessline 630
- **ClinPGx Blog**: https://blog.clinpgx.org/ - Network accessline 631
- **API documentation**: https://api.clinpgx.org/ - Network accessline 632
- **CPIC website**: https://cpicpgx.org/ - Network accessline 633
- **PharmCAT**: https://pharmcat.clinpgx.org/ - Network accessline 634
- **ClinGen**: https://clinicalgenome.org/
bundled/skills/clinpgx-database/references/api_reference.md
- Network accessline 8
https://api.clinpgx.org/v1/ - Network accessline 53
curl "https://api.clinpgx.org/v1/gene/CYP2D6" - Network accessline 82
curl "https://api.clinpgx.org/v1/gene?q=CYP" - Network accessline 100
curl "https://api.clinpgx.org/v1/chemical/PA448515" - Network accessline 114
curl "https://api.clinpgx.org/v1/chemical?name=warfarin" - Network accessline 149
# Get all pairs for a gene curl "https://api.clinpgx.org/v1/geneDrugPair?gene=CYP2D6" - Network accessline 150
curl "https://api.clinpgx.org/v1/geneDrugPair?gene=CYP2D6" - Network accessline 152
# Get specific gene-drug pair curl "https://api.clinpgx.org/v1/geneDrugPair?gene=CYP2D6&drug=codeine" - Network accessline 153
curl "https://api.clinpgx.org/v1/geneDrugPair?gene=CYP2D6&drug=codeine" - Network accessline 155
# Get all CPIC Level A pairs curl "https://api.clinpgx.org/v1/geneDrugPair?cpicLevel=A" - Network accessline 156
curl "https://api.clinpgx.org/v1/geneDrugPair?cpicLevel=A" - Network accessline 168
"clinicalAnnotationCount": 45, "hasGuideline": true, "guidelineUrl": "https://www.clinpgx.org/guideline/..." - Network accessline 169
"hasGuideline": true, "guidelineUrl": "https://www.clinpgx.org/guideline/..." } - Network accessline 170
"guidelineUrl": "https://www.clinpgx.org/guideline/..." - Network accessline 192
# Get all CPIC guidelines curl "https://api.clinpgx.org/v1/guideline?source=CPIC" - Network accessline 193
curl "https://api.clinpgx.org/v1/guideline?source=CPIC" - Network accessline 195
# Get guideline for specific gene-drug curl "https://api.clinpgx.org/v1/guideline?gene=CYP2C19&drug=clopidogrel" - Network accessline 196
curl "https://api.clinpgx.org/v1/guideline?gene=CYP2C19&drug=clopidogrel" - Network accessline 207
curl "https://api.clinpgx.org/v1/guideline/PA166104939" - Network accessline 220
"summary": "Alternative antiplatelet therapy recommended for...", "recommendations": [...], "pdfUrl": "https://www.clinpgx.org/...", - Network accessline 221
"recommendations": [...], "pdfUrl": "https://www.clinpgx.org/...", "pmid": "23400754" - Network accessline 222
"pdfUrl": "https://www.clinpgx.org/...", - Network accessline 242
curl "https://api.clinpgx.org/v1/allele?gene=CYP2D6" - Network accessline 290
curl "https://api.clinpgx.org/v1/allele/CYP2D6*4" - Network accessline 308
curl "https://api.clinpgx.org/v1/variant/rs4244285" - Network accessline 343
curl "https://api.clinpgx.org/v1/variant?chromosome=10&position=94781859" - Network accessline 364
# Get all annotations for a gene curl "https://api.clinpgx.org/v1/clinicalAnnotation?gene=CYP2D6" - Network accessline 365
curl "https://api.clinpgx.org/v1/clinicalAnnotation?gene=CYP2D6" - Network accessline 367
# Get high-quality evidence only curl "https://api.clinpgx.org/v1/clinicalAnnotation?evidenceLevel=1A" - Network accessline 368
curl "https://api.clinpgx.org/v1/clinicalAnnotation?evidenceLevel=1A" - Network accessline 370
# Get annotations for specific gene-drug pair curl "https://api.clinpgx.org/v1/clinicalAnnotation?gene=TPMT&drug=azathioprine" - Network accessline 371
curl "https://api.clinpgx.org/v1/clinicalAnnotation?gene=TPMT&drug=azathioprine" - Network accessline 416
# Get all labels for warfarin curl "https://api.clinpgx.org/v1/drugLabel?drug=warfarin" - Network accessline 417
curl "https://api.clinpgx.org/v1/drugLabel?drug=warfarin" - Network accessline 419
# Get only FDA labels curl "https://api.clinpgx.org/v1/drugLabel?drug=warfarin&source=FDA" - Network accessline 420
curl "https://api.clinpgx.org/v1/drugLabel?drug=warfarin&source=FDA" - Network accessline 435
"biomarkers": ["CYP2C9", "VKORC1"], "testingRecommended": true, "labelUrl": "https://dailymed.nlm.nih.gov/...", - Network accessline 436
"testingRecommended": true, "labelUrl": "https://dailymed.nlm.nih.gov/...", "lastUpdated": "2024-01-15" - Network accessline 437
"labelUrl": "https://dailymed.nlm.nih.gov/...", - Network accessline 458
curl "https://api.clinpgx.org/v1/pathway/PA146123006" - Network accessline 473
curl "https://api.clinpgx.org/v1/pathway?drug=warfarin" - Network accessline 482
"genes": ["CYP2C9", "VKORC1", "CYP4F2", "GGCX"], "description": "Warfarin is metabolized primarily by CYP2C9...", "diagramUrl": "https://www.clinpgx.org/pathway/...", - Network accessline 483
"description": "Warfarin is metabolized primarily by CYP2C9...", "diagramUrl": "https://www.clinpgx.org/pathway/...", "steps": [ - Network accessline 484
"diagramUrl": "https://www.clinpgx.org/pathway/...", - Network accessline 519
for med in patient_meds: for gene in patient_genes: response = requests.get( - Network accessline 520
for gene in patient_genes: response = requests.get( "https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 521
response = requests.get( - Network accessline 522
"https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 534
response = requests.get( - Network accessline 535
"https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 549
alleles = requests.get( - Network accessline 550
"https://api.clinpgx.org/v1/allele", - Network accessline 567
# Screen for HLA-B*57:01 before abacavir response = requests.get( - Network accessline 568
response = requests.get( - Network accessline 569
"https://api.clinpgx.org/v1/geneDrugPair", - Network accessline 605
for attempt in range(max_retries): try: response = requests.get(url, params=params, timeout=10) - Network accessline 607
response = requests.get(url, params=params, timeout=10) - Network accessline 664
results = {} for gene in genes: response = requests.get(f"https://api.clinpgx.org/v1/gene/{gene}") - Network accessline 665
for gene in genes: response = requests.get(f"https://api.clinpgx.org/v1/gene/{gene}") if response.status_code == 200: - Network accessline 666
response = requests.get(f"https://api.clinpgx.org/v1/gene/{gene}") - Network accessline 729
- API version: v1 - Stability: Beta - endpoints stable, parameters may change - Monitor: https://blog.clinpgx.org/ for updates - Network accessline 731
- Monitor: https://blog.clinpgx.org/ for updates - Network accessline 733
### Migration from PharmGKB As of July 2025, PharmGKB URLs redirect to ClinPGx. Update references: - Old: `https://api.pharmgkb.org/` - Network accessline 734
As of July 2025, PharmGKB URLs redirect to ClinPGx. Update references: - Old: `https://api.pharmgkb.org/` - New: `https://api.clinpgx.org/` - Network accessline 735
- Old: `https://api.pharmgkb.org/` - Network accessline 736
- New: `https://api.clinpgx.org/` - Network accessline 745
- **API Issues**: api@clinpgx.org - **Documentation**: https://api.clinpgx.org/ - Network accessline 746
- **Documentation**: https://api.clinpgx.org/ - Network accessline 747
- **General Questions**: https://www.clinpgx.org/page/faqs - Network accessline 748
- **Blog**: https://blog.clinpgx.org/ - Network accessline 749
- **CPIC Guidelines**: https://cpicpgx.org/
bundled/skills/clinpgx-database/scripts/query_clinpgx.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 8
ClinPGx API: https://api.clinpgx.org/ - Network accessline 20
BASE_URL = "https://api.clinpgx.org/v1/" RATE_LIMIT_DELAY = 0.5 # 500ms delay = 2 requests/second - Network accessline 36
response = requests.get(url, params=params) - Network accessline 53
for attempt in range(max_retries): try: response = requests.get(url, params=params, timeout=10) - Network accessline 55
response = requests.get(url, params=params, timeout=10)
bundled/skills/code-reviewer/SKILL.md
- Access to secretsline 150
[Credential-related source omitted]
bundled/skills/code-reviewer/references/python-style-guide.md
bundled/skills/code-reviewer/scripts/check_style.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/code-reviewer/scripts/code_quality_checker.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/code-reviewer/scripts/pr_analyzer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/code-reviewer/scripts/review_report_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/coding-tutor/scripts/create_tutorial.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/coding-tutor/scripts/index_tutorials.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/coding-tutor/scripts/quiz_priority.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/coding-tutor/scripts/setup_tutorials.py
bundled/skills/commit-with-reflection/examples/feature-example.md
- Network accessline 76
Access to fetch at 'http://localhost:5000/api/auth/login' from origin - Network accessline 77
'http://localhost:3000' has been blocked by CORS policy: Response to - Network accessline 89
import cors from 'cors'; app.use(cors({ origin: 'http://localhost:3000', - Network accessline 90
app.use(cors({ origin: 'http://localhost:3000', credentials: true - Network accessline 91
origin: 'http://localhost:3000', - Access to secretsline 114
[Credential-related source omitted] - Access to secretsline 351
[Credential-related source omitted] - Network accessline 480
**测试 6: CORS跨域请求** - 输入: 从 `http://localhost:3000` 发送请求到 `http://localhost:5000` - Network accessline 481
- 输入: 从 `http://localhost:3000` 发送请求到 `http://localhost:5000` - Network accessline 502
# 访问登录页面 # http://localhost:3000/login - Network accessline 503
# http://localhost:3000/login - Network accessline 514
# 访问受保护的API # http://localhost:3000/api/user/profile - Network accessline 515
# http://localhost:3000/api/user/profile - Network accessline 588
### 外部资源 - [TypeScript Handbook - Interfaces](https://www.typescriptlang.org/docs/handbook/interfaces.html) - Network accessline 589
- [TypeScript Handbook - Interfaces](https://www.typescriptlang.org/docs/handbook/interfaces.html) - Network accessline 590
- [JWT Introduction](https://jwt.io/introduction) - Network accessline 591
- [JWT Best Practices (RFC 8725)](https://tools.ietf.org/html/rfc8725) - Network accessline 592
- [Express CORS Middleware](https://expressjs.com/en/resources/middleware/cors.html) - Network accessline 593
- [OWASP Authentication Cheat Sheet](https://cheatsheetseries.owasp.org/cheatsheets/Authentication_Cheat_Sheet.html) - Network accessline 600
### 学习资源 - [Understanding JWT](https://jwt.io/) - Network accessline 601
- [Understanding JWT](https://jwt.io/) - Network accessline 602
- [TypeScript Deep Dive](https://basarat.gitbook.io/typescript/) - Network accessline 603
- [CORS Explained](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS)
bundled/skills/commit-with-reflection/references/best-practices.md
- Network accessline 536
npm run dev # 访问 http://localhost:3000/login - Network accessline 537
# 访问 http://localhost:3000/login - Network accessline 591
### 外部资源 - [TypeScript Handbook - Interfaces](https://www.typescriptlang.org/docs/handbook/interfaces.html) - Network accessline 592
- [TypeScript Handbook - Interfaces](https://www.typescriptlang.org/docs/handbook/interfaces.html) - Network accessline 593
- [Drizzle ORM - Type Safety](https://orm.drizzle.team/docs/type-safety) - Network accessline 594
- [JWT Best Practices](https://tools.ietf.org/html/rfc8725)
bundled/skills/commit-with-reflection/references/error-taxonomy.md
- Network accessline 111
// 异步逻辑错误 async function fetchData() { const data = await fetch(url); - Network accessline 112
async function fetchData() { const data = await fetch(url); return data; // 忘记解析JSON - Network accessline 113
const data = await fetch(url); - Network accessline 199
// CORS跨域问题 fetch('https://api.example.com/data') - Network accessline 200
fetch('https://api.example.com/data') - Network accessline 215
// 认证token过期 const data = await fetch(url, { - Network accessline 216
const data = await fetch(url, { - Network accessline 402
async function fetchData() { const response = await fetch(url); - Network accessline 403
const response = await fetch(url); - Network accessline 412
async function fetchData() { try { const response = await fetch(url); - Network accessline 413
try { const response = await fetch(url); if (!response.ok) { - Network accessline 414
const response = await fetch(url); - Network accessline 508
function searchUsers(query) { const requestId = ++latestRequestId; fetch(`/api/users?q=${query}`) - Network accessline 509
const requestId = ++latestRequestId; fetch(`/api/users?q=${query}`) .then(res => res.json()) - Network accessline 510
fetch(`/api/users?q=${query}`) - Network accessline 522
function searchUsers(query) { const requestId = ++latestRequestId; fetch(`/api/users?q=${query}`) - Network accessline 523
const requestId = ++latestRequestId; fetch(`/api/users?q=${query}`) .then(res => res.json()) - Network accessline 524
fetch(`/api/users?q=${query}`)
bundled/skills/commit-with-reflection/references/index.md
- Network accessline 77
### 外部资源 - [5 Whys Technique](https://en.wikipedia.org/wiki/Five_whys) - 根本原因分析方法 - Network accessline 78
- [5 Whys Technique](https://en.wikipedia.org/wiki/Five_whys) - 根本原因分析方法 - Network accessline 79
- [Postmortem Culture](https://sre.google/sre-book/postmortem-culture/) - Google SRE的事后分析文化 - Network accessline 80
- [Learning from Incidents](https://www.learningfromincidents.io/) - 从事故中学习
bundled/skills/commit-with-reflection/scripts/update-index.js
- Executable scriptline 1
#!/usr/bin/env node
bundled/skills/comprehensive-research-agent/references/patterns_found.json
- Network accessline 178
"type": "tool_misuse", "severity": "medium", "description": "The agent attempted to read a URL that returned an error (https://docs.anthropic.com/en/docs/build-with-claude/context-windows) but proceeded without acknowledging or hand - Network accessline 179
"severity": "medium", "description": "The agent attempted to read a URL that returned an error (https://docs.anthropic.com/en/docs/build-with-claude/context-windows) but proceeded without acknowledging or handling this failure", "su - Network accessline 180
"description": "The agent attempted to read a URL that returned an error (https://docs.anthropic.com/en/docs/build-with-claude/context-windows) but proceeded without acknowledging or handling this failure",
bundled/skills/context-fundamentals/scripts/context_manager.py
- Executable scriptline 1
Executable file
bundled/skills/creating-data-visualizations/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
bundled/skills/creating-data-visualizations/scripts/chart_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/creating-data-visualizations/scripts/data_analyzer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/creating-data-visualizations/scripts/data_validator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/cs-foundations/scripts/proof_validator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/cs-foundations/scripts/verify-proof.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/data-quality-frameworks/SKILL.md
- Network accessline 584
- [Great Expectations Documentation](https://docs.greatexpectations.io/) - Network accessline 585
- [dbt Testing Documentation](https://docs.getdbt.com/docs/build/tests) - Network accessline 586
- [Data Contract Specification](https://datacontract.com/) - Network accessline 587
- [Soda Core](https://docs.soda.io/soda-core/overview.html)
bundled/skills/data-storytelling/SKILL.md
- Network accessline 451
- [Storytelling with Data (Cole Nussbaumer)](https://www.storytellingwithdata.com/) - Network accessline 452
- [The Pyramid Principle (Barbara Minto)](https://www.amazon.com/Pyramid-Principle-Logic-Writing-Thinking/dp/0273710516) - Network accessline 453
- [Resonate (Nancy Duarte)](https://www.duarte.com/resonate/)
bundled/skills/datacommons-client/SKILL.md
- Network accessline 55
# Get latest population data response = client.observation.fetch( - Network accessline 56
response = client.observation.fetch( - Network accessline 62
# Get time series response = client.observation.fetch( - Network accessline 63
response = client.observation.fetch( - Network accessline 69
# Query by hierarchy response = client.observation.fetch( - Network accessline 70
response = client.observation.fetch( - Network accessline 160
response = client.observation.fetch( - Network accessline 195
# Or explore via the web interface # https://datacommons.org/tools/statvar - Network accessline 196
# https://datacommons.org/tools/statvar - Network accessline 204
response = client.observation.fetch( - Network accessline 226
[Credential-related source omitted] - Access to secretsline 226
[Credential-related source omitted] - Access to secretsline 227
[Credential-related source omitted] - Network accessline 228
- Request keys at: https://apikeys.datacommons.org/ - Network accessline 230
**For custom Data Commons instances:** - No API key required - Specify custom endpoint: `client = DataCommonsClient(url="https://custom.datacommons.org")` - Network accessline 232
- Specify custom endpoint: `client = DataCommonsClient(url="https://custom.datacommons.org")` - Network accessline 245
- **Official Documentation**: https://docs.datacommons.org/api/python/v2/ - Network accessline 246
- **Statistical Variable Explorer**: https://datacommons.org/tools/statvar - Network accessline 247
- **Data Commons Browser**: https://datacommons.org/browser/ - Network accessline 248
- **GitHub Repository**: https://github.com/datacommonsorg/api-python
bundled/skills/datacommons-client/references/getting_started.md
- Access to secretsline 14
[Credential-related source omitted] - Network accessline 17
Request an API key at: https://apikeys.datacommons.org/ - Network accessline 43
# Step 2: Query population data response = client.observation.fetch( - Network accessline 44
response = client.observation.fetch( - Network accessline 68
# Query unemployment rate over time response = client.observation.fetch( - Network accessline 69
response = client.observation.fetch( - Network accessline 96
# Query median income for all California counties response = client.observation.fetch( - Network accessline 97
response = client.observation.fetch( - Network accessline 149
response = client.observation.fetch( - Network accessline 200
# Step 4: Query specific variables response = client.observation.fetch( - Network accessline 201
response = client.observation.fetch( - Network accessline 221
# Query with facet filtering response = client.observation.fetch( - Network accessline 222
response = client.observation.fetch( - Network accessline 232
# Compare with all sources response_all = client.observation.fetch( - Network accessline 233
response_all = client.observation.fetch( - Network accessline 334
response = client.observation.fetch( - Network accessline 414
1. Explore available statistical variables: https://datacommons.org/tools/statvar - Network accessline 415
2. Browse the knowledge graph: https://datacommons.org/browser/ - Network accessline 417
4. Check official documentation: https://docs.datacommons.org/api/python/v2/
bundled/skills/datacommons-client/references/node.md
- Network accessline 16
### 1. fetch() - Network accessline 37
# Get outgoing properties from California response = client.node.fetch( - Network accessline 38
response = client.node.fetch( - Network accessline 43
# Get incoming properties (what points to this node) response = client.node.fetch( - Network accessline 44
response = client.node.fetch( - Network accessline 193
# First page response = client.node.fetch( - Network accessline 194
response = client.node.fetch( - Network accessline 200
# Get next page if available if response.nextToken: next_response = client.node.fetch( - Network accessline 201
if response.nextToken: next_response = client.node.fetch( node_dcids=["country/USA"], - Network accessline 202
next_response = client.node.fetch( - Network accessline 238
# Find all entities that reference a specific node references = client.node.fetch( - Network accessline 239
references = client.node.fetch(
bundled/skills/datacommons-client/references/observation.md
- Network accessline 12
### 1. fetch() - Network accessline 42
# Get latest population for multiple entities response = client.observation.fetch( - Network accessline 43
response = client.observation.fetch( - Network accessline 49
# Get complete time series response = client.observation.fetch( - Network accessline 50
response = client.observation.fetch( - Network accessline 56
# Use relation expressions to query hierarchies response = client.observation.fetch( - Network accessline 57
response = client.observation.fetch( - Network accessline 81
Explicit method targeting specific entities by DCID (functionally equivalent to `fetch()` with entity_dcids). - Network accessline 119
response = client.observation.fetch( - Network accessline 130
response = client.observation.fetch( - Network accessline 141
response = client.observation.fetch( - Network accessline 152
# Get data for all counties within California response = client.observation.fetch( - Network accessline 153
response = client.observation.fetch( - Network accessline 169
response = client.observation.fetch( - Network accessline 183
- **orderedFacets** are sorted by reliability/recency - Use relation expressions for complex graph queries - The `fetch()` method is the most flexible—use it for most queries - Network accessline 185
- The `fetch()` method is the most flexible—use it for most queries
bundled/skills/datacommons-client/references/resolve.md
- Network accessline 17
### 1. fetch() - Network accessline 31
# Resolve by name response = client.resolve.fetch( - Network accessline 32
response = client.resolve.fetch( - Network accessline 145
# Step 3: Query data using DCIDs data_response = client.observation.fetch( - Network accessline 146
data_response = client.observation.fetch( - Network accessline 202
# Now query data for that place response = client.observation.fetch( - Network accessline 203
response = client.observation.fetch(
bundled/skills/datavis/scripts/analyze-distribution.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/datavis/scripts/color-palette.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/datavis/scripts/d3-scaffold.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 42
<script src="https://d3js.org/d3.v7.min.js"></script> - Network accessline 483
'description': 'Color-encoded geographic visualization', 'instructions': 'Hover over regions for details.', 'extra_scripts': ' <script src="https://d3js.org/topojson.v3.min.js"></script>', - Network accessline 484
'instructions': 'Hover over regions for details.', 'extra_scripts': ' <script src="https://d3js.org/topojson.v3.min.js"></script>', 'css': BASE_CSS + """ - Network accessline 485
'extra_scripts': ' <script src="https://d3js.org/topojson.v3.min.js"></script>', - Network accessline 534
// Load US TopoJSON d3.json('https://cdn.jsdelivr.net/npm/us-atlas@3/states-10m.json') - Network accessline 535
d3.json('https://cdn.jsdelivr.net/npm/us-atlas@3/states-10m.json') - Network accessline 946
print(f" 1. cd {project_dir}") print(f" 2. python3 -m http.server 8000") print(f" 3. Open http://localhost:8000/") - Network accessline 947
print(f" 2. python3 -m http.server 8000") print(f" 3. Open http://localhost:8000/") print(f" 4. Replace sample data with your own") - Network accessline 948
print(f" 3. Open http://localhost:8000/")
bundled/skills/denario/references/installation.md
- Network accessline 42
# Clone the repository git clone https://github.com/AstroPilot-AI/Denario.git - Network accessline 43
git clone https://github.com/AstroPilot-AI/Denario.git - Access to secretsline 66
[Credential-related source omitted] - Network accessline 69
Access the GUI at `http://localhost:8501` after the container starts. - Dangerous shell operationline 126
sudo apt-get install texlive-full - Network accessline 134
### Windows Download and install [MiKTeX](https://miktex.org/download) or [TeX Live](https://tug.org/texlive/). - Network accessline 135
Download and install [MiKTeX](https://miktex.org/download) or [TeX Live](https://tug.org/texlive/).
bundled/skills/denario/references/llm_configuration.md
- Network accessline 28
1. **Create Google Cloud Project** - Navigate to [Google Cloud Console](https://console.cloud.google.com/) - Network accessline 29
- Navigate to [Google Cloud Console](https://console.cloud.google.com/) - Network accessline 49
1. **Create OpenAI Account** - Visit [platform.openai.com](https://platform.openai.com/) - Network accessline 50
- Visit [platform.openai.com](https://platform.openai.com/) - Access to secretsline 60
[Credential-related source omitted] - Access to secretsline 69
[Credential-related source omitted] - Access to secretsline 77
[Credential-related source omitted] - Access to secretsline 82
[Credential-related source omitted] - Access to secretsline 88
[Credential-related source omitted] - Access to secretsline 116
[Credential-related source omitted] - Access to secretsline 119
[Credential-related source omitted] - Access to secretsline 120
[Credential-related source omitted] - Network accessline 136
# Linux/macOS curl https://sdk.cloud.google.com | bash - Dangerous shell operationline 137
curl https://sdk.cloud.google.com | bash - Network accessline 137
curl https://sdk.cloud.google.com | bash - Access to secretsline 174
[Credential-related source omitted] - Access to secretsline 175
[Credential-related source omitted] - Network accessline 202
- **OpenAI**: Track usage at [platform.openai.com/usage](https://platform.openai.com/usage) - Access to secretsline 227
[Credential-related source omitted] - Access to secretsline 248
[Credential-related source omitted]
bundled/skills/detecting-data-anomalies/SKILL.md
- Broad permissionsline 1
Read, Bash(python:*), Grep, Glob
bundled/skills/detecting-data-anomalies/scripts/algorithm_selector.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-data-anomalies/scripts/anomaly_visualizer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-data-anomalies/scripts/data_loader.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-data-anomalies/scripts/report_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-performance-regressions/scripts/analyze_metrics.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-performance-regressions/scripts/create_github_comment.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/detecting-performance-regressions/scripts/generate_report.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/digital-brain/.gitignore
- Access to secretsline 23
[Credential-related source omitted]
bundled/skills/digital-brain/HOW-SKILLS-BUILT-THIS.md
- Network accessline 3
> This document demonstrates how the [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) collection was used by a Claude Code agent to design and build a production-ready personal k - Network accessline 402
- **Skills Collection**: [github.com/muratcankoylan/Agent-Skills-for-Context-Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) - Network accessline 403
- **Digital Brain**: [github.com/muratcankoylan/digital-brain-skill](https://github.com/muratcankoylan/digital-brain-skill)
bundled/skills/digital-brain/README.md
- Network accessline 3
> A personal operating system for founders, creators, and builders. Part of the [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) collection. - Network accessline 98
# User-wide installation git clone https://github.com/muratcankoylan/digital-brain-skill.git \ - Network accessline 99
git clone https://github.com/muratcankoylan/digital-brain-skill.git \ - Network accessline 102
# Or project-specific git clone https://github.com/muratcankoylan/digital-brain-skill.git \ - Network accessline 103
git clone https://github.com/muratcankoylan/digital-brain-skill.git \ - Network accessline 110
git clone https://github.com/muratcankoylan/digital-brain-skill.git ~/digital-brain - Network accessline 193
This is part of the [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) collection.
bundled/skills/digital-brain/SKILL.md
- Network accessline 192
External resources: - [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) - Network accessline 193
- [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) - Network accessline 194
- [Anthropic Context Engineering Guide](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents)
bundled/skills/digital-brain/SKILLS-MAPPING.md
- Network accessline 3
This document maps how [Agent Skills for Context Engineering](https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering) principles are applied in the Digital Brain implementation.
bundled/skills/digital-brain/agents/scripts/content_ideas.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/digital-brain/agents/scripts/idea_to_draft.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/digital-brain/agents/scripts/stale_contacts.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/digital-brain/agents/scripts/weekly_review.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/digital-brain/examples/content-workflow.md
- Network accessline 165
"type": "thread", "content": "Unpopular opinion: Building in public isn't about the wins...", "url": "https://twitter.com/user/status/123456789", - Network accessline 166
"content": "Unpopular opinion: Building in public isn't about the wins...", "url": "https://twitter.com/user/status/123456789", "pillar": "building_in_public", - Network accessline 167
"url": "https://twitter.com/user/status/123456789",
bundled/skills/digital-brain/examples/meeting-prep.md
- Network accessline 41
"last_contact": "2024-12-15T00:00:00Z", "links": { "twitter": "https://twitter.com/sarahchen_ai", - Network accessline 42
"links": { "twitter": "https://twitter.com/sarahchen_ai", "linkedin": "https://linkedin.com/in/sarahchen" - Network accessline 43
"twitter": "https://twitter.com/sarahchen_ai", - Network accessline 44
"linkedin": "https://linkedin.com/in/sarahchen"
bundled/skills/digital-brain/knowledge/KNOWLEDGE.md
bundled/skills/digital-brain/package.json
- Executable scriptline 1
Executable file - Network accessline 18
"repository": { "type": "git", "url": "https://github.com/muratcankoylan/digital-brain-skill" - Network accessline 19
"type": "git", "url": "https://github.com/muratcankoylan/digital-brain-skill" }, - Network accessline 20
"url": "https://github.com/muratcankoylan/digital-brain-skill" - Network accessline 21
}, "homepage": "https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering", "bugs": { - Network accessline 22
"homepage": "https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering", - Network accessline 23
"bugs": { "url": "https://github.com/muratcankoylan/digital-brain-skill/issues" }, - Network accessline 24
"url": "https://github.com/muratcankoylan/digital-brain-skill/issues"
bundled/skills/digital-brain/references/file-formats.md
- Network accessline 54
"type": "post|thread|article|video|podcast", "content": "Full content or summary", "url": "https://...", - Network accessline 55
"content": "Full content or summary", "url": "https://...", "pillar": "content_pillar_name", - Network accessline 56
"url": "https://...", - Network accessline 91
"last_contact": "2024-12-15T00:00:00Z", "links": { "twitter": "https://twitter.com/johndoe", - Network accessline 92
"links": { "twitter": "https://twitter.com/johndoe", "linkedin": "https://linkedin.com/in/johndoe", - Network accessline 93
"twitter": "https://twitter.com/johndoe", - Network accessline 94
"linkedin": "https://linkedin.com/in/johndoe", - Network accessline 95
"website": "https://johndoe.com" - Network accessline 119
"id": "bm_20241229_120000", "saved_at": "2024-12-29T12:00:00Z", "url": "https://example.com/article", - Network accessline 120
"saved_at": "2024-12-29T12:00:00Z", "url": "https://example.com/article", "title": "Article Title", - Network accessline 121
"url": "https://example.com/article", - Network accessline 260
- type: "course|book|tutorial|project" title: "Resource name" url: "https://..." - Network accessline 261
title: "Resource name" url: "https://..." status: "not_started|in_progress|completed" - Network accessline 262
url: "https://..."
bundled/skills/digital-brain/scripts/install.sh
bundled/skills/dnanexus-integration/SKILL.md
bundled/skills/dnanexus-integration/references/configuration.md
- Access to secretsline 363
[Credential-related source omitted]
bundled/skills/dnanexus-integration/references/python-sdk.md
bundled/skills/doc/LICENSE.txt
bundled/skills/doc/SKILL.md
- Dangerous shell operationline 46
sudo apt-get install -y libreoffice poppler-utils
bundled/skills/doc/assets/doc-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/doc/scripts/render_docx.py
- Executable scriptline 1
Executable file - Network accessline 39
xml = zf.read("word/document.xml") root = ET.fromstring(xml) ns = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"} - Network accessline 41
ns = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"} - Network accessline 52
w_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}w" - Network accessline 53
"{http://schemas.openxmlformats.org/wordprocessingml/2006/main}w" - Network accessline 54
) or pg_sz.get("w") h_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" - Network accessline 55
h_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" ) or pg_sz.get("h") - Network accessline 56
"{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" - Access to secretsline 106
[Credential-related source omitted]
bundled/skills/docs-review/SKILL.md
- Broad permissionsline 1
Read, Grep, Bash, Glob
bundled/skills/docs-write/SKILL.md
- Broad permissionsline 1
Read, Write, Grep, Bash, Glob
bundled/skills/document-skills/docx/LICENSE.txt
- Network accessline 6
exists, use is governed by Anthropic's Consumer Terms of Service or Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms - Network accessline 7
Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms https://www.anthropic.com/legal/commercial-terms - Network accessline 8
https://www.anthropic.com/legal/consumer-terms - Network accessline 9
https://www.anthropic.com/legal/commercial-terms
bundled/skills/document-skills/docx/SKILL.md
- Dangerous shell operationline 227
- **pandoc**: `sudo apt-get install pandoc` (for text extraction) - Dangerous shell operationline 229
- **LibreOffice**: `sudo apt-get install libreoffice` (for PDF conversion) - Dangerous shell operationline 230
- **Poppler**: `sudo apt-get install poppler-utils` (for pdftoppm to convert PDF to images)
bundled/skills/document-skills/docx/docx-js.md
- Network accessline 238
children: [new ExternalHyperlink({ children: [new TextRun({ text: "Google", style: "Hyperlink" })], link: "https://www.google.com" - Network accessline 239
children: [new TextRun({ text: "Google", style: "Hyperlink" })], link: "https://www.google.com" })] - Network accessline 240
link: "https://www.google.com"
bundled/skills/document-skills/docx/ooxml.md
- Network accessline 166
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/numbering" Target="numbering.xml"/> - Network accessline 167
<Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/> - Network accessline 185
<wp:extent cx="2743200" cy="1828800"/> <wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 186
<wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 187
<a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 188
<a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 189
<pic:pic xmlns:pic="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 230
<!-- In word/_rels/document.xml.rels --> <Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/hyperlink" - Network accessline 231
<Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/hyperlink" - Network accessline 232
Target="https://www.example.com/" TargetMode="External"/> - Network accessline 463
next_rid = rels_editor.get_next_rid() rels_editor.append_to(rels_editor.dom.documentElement, f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') - Network accessline 464
rels_editor.append_to(rels_editor.dom.documentElement, f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') doc['[Content_Types].xml'].append_to(d - Network accessline 465
f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') - Network accessline 475
<wp:extent cx="{width_emus}" cy="{height_emus}"/> <wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 476
<wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 477
<a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 478
<a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 479
<pic:pic xmlns:pic="http://schemas.openxmlformats.org/drawingml/2006/picture">
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-chart.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 6
xmlns:cdr="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 7
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 9
elementFormDefault="qualified" attributeFormDefault="unqualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 11
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 13
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" schemaLocation="dml-chartDrawing.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 15
schemaLocation="dml-chartDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 6
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-diagram.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 8
elementFormDefault="qualified" attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 12
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-main.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
xmlns="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 7
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 9
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 11
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" schemaLocation="dml-diagram.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 13
schemaLocation="dml-diagram.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chart" schemaLocation="dml-chart.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 15
schemaLocation="dml-chart.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" schemaLocation="dml-picture.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 17
schemaLocation="dml-picture.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas" schemaLocation="dml-lockedCanvas.xsd"/> - Network accessline 18
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-picture.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" elementFormDefault="qualified" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 6
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-spreadsheetDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 7
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 9
schemaLocation="dml-main.xsd"/> <xsd:import schemaLocation="shared-relationshipReference.xsd" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/> - Network accessline 10
<xsd:import schemaLocation="shared-relationshipReference.xsd" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/> <xsd:element name="from" type="CT_Marker"/> - Network accessline 11
namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/>
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-wordprocessingDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 5
xmlns:dpct="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 6
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 7
xmlns="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 9
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 11
schemaLocation="dml-main.xsd"/> <xsd:import schemaLocation="wml.xsd" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> - Network accessline 12
<xsd:import schemaLocation="wml.xsd" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 13
namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 15
schemaLocation="dml-picture.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/pml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/presentationml/2006/main" - Network accessline 4
xmlns:p="http://schemas.openxmlformats.org/presentationml/2006/main" - Network accessline 5
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 6
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 7
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 8
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/presentationml/2006/main"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 9
targetNamespace="http://schemas.openxmlformats.org/presentationml/2006/main"> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 11
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 13
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-additionalCharacteristics.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/characteristics" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/characteristics"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-bibliography.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" - Network accessline 6
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlDataProperties.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/customXml" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/customXml" - Network accessline 6
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlSchemaProperties.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesCustom.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/custom-properties" - Network accessline 4
xmlns:vt="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 5
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/custom-properties" - Network accessline 7
blockDefault="#all" elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 9
schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesExtended.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/extended-properties" - Network accessline 4
xmlns:vt="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/extended-properties" - Network accessline 6
elementFormDefault="qualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesVariantTypes.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 6
blockDefault="#all" elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-math.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 4
xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 5
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/math"> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/ - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/math"> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 10
schemaLocation="wml.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="xml.xsd"/> <xsd:simpleType name="ST_Integer255"> - Network accessline 13
<xsd:import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="xml.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-relationshipReference.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" blockDefault="#all"> - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/sml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/spreadsheetml/2006/main" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:xdr="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/spreadsheetml/2006/main" - Network accessline 8
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" schemaLocation="dml-spreadsheetDrawing.xsd"/> - Network accessline 14
namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-main.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns="urn:schemas-microsoft-com:vml" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns="urn:schemas-microsoft-com:vml" - Network accessline 3
xmlns:pvml="urn:schemas-microsoft-com:office:powerpoint" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 4
xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:w10="urn:schemas-microsoft-com:office:word" - Network accessline 5
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 6
xmlns:w10="urn:schemas-microsoft-com:office:word" xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" xmlns:x="urn:schemas-microsoft-com:office:excel" - Network accessline 7
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 8
xmlns:x="urn:schemas-microsoft-com:office:excel" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" targetNamespace="urn:schemas-microsoft-com:vml" elementFormDefault="qualified" - Network accessline 9
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
<xsd:import namespace="urn:schemas-microsoft-com:office:office" schemaLocation="vml-officeDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 13
schemaLocation="vml-officeDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="wml.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 16
<xsd:import namespace="urn:schemas-microsoft-com:office:word" schemaLocation="vml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 17
schemaLocation="vml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 18
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 22
<xsd:import namespace="urn:schemas-microsoft-com:office:powerpoint" schemaLocation="vml-presentationDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 23
schemaLocation="vml-presentationDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 24
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-officeDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="urn:schemas-microsoft-com:office:office" xmlns:v="urn:schemas-microsoft-com:vml" xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedT - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
attributeFormDefault="unqualified"> <xsd:import namespace="urn:schemas-microsoft-com:vml" schemaLocation="vml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 8
<xsd:import namespace="urn:schemas-microsoft-com:vml" schemaLocation="vml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-presentationDrawing.xsd
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-spreadsheetDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="urn:schemas-microsoft-com:office:excel" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" targetNamespace="urn:schemas-microsoft-com:office:excel" elementFormDefault="qualified" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="urn:schemas-microsoft-com:office:excel" elementFormDefault="qualified" attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 6
attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-wordprocessingDrawing.xsd
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/wml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:sl="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 6
xmlns:wp="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 7
xmlns="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 8
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 9
xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 10
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" targetNamespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"> <xsd:import namespace="http://schemas.openxmlformats.org/markup-compatib - Network accessline 11
targetNamespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/markup-compatibility/2006" schemaLocation="../mce/mc.xsd"/> - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 14
schemaLocation="dml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/math" schemaLocation="shared-math.xsd"/> - Network accessline 15
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 16
schemaLocation="shared-math.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 17
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 18
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 19
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 20
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main" schemaLocation="shared-customXmlSchemaProperties.xsd"/> - Network accessline 21
<xsd:import namespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 22
schemaLocation="shared-customXmlSchemaProperties.xsd"/> <xsd:import namespace="http://www.w3.org/XML/1998/namespace"/> <xsd:complexType name="CT_Empty"/> - Network accessline 23
<xsd:import namespace="http://www.w3.org/XML/1998/namespace"/>
bundled/skills/document-skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/xml.xsd
- Network accessline 1
<?xml version='1.0'?> <xs:schema targetNamespace="http://www.w3.org/XML/1998/namespace" xmlns:xs="http://www.w3.org/2001/XMLSchema" xml:lang="en"> - Network accessline 2
<xs:schema targetNamespace="http://www.w3.org/XML/1998/namespace" xmlns:xs="http://www.w3.org/2001/XMLSchema" xml:lang="en"> - Network accessline 4
<xs:annotation> <xs:documentation> See http://www.w3.org/XML/1998/namespace.html and - Network accessline 5
<xs:documentation> See http://www.w3.org/XML/1998/namespace.html and http://www.w3.org/TR/REC-xml for information about this namespace. - Network accessline 6
See http://www.w3.org/XML/1998/namespace.html and - Network accessline 7
http://www.w3.org/TR/REC-xml for information about this namespace. - Network accessline 55
<schema . . .> . . . <import namespace="http://www.w3.org/XML/1998/namespace" - Network accessline 56
. . . <import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="http://www.w3.org/2001/03/xml.xsd"/> - Network accessline 57
<import namespace="http://www.w3.org/XML/1998/namespace" - Network accessline 58
schemaLocation="http://www.w3.org/2001/03/xml.xsd"/> - Network accessline 72
<xs:documentation>In keeping with the XML Schema WG's standard versioning policy, this schema document will persist at http://www.w3.org/2001/03/xml.xsd. - Network accessline 73
policy, this schema document will persist at http://www.w3.org/2001/03/xml.xsd. At the date of issue it can also be found at - Network accessline 74
http://www.w3.org/2001/03/xml.xsd. - Network accessline 75
At the date of issue it can also be found at http://www.w3.org/2001/xml.xsd. The schema document at that URI may however change in the future, - Network accessline 76
http://www.w3.org/2001/xml.xsd. - Network accessline 79
itself. In other words, if the XML Schema namespace changes, the version of this document at http://www.w3.org/2001/xml.xsd will change - Network accessline 80
of this document at http://www.w3.org/2001/xml.xsd will change accordingly; the version at - Network accessline 81
http://www.w3.org/2001/xml.xsd will change - Network accessline 82
accordingly; the version at http://www.w3.org/2001/03/xml.xsd will not change. </xs:documentation> - Network accessline 83
http://www.w3.org/2001/03/xml.xsd will not change. - Network accessline 103
<xs:attribute name="base" type="xs:anyURI"> <xs:annotation> <xs:documentation>See http://www.w3.org/TR/xmlbase/ for - Network accessline 104
<xs:annotation> <xs:documentation>See http://www.w3.org/TR/xmlbase/ for information about this attribute.</xs:documentation> - Network accessline 105
<xs:documentation>See http://www.w3.org/TR/xmlbase/ for
bundled/skills/document-skills/docx/ooxml/schemas/ecma/fouth-edition/opc-contentTypes.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8" standalone="no"?> <xs:schema xmlns="http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 2
<xs:schema xmlns="http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 3
xmlns:xs="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/content-types"
bundled/skills/document-skills/docx/ooxml/schemas/ecma/fouth-edition/opc-coreProperties.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8"?> <xs:schema targetNamespace="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 2
<xs:schema targetNamespace="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 4
xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:dc="http://purl.org/dc/elements/1.1/" - Network accessline 5
xmlns:dcterms="http://purl.org/dc/terms/" elementFormDefault="qualified" blockDefault="#all"> - Network accessline 7
<xs:import namespace="http://purl.org/dc/elements/1.1/" - Network accessline 8
schemaLocation="http://dublincore.org/schemas/xmls/qdc/2003/04/02/dc.xsd"/> - Network accessline 9
<xs:import namespace="http://purl.org/dc/terms/" - Network accessline 10
schemaLocation="http://dublincore.org/schemas/xmls/qdc/2003/04/02/dcterms.xsd"/> - Network accessline 11
<xs:import id="xml" namespace="http://www.w3.org/XML/1998/namespace"/>
bundled/skills/document-skills/docx/ooxml/schemas/ecma/fouth-edition/opc-digSig.xsd
- Network accessline 1
<?xml version="1.0" encoding="UTF-8"?> <xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/digital-signature" - Network accessline 2
<xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/digital-signature" - Network accessline 3
xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/digital-signature"
bundled/skills/document-skills/docx/ooxml/schemas/ecma/fouth-edition/opc-relationships.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8" standalone="no"?> <xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 2
<xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 3
xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/relationships"
bundled/skills/document-skills/docx/ooxml/schemas/mce/mc.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 2
<xsd:schema xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 3
attributeFormDefault="unqualified" elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/markup-compatibility/2006" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 5
xmlns:xsd="http://www.w3.org/2001/XMLSchema"> - Network accessline 7
<!-- This XSD is a modified version of the one found at: https://github.com/plutext/docx4j/blob/master/xsd/mce/markup-compatibility-2006-MINIMAL.xsd - Network accessline 9
https://github.com/plutext/docx4j/blob/master/xsd/mce/markup-compatibility-2006-MINIMAL.xsd - Network accessline 15
<w:document xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 16
xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 17
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main"
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-2010.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns:r="http://schemas.op - Network accessline 2
<!-- <xsd:import id="rel" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="orel.xsd"/> --> - Network accessline 3
<xsd:import id="w" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 4
<!-- <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="oartbasetypes.xsd"/> - Network accessline 5
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="oartsplineproperties.xsd"/> -->
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-2012.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" elementFormDefault="qualified" att - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 3
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="../ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-2018.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-cex-2018.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" xmlns:w16="http://schemas.microsoft. - Network accessline 2
<xsd:import id="w16" namespace="http://schemas.microsoft.com/office/word/2018/wordml" schemaLocation="wml-2018.xsd"/> - Network accessline 3
<xsd:import id="w" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 4
<xsd:import id="s" namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="../ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-cid-2016.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-sdtdatahash-2020.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/document-skills/docx/ooxml/schemas/microsoft/wml-symex-2015.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/document-skills/docx/ooxml/scripts/pack.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/document-skills/docx/ooxml/scripts/unpack.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/document-skills/docx/ooxml/scripts/validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/document-skills/docx/ooxml/scripts/validation/__init__.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/docx/ooxml/scripts/validation/base.py
- Executable scriptline 1
Executable file - Network accessline 70
MC_NAMESPACE = "http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 71
XML_NAMESPACE = "http://www.w3.org/XML/1998/namespace" - Network accessline 74
PACKAGE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 75
"http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 76
) OFFICE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 77
OFFICE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/officeDocument/2006/relationships" ) - Network accessline 78
"http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 79
) CONTENT_TYPES_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 80
CONTENT_TYPES_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/content-types" ) - Network accessline 81
"http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 88
OOXML_NAMESPACES = { "http://schemas.openxmlformats.org/officeDocument/2006/math", - Network accessline 89
"http://schemas.openxmlformats.org/officeDocument/2006/math", - Network accessline 90
"http://schemas.openxmlformats.org/officeDocument/2006/relationships", - Network accessline 91
"http://schemas.openxmlformats.org/schemaLibrary/2006/main", - Network accessline 92
"http://schemas.openxmlformats.org/drawingml/2006/main", - Network accessline 93
"http://schemas.openxmlformats.org/drawingml/2006/chart", - Network accessline 94
"http://schemas.openxmlformats.org/drawingml/2006/chartDrawing", - Network accessline 95
"http://schemas.openxmlformats.org/drawingml/2006/diagram", - Network accessline 96
"http://schemas.openxmlformats.org/drawingml/2006/picture", - Network accessline 97
"http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing", - Network accessline 98
"http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing", - Network accessline 99
"http://schemas.openxmlformats.org/wordprocessingml/2006/main", - Network accessline 100
"http://schemas.openxmlformats.org/presentationml/2006/main", - Network accessline 101
"http://schemas.openxmlformats.org/spreadsheetml/2006/main", - Network accessline 102
"http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes", - Network accessline 103
"http://www.w3.org/XML/1998/namespace",
bundled/skills/document-skills/docx/ooxml/scripts/validation/docx.py
bundled/skills/document-skills/docx/ooxml/scripts/validation/pptx.py
bundled/skills/document-skills/docx/ooxml/scripts/validation/redlining.py
- Executable scriptline 1
Executable file - Network accessline 17
self.verbose = verbose self.namespaces = { "w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 18
self.namespaces = { "w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main" } - Network accessline 19
"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"
bundled/skills/document-skills/docx/scripts/__init__.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/docx/scripts/document.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 93
root.setAttribute( # type: ignore "xmlns:w16du", "http://schemas.microsoft.com/office/word/2023/wordml/word16du", - Network accessline 94
"xmlns:w16du", "http://schemas.microsoft.com/office/word/2023/wordml/word16du", ) - Network accessline 95
"http://schemas.microsoft.com/office/word/2023/wordml/word16du", - Network accessline 102
root.setAttribute( # type: ignore "xmlns:w16cex", "http://schemas.microsoft.com/office/word/2018/wordml/cex", - Network accessline 103
"xmlns:w16cex", "http://schemas.microsoft.com/office/word/2018/wordml/cex", ) - Network accessline 104
"http://schemas.microsoft.com/office/word/2018/wordml/cex", - Network accessline 111
root.setAttribute( # type: ignore "xmlns:w14", "http://schemas.microsoft.com/office/word/2010/wordml", - Network accessline 112
"xmlns:w14", "http://schemas.microsoft.com/office/word/2010/wordml", ) - Network accessline 113
"http://schemas.microsoft.com/office/word/2010/wordml", - Network accessline 445
wrapper = f'<root xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main">{xml_content}</root>' - Network accessline 985
rel_xml = f'<{prefix}Relationship Id="{next_rid}" Type="http://schemas.microsoft.com/office/2011/relationships/people" Target="people.xml"/>' - Network accessline 1217
( next_rid_num, "http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", - Network accessline 1218
next_rid_num, "http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", "comments.xml", - Network accessline 1219
"http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", - Network accessline 1222
( next_rid_num + 1, "http://schemas.microsoft.com/office/2011/relationships/commentsExtended", - Network accessline 1223
next_rid_num + 1, "http://schemas.microsoft.com/office/2011/relationships/commentsExtended", "commentsExtended.xml", - Network accessline 1224
"http://schemas.microsoft.com/office/2011/relationships/commentsExtended", - Network accessline 1227
( next_rid_num + 2, "http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", - Network accessline 1228
next_rid_num + 2, "http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", "commentsIds.xml", - Network accessline 1229
"http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", - Network accessline 1232
( next_rid_num + 3, "http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible", - Network accessline 1233
next_rid_num + 3, "http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible", "commentsExtensible.xml", - Network accessline 1234
"http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible",
bundled/skills/document-skills/docx/scripts/templates/comments.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w:comments xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas - Network accessline 2
<w:comments xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex" xmlns:cx
bundled/skills/document-skills/docx/scripts/templates/commentsExtended.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w15:commentsEx xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://sch - Network accessline 2
<w15:commentsEx xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex" xmln
bundled/skills/document-skills/docx/scripts/templates/commentsExtensible.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w16cex:commentsExtensible xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1= - Network accessline 2
<w16cex:commentsExtensible xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/ch
bundled/skills/document-skills/docx/scripts/templates/commentsIds.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w16cid:commentsIds xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http:/ - Network accessline 2
<w16cid:commentsIds xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex"
bundled/skills/document-skills/docx/scripts/templates/people.xml
bundled/skills/document-skills/docx/scripts/utilities.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/document-skills/pdf/LICENSE.txt
- Network accessline 6
exists, use is governed by Anthropic's Consumer Terms of Service or Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms - Network accessline 7
Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms https://www.anthropic.com/legal/commercial-terms - Network accessline 8
https://www.anthropic.com/legal/consumer-terms - Network accessline 9
https://www.anthropic.com/legal/commercial-terms
bundled/skills/document-skills/pdf/scripts/check_bounding_boxes.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/check_bounding_boxes_test.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/check_fillable_fields.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/convert_pdf_to_images.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/create_validation_image.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/extract_form_field_info.py
- Executable scriptline 1
Executable file - Network accessline 31
# "/Off" seems to always be the unchecked value, as suggested by # https://opensource.adobe.com/dc-acrobat-sdk-docs/standards/pdfstandards/pdf/PDF32000_2008.pdf#page=448 - Network accessline 32
# https://opensource.adobe.com/dc-acrobat-sdk-docs/standards/pdfstandards/pdf/PDF32000_2008.pdf#page=448 - Network accessline 79
# Radio button options have a separate annotation for each choice; # all choices have the same field name. # See https://westhealth.github.io/exploring-fillable-forms-with-pdfrw.html - Network accessline 81
# See https://westhealth.github.io/exploring-fillable-forms-with-pdfrw.html
bundled/skills/document-skills/pdf/scripts/fill_fillable_fields.py
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pdf/scripts/fill_pdf_form_with_annotations.py
bundled/skills/document-skills/pptx/LICENSE.txt
- Network accessline 6
exists, use is governed by Anthropic's Consumer Terms of Service or Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms - Network accessline 7
Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms https://www.anthropic.com/legal/commercial-terms - Network accessline 8
https://www.anthropic.com/legal/consumer-terms - Network accessline 9
https://www.anthropic.com/legal/commercial-terms
bundled/skills/document-skills/pptx/SKILL.md
bundled/skills/document-skills/pptx/html2pptx.md
bundled/skills/document-skills/pptx/ooxml.md
- Network accessline 239
</p:xfrm> <a:graphic> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/table"> - Network accessline 240
<a:graphic> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/table"> <a:tbl> - Network accessline 241
<a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/table"> - Network accessline 325
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/slide" Target="slides/slide1.xml"/> - Network accessline 326
<Relationship Id="rId2" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/slideMaster" Target="slideMasters/slideMaster1.xml"/> - Network accessline 331
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/slideLayout" Target="../slideLayouts/slideLayout1.xml"/> - Network accessline 332
<Relationship Id="rId2" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="../media/image1.png"/>
bundled/skills/document-skills/pptx/ooxml/scripts/pack.py
bundled/skills/document-skills/pptx/ooxml/scripts/unpack.py
bundled/skills/document-skills/pptx/ooxml/scripts/validate.py
bundled/skills/document-skills/pptx/scripts/html2pptx.js
- Executable scriptline 1
Executable file
bundled/skills/document-skills/pptx/scripts/inventory.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 166
): pPr = paragraph._p.pPr ns = "{http://schemas.openxmlformats.org/drawingml/2006/main}" - Network accessline 167
pPr = paragraph._p.pPr ns = "{http://schemas.openxmlformats.org/drawingml/2006/main}" if ( - Network accessline 168
ns = "{http://schemas.openxmlformats.org/drawingml/2006/main}"
bundled/skills/document-skills/pptx/scripts/rearrange.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 103
for blip in blips: old_rId = blip.get( "{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed" - Network accessline 104
old_rId = blip.get( "{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed" ) - Network accessline 105
"{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed" - Network accessline 115
blip.set( "{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed", - Network accessline 116
"{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed",
bundled/skills/document-skills/pptx/scripts/replace.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/document-skills/pptx/scripts/thumbnail.py
bundled/skills/docx-comment-reply/scripts/apply_comment_replies.py
- Executable scriptline 1
Executable file
bundled/skills/docx-comment-reply/scripts/extract_comment_context.py
- Executable scriptline 1
Executable file - Network accessline 17
NS = { "w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main", - Network accessline 18
"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main", - Network accessline 19
"w14": "http://schemas.microsoft.com/office/word/2010/wordml", - Network accessline 20
"w15": "http://schemas.microsoft.com/office/word/2012/wordml",
bundled/skills/docx-comment-reply/scripts/lint_replies.py
- Executable scriptline 1
Executable file
bundled/skills/docx/LICENSE.txt
- Network accessline 6
exists, use is governed by Anthropic's Consumer Terms of Service or Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms - Network accessline 7
Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms https://www.anthropic.com/legal/commercial-terms - Network accessline 8
https://www.anthropic.com/legal/consumer-terms - Network accessline 9
https://www.anthropic.com/legal/commercial-terms
bundled/skills/docx/SKILL.md
- Dangerous shell operationline 193
- **pandoc**: `sudo apt-get install pandoc` (for text extraction) - Dangerous shell operationline 195
- **LibreOffice**: `sudo apt-get install libreoffice` (for PDF conversion) - Dangerous shell operationline 196
- **Poppler**: `sudo apt-get install poppler-utils` (for pdftoppm to convert PDF to images)
bundled/skills/docx/docx-js.md
- Network accessline 238
children: [new ExternalHyperlink({ children: [new TextRun({ text: "Google", style: "Hyperlink" })], link: "https://www.google.com" - Network accessline 239
children: [new TextRun({ text: "Google", style: "Hyperlink" })], link: "https://www.google.com" })] - Network accessline 240
link: "https://www.google.com"
bundled/skills/docx/ooxml.md
- Network accessline 166
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/numbering" Target="numbering.xml"/> - Network accessline 167
<Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/> - Network accessline 185
<wp:extent cx="2743200" cy="1828800"/> <wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 186
<wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 187
<a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 188
<a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 189
<pic:pic xmlns:pic="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 230
<!-- In word/_rels/document.xml.rels --> <Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/hyperlink" - Network accessline 231
<Relationship Id="rId5" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/hyperlink" - Network accessline 232
Target="https://www.example.com/" TargetMode="External"/> - Network accessline 463
next_rid = rels_editor.get_next_rid() rels_editor.append_to(rels_editor.dom.documentElement, f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') - Network accessline 464
rels_editor.append_to(rels_editor.dom.documentElement, f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') doc['[Content_Types].xml'].append_to(d - Network accessline 465
f'<Relationship Id="{next_rid}" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/image" Target="media/image1.png"/>') - Network accessline 475
<wp:extent cx="{width_emus}" cy="{height_emus}"/> <wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 476
<wp:docPr id="1" name="Picture 1"/> <a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> <a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 477
<a:graphic xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main"> - Network accessline 478
<a:graphicData uri="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 479
<pic:pic xmlns:pic="http://schemas.openxmlformats.org/drawingml/2006/picture">
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-chart.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 6
xmlns:cdr="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 7
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 9
elementFormDefault="qualified" attributeFormDefault="unqualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 11
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 13
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" schemaLocation="dml-chartDrawing.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 15
schemaLocation="dml-chartDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/chartDrawing" - Network accessline 6
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-diagram.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 8
elementFormDefault="qualified" attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 12
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-main.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
xmlns="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 7
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 9
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 11
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" schemaLocation="dml-diagram.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/diagram" - Network accessline 13
schemaLocation="dml-diagram.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chart" schemaLocation="dml-chart.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/chart" - Network accessline 15
schemaLocation="dml-chart.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" schemaLocation="dml-picture.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 17
schemaLocation="dml-picture.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas" schemaLocation="dml-lockedCanvas.xsd"/> - Network accessline 18
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/lockedCanvas"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-picture.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 4
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" elementFormDefault="qualified" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/picture"> - Network accessline 6
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-spreadsheetDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 5
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 7
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 9
schemaLocation="dml-main.xsd"/> <xsd:import schemaLocation="shared-relationshipReference.xsd" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/> - Network accessline 10
<xsd:import schemaLocation="shared-relationshipReference.xsd" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/> <xsd:element name="from" type="CT_Marker"/> - Network accessline 11
namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"/>
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/dml-wordprocessingDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 4
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 5
xmlns:dpct="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 6
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 7
xmlns="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 9
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 11
schemaLocation="dml-main.xsd"/> <xsd:import schemaLocation="wml.xsd" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> - Network accessline 12
<xsd:import schemaLocation="wml.xsd" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 13
namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/picture" - Network accessline 15
schemaLocation="dml-picture.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 16
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/pml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/presentationml/2006/main" - Network accessline 4
xmlns:p="http://schemas.openxmlformats.org/presentationml/2006/main" - Network accessline 5
xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 6
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 7
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 8
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/presentationml/2006/main"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 9
targetNamespace="http://schemas.openxmlformats.org/presentationml/2006/main"> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 11
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="dml-main.xsd"/> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" - Network accessline 13
schemaLocation="dml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-additionalCharacteristics.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/characteristics" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/characteristics"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-bibliography.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" - Network accessline 6
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlDataProperties.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/customXml" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/customXml" - Network accessline 6
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-customXmlSchemaProperties.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesCustom.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/custom-properties" - Network accessline 4
xmlns:vt="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 5
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/custom-properties" - Network accessline 7
blockDefault="#all" elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> - Network accessline 8
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 9
schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 10
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesExtended.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/extended-properties" - Network accessline 4
xmlns:vt="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/extended-properties" - Network accessline 6
elementFormDefault="qualified" blockDefault="#all"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" schemaLocation="shared-documentPropertiesVariantTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-documentPropertiesVariantTypes.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes" - Network accessline 6
blockDefault="#all" elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-math.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 4
xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 5
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/math"> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/ - Network accessline 8
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/math"> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 10
schemaLocation="wml.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="xml.xsd"/> <xsd:simpleType name="ST_Integer255"> - Network accessline 13
<xsd:import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="xml.xsd"/>
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/shared-relationshipReference.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" blockDefault="#all"> - Network accessline 6
targetNamespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/sml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/spreadsheetml/2006/main" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:xdr="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 6
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
targetNamespace="http://schemas.openxmlformats.org/spreadsheetml/2006/main" - Network accessline 8
elementFormDefault="qualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing" schemaLocation="dml-spreadsheetDrawing.xsd"/> - Network accessline 14
namespace="http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-main.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns="urn:schemas-microsoft-com:vml" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns="urn:schemas-microsoft-com:vml" - Network accessline 3
xmlns:pvml="urn:schemas-microsoft-com:office:powerpoint" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 4
xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:w10="urn:schemas-microsoft-com:office:word" - Network accessline 5
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 6
xmlns:w10="urn:schemas-microsoft-com:office:word" xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" xmlns:x="urn:schemas-microsoft-com:office:excel" - Network accessline 7
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 8
xmlns:x="urn:schemas-microsoft-com:office:excel" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" targetNamespace="urn:schemas-microsoft-com:vml" elementFormDefault="qualified" - Network accessline 9
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 12
<xsd:import namespace="urn:schemas-microsoft-com:office:office" schemaLocation="vml-officeDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 13
schemaLocation="vml-officeDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="wml.xsd"/> - Network accessline 14
<xsd:import namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 16
<xsd:import namespace="urn:schemas-microsoft-com:office:word" schemaLocation="vml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 17
schemaLocation="vml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 18
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 22
<xsd:import namespace="urn:schemas-microsoft-com:office:powerpoint" schemaLocation="vml-presentationDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 23
schemaLocation="vml-presentationDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 24
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-officeDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="urn:schemas-microsoft-com:office:office" xmlns:v="urn:schemas-microsoft-com:vml" xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedT - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 7
attributeFormDefault="unqualified"> <xsd:import namespace="urn:schemas-microsoft-com:vml" schemaLocation="vml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 8
<xsd:import namespace="urn:schemas-microsoft-com:vml" schemaLocation="vml-main.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 9
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 10
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 11
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-presentationDrawing.xsd
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-spreadsheetDrawing.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns="urn:schemas-microsoft-com:office:excel" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" targetNamespace="urn:schemas-microsoft-com:office:excel" elementFormDefault="qualified" - Network accessline 4
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 5
targetNamespace="urn:schemas-microsoft-com:office:excel" elementFormDefault="qualified" attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 6
attributeFormDefault="unqualified"> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 7
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes"
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/vml-wordprocessingDrawing.xsd
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/wml.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 2
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 3
xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 4
xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 5
xmlns:sl="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 6
xmlns:wp="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 7
xmlns="http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 8
xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 9
xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 10
elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" targetNamespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"> <xsd:import namespace="http://schemas.openxmlformats.org/markup-compatib - Network accessline 11
targetNamespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main"> - Network accessline 12
<xsd:import namespace="http://schemas.openxmlformats.org/markup-compatibility/2006" schemaLocation="../mce/mc.xsd"/> - Network accessline 13
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" - Network accessline 14
schemaLocation="dml-wordprocessingDrawing.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/math" schemaLocation="shared-math.xsd"/> - Network accessline 15
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/math" - Network accessline 16
schemaLocation="shared-math.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="shared-relationshipReference.xsd"/> - Network accessline 17
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 18
schemaLocation="shared-relationshipReference.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="shared-commonSimpleTypes.xsd"/> - Network accessline 19
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" - Network accessline 20
schemaLocation="shared-commonSimpleTypes.xsd"/> <xsd:import namespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main" schemaLocation="shared-customXmlSchemaProperties.xsd"/> - Network accessline 21
<xsd:import namespace="http://schemas.openxmlformats.org/schemaLibrary/2006/main" - Network accessline 22
schemaLocation="shared-customXmlSchemaProperties.xsd"/> <xsd:import namespace="http://www.w3.org/XML/1998/namespace"/> <xsd:complexType name="CT_Empty"/> - Network accessline 23
<xsd:import namespace="http://www.w3.org/XML/1998/namespace"/>
bundled/skills/docx/ooxml/schemas/ISO-IEC29500-4_2016/xml.xsd
- Network accessline 1
<?xml version='1.0'?> <xs:schema targetNamespace="http://www.w3.org/XML/1998/namespace" xmlns:xs="http://www.w3.org/2001/XMLSchema" xml:lang="en"> - Network accessline 2
<xs:schema targetNamespace="http://www.w3.org/XML/1998/namespace" xmlns:xs="http://www.w3.org/2001/XMLSchema" xml:lang="en"> - Network accessline 4
<xs:annotation> <xs:documentation> See http://www.w3.org/XML/1998/namespace.html and - Network accessline 5
<xs:documentation> See http://www.w3.org/XML/1998/namespace.html and http://www.w3.org/TR/REC-xml for information about this namespace. - Network accessline 6
See http://www.w3.org/XML/1998/namespace.html and - Network accessline 7
http://www.w3.org/TR/REC-xml for information about this namespace. - Network accessline 55
<schema . . .> . . . <import namespace="http://www.w3.org/XML/1998/namespace" - Network accessline 56
. . . <import namespace="http://www.w3.org/XML/1998/namespace" schemaLocation="http://www.w3.org/2001/03/xml.xsd"/> - Network accessline 57
<import namespace="http://www.w3.org/XML/1998/namespace" - Network accessline 58
schemaLocation="http://www.w3.org/2001/03/xml.xsd"/> - Network accessline 72
<xs:documentation>In keeping with the XML Schema WG's standard versioning policy, this schema document will persist at http://www.w3.org/2001/03/xml.xsd. - Network accessline 73
policy, this schema document will persist at http://www.w3.org/2001/03/xml.xsd. At the date of issue it can also be found at - Network accessline 74
http://www.w3.org/2001/03/xml.xsd. - Network accessline 75
At the date of issue it can also be found at http://www.w3.org/2001/xml.xsd. The schema document at that URI may however change in the future, - Network accessline 76
http://www.w3.org/2001/xml.xsd. - Network accessline 79
itself. In other words, if the XML Schema namespace changes, the version of this document at http://www.w3.org/2001/xml.xsd will change - Network accessline 80
of this document at http://www.w3.org/2001/xml.xsd will change accordingly; the version at - Network accessline 81
http://www.w3.org/2001/xml.xsd will change - Network accessline 82
accordingly; the version at http://www.w3.org/2001/03/xml.xsd will not change. </xs:documentation> - Network accessline 83
http://www.w3.org/2001/03/xml.xsd will not change. - Network accessline 103
<xs:attribute name="base" type="xs:anyURI"> <xs:annotation> <xs:documentation>See http://www.w3.org/TR/xmlbase/ for - Network accessline 104
<xs:annotation> <xs:documentation>See http://www.w3.org/TR/xmlbase/ for information about this attribute.</xs:documentation> - Network accessline 105
<xs:documentation>See http://www.w3.org/TR/xmlbase/ for
bundled/skills/docx/ooxml/schemas/ecma/fouth-edition/opc-contentTypes.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8" standalone="no"?> <xs:schema xmlns="http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 2
<xs:schema xmlns="http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 3
xmlns:xs="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/content-types"
bundled/skills/docx/ooxml/schemas/ecma/fouth-edition/opc-coreProperties.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8"?> <xs:schema targetNamespace="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 2
<xs:schema targetNamespace="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 3
xmlns="http://schemas.openxmlformats.org/package/2006/metadata/core-properties" - Network accessline 4
xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:dc="http://purl.org/dc/elements/1.1/" - Network accessline 5
xmlns:dcterms="http://purl.org/dc/terms/" elementFormDefault="qualified" blockDefault="#all"> - Network accessline 7
<xs:import namespace="http://purl.org/dc/elements/1.1/" - Network accessline 8
schemaLocation="http://dublincore.org/schemas/xmls/qdc/2003/04/02/dc.xsd"/> - Network accessline 9
<xs:import namespace="http://purl.org/dc/terms/" - Network accessline 10
schemaLocation="http://dublincore.org/schemas/xmls/qdc/2003/04/02/dcterms.xsd"/> - Network accessline 11
<xs:import id="xml" namespace="http://www.w3.org/XML/1998/namespace"/>
bundled/skills/docx/ooxml/schemas/ecma/fouth-edition/opc-digSig.xsd
- Network accessline 1
<?xml version="1.0" encoding="UTF-8"?> <xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/digital-signature" - Network accessline 2
<xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/digital-signature" - Network accessline 3
xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/digital-signature"
bundled/skills/docx/ooxml/schemas/ecma/fouth-edition/opc-relationships.xsd
- Network accessline 1
<U+FEFF><?xml version="1.0" encoding="UTF-8" standalone="no"?> <xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 2
<xsd:schema xmlns="http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 3
xmlns:xsd="http://www.w3.org/2001/XMLSchema" - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/package/2006/relationships"
bundled/skills/docx/ooxml/schemas/mce/mc.xsd
- Network accessline 1
<?xml version="1.0" encoding="utf-8"?> <xsd:schema xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 2
<xsd:schema xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 3
attributeFormDefault="unqualified" elementFormDefault="qualified" targetNamespace="http://schemas.openxmlformats.org/markup-compatibility/2006" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> - Network accessline 4
targetNamespace="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 5
xmlns:xsd="http://www.w3.org/2001/XMLSchema"> - Network accessline 7
<!-- This XSD is a modified version of the one found at: https://github.com/plutext/docx4j/blob/master/xsd/mce/markup-compatibility-2006-MINIMAL.xsd - Network accessline 9
https://github.com/plutext/docx4j/blob/master/xsd/mce/markup-compatibility-2006-MINIMAL.xsd - Network accessline 15
<w:document xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 16
xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 17
xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main"
bundled/skills/docx/ooxml/schemas/microsoft/wml-2010.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns:r="http://schemas.op - Network accessline 2
<!-- <xsd:import id="rel" namespace="http://schemas.openxmlformats.org/officeDocument/2006/relationships" schemaLocation="orel.xsd"/> --> - Network accessline 3
<xsd:import id="w" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 4
<!-- <xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="oartbasetypes.xsd"/> - Network accessline 5
<xsd:import namespace="http://schemas.openxmlformats.org/drawingml/2006/main" schemaLocation="oartsplineproperties.xsd"/> -->
bundled/skills/docx/ooxml/schemas/microsoft/wml-2012.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" elementFormDefault="qualified" att - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 3
<xsd:import namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="../ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd"/>
bundled/skills/docx/ooxml/schemas/microsoft/wml-2018.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/docx/ooxml/schemas/microsoft/wml-cex-2018.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" xmlns:s="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" xmlns:w16="http://schemas.microsoft. - Network accessline 2
<xsd:import id="w16" namespace="http://schemas.microsoft.com/office/word/2018/wordml" schemaLocation="wml-2018.xsd"/> - Network accessline 3
<xsd:import id="w" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/> - Network accessline 4
<xsd:import id="s" namespace="http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes" schemaLocation="../ISO-IEC29500-4_2016/shared-commonSimpleTypes.xsd"/>
bundled/skills/docx/ooxml/schemas/microsoft/wml-cid-2016.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/docx/ooxml/schemas/microsoft/wml-sdtdatahash-2020.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/docx/ooxml/schemas/microsoft/wml-symex-2015.xsd
- Network accessline 1
<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:w12="http://schemas.openxmlformats.org/wordprocessingml/2006/main" elementFormDefault="qualified" attributeFormDefault="qualified" blockDefault="#all" xmlns="http://schemas.micr - Network accessline 2
<xsd:import id="w12" namespace="http://schemas.openxmlformats.org/wordprocessingml/2006/main" schemaLocation="../ISO-IEC29500-4_2016/wml.xsd"/>
bundled/skills/docx/ooxml/scripts/pack.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/docx/ooxml/scripts/unpack.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/docx/ooxml/scripts/validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/docx/ooxml/scripts/validation/__init__.py
- Executable scriptline 1
Executable file
bundled/skills/docx/ooxml/scripts/validation/base.py
- Executable scriptline 1
Executable file - Network accessline 70
MC_NAMESPACE = "http://schemas.openxmlformats.org/markup-compatibility/2006" - Network accessline 71
XML_NAMESPACE = "http://www.w3.org/XML/1998/namespace" - Network accessline 74
PACKAGE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 75
"http://schemas.openxmlformats.org/package/2006/relationships" - Network accessline 76
) OFFICE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 77
OFFICE_RELATIONSHIPS_NAMESPACE = ( "http://schemas.openxmlformats.org/officeDocument/2006/relationships" ) - Network accessline 78
"http://schemas.openxmlformats.org/officeDocument/2006/relationships" - Network accessline 79
) CONTENT_TYPES_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 80
CONTENT_TYPES_NAMESPACE = ( "http://schemas.openxmlformats.org/package/2006/content-types" ) - Network accessline 81
"http://schemas.openxmlformats.org/package/2006/content-types" - Network accessline 88
OOXML_NAMESPACES = { "http://schemas.openxmlformats.org/officeDocument/2006/math", - Network accessline 89
"http://schemas.openxmlformats.org/officeDocument/2006/math", - Network accessline 90
"http://schemas.openxmlformats.org/officeDocument/2006/relationships", - Network accessline 91
"http://schemas.openxmlformats.org/schemaLibrary/2006/main", - Network accessline 92
"http://schemas.openxmlformats.org/drawingml/2006/main", - Network accessline 93
"http://schemas.openxmlformats.org/drawingml/2006/chart", - Network accessline 94
"http://schemas.openxmlformats.org/drawingml/2006/chartDrawing", - Network accessline 95
"http://schemas.openxmlformats.org/drawingml/2006/diagram", - Network accessline 96
"http://schemas.openxmlformats.org/drawingml/2006/picture", - Network accessline 97
"http://schemas.openxmlformats.org/drawingml/2006/spreadsheetDrawing", - Network accessline 98
"http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing", - Network accessline 99
"http://schemas.openxmlformats.org/wordprocessingml/2006/main", - Network accessline 100
"http://schemas.openxmlformats.org/presentationml/2006/main", - Network accessline 101
"http://schemas.openxmlformats.org/spreadsheetml/2006/main", - Network accessline 102
"http://schemas.openxmlformats.org/officeDocument/2006/sharedTypes", - Network accessline 103
"http://www.w3.org/XML/1998/namespace",
bundled/skills/docx/ooxml/scripts/validation/docx.py
bundled/skills/docx/ooxml/scripts/validation/pptx.py
bundled/skills/docx/ooxml/scripts/validation/redlining.py
- Executable scriptline 1
Executable file - Network accessline 17
self.verbose = verbose self.namespaces = { "w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main" - Network accessline 18
self.namespaces = { "w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main" } - Network accessline 19
"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"
bundled/skills/docx/scripts/__init__.py
- Executable scriptline 1
Executable file
bundled/skills/docx/scripts/document.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 93
root.setAttribute( # type: ignore "xmlns:w16du", "http://schemas.microsoft.com/office/word/2023/wordml/word16du", - Network accessline 94
"xmlns:w16du", "http://schemas.microsoft.com/office/word/2023/wordml/word16du", ) - Network accessline 95
"http://schemas.microsoft.com/office/word/2023/wordml/word16du", - Network accessline 102
root.setAttribute( # type: ignore "xmlns:w16cex", "http://schemas.microsoft.com/office/word/2018/wordml/cex", - Network accessline 103
"xmlns:w16cex", "http://schemas.microsoft.com/office/word/2018/wordml/cex", ) - Network accessline 104
"http://schemas.microsoft.com/office/word/2018/wordml/cex", - Network accessline 111
root.setAttribute( # type: ignore "xmlns:w14", "http://schemas.microsoft.com/office/word/2010/wordml", - Network accessline 112
"xmlns:w14", "http://schemas.microsoft.com/office/word/2010/wordml", ) - Network accessline 113
"http://schemas.microsoft.com/office/word/2010/wordml", - Network accessline 445
wrapper = f'<root xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main">{xml_content}</root>' - Network accessline 985
rel_xml = f'<{prefix}Relationship Id="{next_rid}" Type="http://schemas.microsoft.com/office/2011/relationships/people" Target="people.xml"/>' - Network accessline 1217
( next_rid_num, "http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", - Network accessline 1218
next_rid_num, "http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", "comments.xml", - Network accessline 1219
"http://schemas.openxmlformats.org/officeDocument/2006/relationships/comments", - Network accessline 1222
( next_rid_num + 1, "http://schemas.microsoft.com/office/2011/relationships/commentsExtended", - Network accessline 1223
next_rid_num + 1, "http://schemas.microsoft.com/office/2011/relationships/commentsExtended", "commentsExtended.xml", - Network accessline 1224
"http://schemas.microsoft.com/office/2011/relationships/commentsExtended", - Network accessline 1227
( next_rid_num + 2, "http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", - Network accessline 1228
next_rid_num + 2, "http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", "commentsIds.xml", - Network accessline 1229
"http://schemas.microsoft.com/office/2016/09/relationships/commentsIds", - Network accessline 1232
( next_rid_num + 3, "http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible", - Network accessline 1233
next_rid_num + 3, "http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible", "commentsExtensible.xml", - Network accessline 1234
"http://schemas.microsoft.com/office/2018/08/relationships/commentsExtensible",
bundled/skills/docx/scripts/templates/comments.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w:comments xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas - Network accessline 2
<w:comments xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex" xmlns:cx
bundled/skills/docx/scripts/templates/commentsExtended.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w15:commentsEx xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://sch - Network accessline 2
<w15:commentsEx xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex" xmln
bundled/skills/docx/scripts/templates/commentsExtensible.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w16cex:commentsExtensible xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1= - Network accessline 2
<w16cex:commentsExtensible xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/ch
bundled/skills/docx/scripts/templates/commentsIds.xml
- Network accessline 1
<?xml version="1.0" encoding="UTF-8" standalone="yes"?> <w16cid:commentsIds xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http:/ - Network accessline 2
<w16cid:commentsIds xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" xmlns:cx="http://schemas.microsoft.com/office/drawing/2014/chartex" xmlns:cx1="http://schemas.microsoft.com/office/drawing/2015/9/8/chartex"
bundled/skills/docx/scripts/templates/people.xml
bundled/skills/docx/scripts/utilities.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/edgartools/references/companies.md
- Network accessline 61
company.fiscal_year_end # "0630" (June 30) company.exchange # "Nasdaq" company.website # "https://www.microsoft.com" - Network accessline 62
company.exchange # "Nasdaq" company.website # "https://www.microsoft.com" company.city # "Redmond" - Network accessline 63
company.website # "https://www.microsoft.com"
bundled/skills/edgartools/references/filings.md
bundled/skills/embedding-strategies/SKILL.md
bundled/skills/ena-database/SKILL.md
- Network accessline 53
**ENA Portal API** - Advanced search functionality across all ENA data types - Documentation: https://www.ebi.ac.uk/ena/portal/api/doc - Network accessline 54
- Documentation: https://www.ebi.ac.uk/ena/portal/api/doc - Network accessline 57
**ENA Browser API** - Direct retrieval of records and metadata - Documentation: https://www.ebi.ac.uk/ena/browser/api/doc - Network accessline 58
- Documentation: https://www.ebi.ac.uk/ena/browser/api/doc - Network accessline 65
**ENA Cross Reference Service** - Access related records from external databases - Endpoint: https://www.ebi.ac.uk/ena/xref/rest/ - Network accessline 66
- Endpoint: https://www.ebi.ac.uk/ena/xref/rest/ - Network accessline 68
**CRAM Reference Registry** - Retrieve reference sequences - Endpoint: https://www.ebi.ac.uk/ena/cram/ - Network accessline 69
- Endpoint: https://www.ebi.ac.uk/ena/cram/ - Network accessline 91
# Search for samples from a specific study base_url = "https://www.ebi.ac.uk/ena/portal/api/search" - Network accessline 92
base_url = "https://www.ebi.ac.uk/ena/portal/api/search" - Network accessline 100
response = requests.get(base_url, params=params) - Network accessline 127
# Download run files using Browser API accession = "ERR123456" url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}" - Network accessline 129
url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}" - Network accessline 134
# Use Portal API to list samples study_id = "PRJNA123456" url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=sample&query=study_accession={study_id}&format=tsv" - Network accessline 136
url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=sample&query=study_accession={study_id}&format=tsv" - Network accessline 141
# Search assemblies by taxonomy organism = "Escherichia coli" url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=assembly&query=tax_tree({organism})&format=json" - Network accessline 143
url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=assembly&query=tax_tree({organism})&format=json" - Network accessline 148
# Query taxonomy API taxon_id = "562" # E. coli url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}" - Network accessline 150
url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}"
bundled/skills/ena-database/references/api_reference.md
- Network accessline 7
**Base URL:** `https://www.ebi.ac.uk/ena/portal/api` - Network accessline 9
**Official Documentation:** https://www.ebi.ac.uk/ena/portal/api/doc - Network accessline 66
# Search for human samples url = "https://www.ebi.ac.uk/ena/portal/api/search" - Network accessline 67
url = "https://www.ebi.ac.uk/ena/portal/api/search" - Network accessline 73
"limit": 100 } response = requests.get(url, params=params) - Network accessline 75
response = requests.get(url, params=params) - Network accessline 81
"format": "tsv" } response = requests.get(url, params=params) - Network accessline 83
response = requests.get(url, params=params) - Network accessline 89
"format": "json" } response = requests.get(url, params=params) - Network accessline 91
response = requests.get(url, params=params) - Network accessline 112
# Get all available fields for samples url = "https://www.ebi.ac.uk/ena/portal/api/returnFields" - Network accessline 113
url = "https://www.ebi.ac.uk/ena/portal/api/returnFields" params = {"result": "sample"} response = requests.get(url, params=params) - Network accessline 114
params = {"result": "sample"} response = requests.get(url, params=params) fields = response.json() - Network accessline 115
response = requests.get(url, params=params) - Network accessline 130
url = "https://www.ebi.ac.uk/ena/portal/api/results" response = requests.get(url) - Network accessline 131
response = requests.get(url) - Network accessline 164
# Get FASTQ download URLs for a run url = "https://www.ebi.ac.uk/ena/portal/api/filereport" - Network accessline 165
url = "https://www.ebi.ac.uk/ena/portal/api/filereport" - Network accessline 170
"fields": "run_accession,fastq_ftp,fastq_md5,fastq_bytes" } response = requests.get(url, params=params) - Network accessline 171
} response = requests.get(url, params=params) file_info = response.json() - Network accessline 172
response = requests.get(url, params=params) - Network accessline 183
**Base URL:** `https://www.ebi.ac.uk/ena/browser/api` - Network accessline 185
**Official Documentation:** https://www.ebi.ac.uk/ena/browser/api/doc - Network accessline 206
# Get sample metadata in XML accession = "SAMEA123456" url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}" - Network accessline 207
accession = "SAMEA123456" url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}" response = requests.get(url) - Network accessline 208
url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}" response = requests.get(url) xml_data = response.text - Network accessline 209
response = requests.get(url) - Network accessline 212
# Get study with cross-references url = f"https://www.ebi.ac.uk/ena/browser/api/xml/PRJNA123456" - Network accessline 213
url = f"https://www.ebi.ac.uk/ena/browser/api/xml/PRJNA123456" params = {"includeLinks": "true"} response = requests.get(url, params=params) - Network accessline 215
response = requests.get(url, params=params) - Network accessline 238
# Get sequence in EMBL format url = "https://www.ebi.ac.uk/ena/browser/api/text/LN847353" response = requests.get(url) - Network accessline 239
url = "https://www.ebi.ac.uk/ena/browser/api/text/LN847353" response = requests.get(url) embl_format = response.text - Network accessline 240
response = requests.get(url) - Network accessline 264
# Get full sequence url = "https://www.ebi.ac.uk/ena/browser/api/fasta/LN847353" response = requests.get(url) - Network accessline 265
url = "https://www.ebi.ac.uk/ena/browser/api/fasta/LN847353" response = requests.get(url) fasta_data = response.text - Network accessline 266
response = requests.get(url) - Network accessline 269
# Get subsequence url = "https://www.ebi.ac.uk/ena/browser/api/fasta/LN847353" - Network accessline 270
url = "https://www.ebi.ac.uk/ena/browser/api/fasta/LN847353" params = {"range": "1000-2000"} response = requests.get(url, params=params) - Network accessline 272
response = requests.get(url, params=params) - Network accessline 294
# Get all links for a sample url = "https://www.ebi.ac.uk/ena/browser/api/links/sample/SAMEA123456" response = requests.get(url) - Network accessline 295
url = "https://www.ebi.ac.uk/ena/browser/api/links/sample/SAMEA123456" - Network accessline 296
response = requests.get(url) - Network accessline 301
**Base URL:** `https://www.ebi.ac.uk/ena/taxonomy/rest` - Network accessline 316
# Get E. coli taxonomy taxon_id = "562" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}" - Network accessline 317
taxon_id = "562" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}" response = requests.get(url) - Network accessline 318
url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}" response = requests.get(url) taxonomy = response.json() - Network accessline 319
response = requests.get(url) - Network accessline 335
# Search by scientific name name = "Escherichia coli" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/scientific-name/{name}" - Network accessline 336
name = "Escherichia coli" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/scientific-name/{name}" response = requests.get(url) - Network accessline 337
url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/scientific-name/{name}" - Network accessline 338
response = requests.get(url) - Network accessline 352
# Get suggestions partial = "Escheri" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/suggest-for-submission/{partial}" - Network accessline 353
partial = "Escheri" url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/suggest-for-submission/{partial}" response = requests.get(url) - Network accessline 354
url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/suggest-for-submission/{partial}" - Network accessline 355
response = requests.get(url) - Network accessline 360
**Base URL:** `https://www.ebi.ac.uk/ena/xref/rest` - Network accessline 382
# Get cross-references for an SRA accession url = "https://www.ebi.ac.uk/ena/xref/rest/json/sra/SRR000001" response = requests.get(url) - Network accessline 383
url = "https://www.ebi.ac.uk/ena/xref/rest/json/sra/SRR000001" response = requests.get(url) xrefs = response.json() - Network accessline 384
response = requests.get(url) - Network accessline 390
**Base URL:** `https://www.ebi.ac.uk/ena/cram` - Network accessline 405
# Get reference by MD5 md5 = "7c3f69f0c5f0f0de6d7c34e7c2e25f5c" url = f"https://www.ebi.ac.uk/ena/cram/md5/{md5}" - Network accessline 406
md5 = "7c3f69f0c5f0f0de6d7c34e7c2e25f5c" url = f"https://www.ebi.ac.uk/ena/cram/md5/{md5}" response = requests.get(url) - Network accessline 407
url = f"https://www.ebi.ac.uk/ena/cram/md5/{md5}" response = requests.get(url) reference_fasta = response.text - Network accessline 408
response = requests.get(url) - Network accessline 436
def create_session_with_retries(): """Create requests session with retry logic""" session = requests.Session() - Network accessline 437
"""Create requests session with retry logic""" session = requests.Session() retries = Retry( - Network accessline 438
session = requests.Session() - Network accessline 475
accessions = ["ERR001", "ERR002", "ERR003"] for acc in accessions: response = requests.get(f"{base_url}/xml/{acc}") - Network accessline 476
for acc in accessions: response = requests.get(f"{base_url}/xml/{acc}") # Process response - Network accessline 477
response = requests.get(f"{base_url}/xml/{acc}")
bundled/skills/error-resolver/SKILL.md
bundled/skills/error-resolver/patterns/database.md
- Dangerous shell operationline 43
sudo systemctl start postgresql # Linux - Dangerous shell operationline 47
sudo systemctl start mysql # Linux - Dangerous shell operationline 71
sudo -u postgres psql - Dangerous shell operationline 419
sudo systemctl start mongod # Linux - Dangerous shell operationline 495
sudo systemctl start redis # Linux
bundled/skills/error-resolver/patterns/docker.md
- Dangerous shell operationline 123
sudo systemctl start docker - Dangerous shell operationline 129
sudo usermod -aG docker $USER - Dangerous shell operationline 245
# Run with sudo (not recommended for regular use) - Dangerous shell operationline 246
sudo docker ps - Dangerous shell operationline 249
sudo usermod -aG docker $USER - Dangerous shell operationline 398
chmod 777 /host/path # Not recommended for production
bundled/skills/error-resolver/patterns/git.md
- Dangerous shell operationline 79
eval "$(ssh-agent -s)" - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 86
[Credential-related source omitted] - Network accessline 89
# Or use HTTPS instead of SSH git remote set-url origin https://github.com/user/repo.git - Network accessline 90
git remote set-url origin https://github.com/user/repo.git - Network accessline 98
remote: Invalid username or password. fatal: Authentication failed for 'https://github.com/...' - Network accessline 99
fatal: Authentication failed for 'https://github.com/...'
bundled/skills/error-resolver/patterns/network.md
- Network accessline 25
# Check request curl -v -X POST https://api.example.com/endpoint \ - Network accessline 26
curl -v -X POST https://api.example.com/endpoint \ - Network accessline 33
// Check Content-Type fetch(url, { - Network accessline 34
fetch(url, { - Network accessline 65
// Check Authorization header format fetch(url, { - Network accessline 66
fetch(url, { - Network accessline 72
// Refresh token if expired async function fetchWithAuth(url) { let response = await fetch(url, { - Network accessline 73
[Credential-related source omitted] - Network accessline 74
let response = await fetch(url, { - Network accessline 78
if (response.status === 401) { accessToken = await refreshToken() response = await fetch(url, { - Network accessline 79
[Credential-related source omitted] - Network accessline 80
response = await fetch(url, { - Network accessline 129
# Check URL is correct curl -I https://api.example.com/users/123 - Network accessline 130
curl -I https://api.example.com/users/123 - Network accessline 132
# Try with/without trailing slash curl https://api.example.com/users/ - Network accessline 133
curl https://api.example.com/users/ - Network accessline 134
curl https://api.example.com/users - Network accessline 139
// Handle 404 gracefully const response = await fetch(`/api/users/${id}`) - Network accessline 140
const response = await fetch(`/api/users/${id}`) - Network accessline 162
# Check allowed methods curl -I -X OPTIONS https://api.example.com/endpoint - Network accessline 163
curl -I -X OPTIONS https://api.example.com/endpoint - Network accessline 166
# Use correct method curl -X POST https://api.example.com/users # Not GET - Network accessline 167
curl -X POST https://api.example.com/users # Not GET - Network accessline 186
async function fetchWithRetry(url, maxRetries = 3) { for (let i = 0; i < maxRetries; i++) { const response = await fetch(url) - Network accessline 188
const response = await fetch(url) - Network accessline 207
async function limitedFetch(url) { await limiter.removeTokens(1) return fetch(url) - Network accessline 208
await limiter.removeTokens(1) return fetch(url) } - Network accessline 209
return fetch(url) - Network accessline 272
for (let i = 0; i < maxRetries; i++) { try { const response = await fetch(url) - Network accessline 273
try { const response = await fetch(url) if (response.status === 503) { - Network accessline 274
const response = await fetch(url) - Network accessline 325
lsof -i :3000 netstat -an | grep 3000 curl -v http://localhost:3000 - Network accessline 327
curl -v http://localhost:3000 - Network accessline 381
try { const response = await fetch(url, { signal: controller.signal }) - Network accessline 382
const response = await fetch(url, { signal: controller.signal }) - Network accessline 410
for (let i = 0; i < retries; i++) { try { return await fetch(url) - Network accessline 411
try { return await fetch(url) } catch (error) { - Network accessline 412
return await fetch(url) - Network accessline 447
ca: fs.readFileSync('ca-cert.pem'), }) fetch(url, { agent }) - Network accessline 449
fetch(url, { agent }) - Network accessline 470
Access to fetch at 'https://api.example.com' from origin 'https://myapp.com' - Network accessline 482
const cors = require('cors') app.use(cors({ origin: 'https://myapp.com', // Or '*' for all (not recommended) - Network accessline 483
app.use(cors({ origin: 'https://myapp.com', // Or '*' for all (not recommended) credentials: true, - Network accessline 484
origin: 'https://myapp.com', // Or '*' for all (not recommended) - Network accessline 488
// Manual headers app.use((req, res, next) => { res.header('Access-Control-Allow-Origin', 'https://myapp.com') - Network accessline 489
app.use((req, res, next) => { res.header('Access-Control-Allow-Origin', 'https://myapp.com') res.header('Access-Control-Allow-Methods', 'GET, POST, PUT, DELETE') - Network accessline 490
res.header('Access-Control-Allow-Origin', 'https://myapp.com') - Network accessline 504
proxy: { '/api': { target: 'https://api.example.com', - Network accessline 505
'/api': { target: 'https://api.example.com', changeOrigin: true, - Network accessline 506
target: 'https://api.example.com', - Network accessline 513
// Then fetch from /api instead fetch('/api/endpoint') - Network accessline 514
fetch('/api/endpoint') - Network accessline 560
const response = await fetch(url) - Network accessline 569
// Check response before parsing const response = await fetch(url) - Network accessline 570
const response = await fetch(url)
bundled/skills/error-resolver/patterns/nodejs.md
- Dangerous shell operationline 25
rm -rf node_modules package-lock.json - Network accessline 107
# Test connectivity ping hostname curl -I https://hostname - Network accessline 109
curl -I https://hostname - Network accessline 138
const controller = new AbortController() setTimeout(() => controller.abort(), 30000) fetch(url, { signal: controller.signal }) - Network accessline 140
fetch(url, { signal: controller.signal }) - Dangerous shell operationline 212
sudo chown $USER:$USER /path/to/file - Dangerous shell operationline 215
sudo chown -R $USER /usr/local/lib/node_modules - Network accessline 278
// For '<' - check API response const res = await fetch(url) - Network accessline 279
const res = await fetch(url) - Dangerous shell operationline 581
rm -rf node_modules package-lock.json
bundled/skills/error-resolver/patterns/python.md
bundled/skills/error-resolver/patterns/react.md
- Network accessline 202
fetch(url, { signal: controller.signal })
bundled/skills/error-resolver/replay/README.md
- Network accessline 263
root_cause: "useEffect cleanup not cancelling async operations" factors: - "fetch() or setTimeout() completing after unmount" - Network accessline 264
factors: - "fetch() or setTimeout() completing after unmount" - "No cleanup function in useEffect" - Network accessline 265
- "fetch() or setTimeout() completing after unmount" - Network accessline 273
useEffect(() => { const controller = new AbortController() fetch(url, { signal: controller.signal }) - Network accessline 274
const controller = new AbortController() fetch(url, { signal: controller.signal }) .then(res => res.json()) - Network accessline 275
fetch(url, { signal: controller.signal }) - Dangerous shell operationline 297
- "chmod 777 /host/path" # Quick but not secure
bundled/skills/etetoolkit/SKILL.md
bundled/skills/etetoolkit/scripts/quick_visualize.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/etetoolkit/scripts/tree_operations.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/evals-context/SKILL.md
- Network accessline 33
| **Evals Management UI** | `apps/web-evals/` | Next.js app for creating/monitoring eval runs (localhost:3446) | | **Website Evals Page** | `apps/web-roo-code/src/app/evals/` - Network accessline 35
| **External Exercises Repo** | [Roo-Code-Evals](https://github.com/RooCodeInc/Roo-Code-Evals) | Actual coding exercises (NOT in this monorepo) | - Network accessline 126
1. Add exercise to [Roo-Code-Evals](https://github.com/RooCodeInc/Roo-Code-Evals) repo (external) - Network accessline 163
# Opens web UI at http://localhost:3446
bundled/skills/evaluating-code-models/SKILL.md
- Network accessline 19
git clone https://github.com/bigcode-project/bigcode-evaluation-harness.git - Access to secretsline 96
[Credential-related source omitted] - Access to secretsline 100
[Credential-related source omitted] - Network accessline 401
- **GitHub**: https://github.com/bigcode-project/bigcode-evaluation-harness - Network accessline 402
- **Documentation**: https://github.com/bigcode-project/bigcode-evaluation-harness/tree/main/docs - Network accessline 403
- **BigCode Leaderboard**: https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard - Network accessline 404
- **HumanEval Dataset**: https://huggingface.co/datasets/openai/openai_humaneval - Network accessline 405
- **MultiPL-E**: https://github.com/nuprl/MultiPL-E
bundled/skills/evaluating-code-models/references/issues.md
- Network accessline 16
# Install matching PyTorch (example for CUDA 11.8) pip install torch --index-url https://download.pytorch.org/whl/cu118 - Network accessline 17
pip install torch --index-url https://download.pytorch.org/whl/cu118 - Network accessline 33
# Install specific dependencies pip install -e ".[ds1000]" pip install torch==1.12.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 - Network accessline 35
pip install torch==1.12.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 - Access to secretsline 52
[Credential-related source omitted] - Access to secretsline 54
[Credential-related source omitted] - Access to secretsline 250
[Credential-related source omitted] - Network accessline 315
# Clone repo git clone https://github.com/bigcode-project/bigcode-evaluation-harness.git - Network accessline 316
git clone https://github.com/bigcode-project/bigcode-evaluation-harness.git - Dangerous shell operationline 320
sudo make DOCKERFILE=Dockerfile all - Dangerous shell operationline 323
sudo make DOCKERFILE=Dockerfile-multiple all - Network accessline 388
1. **Check existing issues**: https://github.com/bigcode-project/bigcode-evaluation-harness/issues
bundled/skills/evaluating-llms-harness/SKILL.md
- Dangerous shell operationline 184
Avoid for frequent eval (too slow): - Network accessline 484
- GitHub: https://github.com/EleutherAI/lm-evaluation-harness - Network accessline 485
- Docs: https://github.com/EleutherAI/lm-evaluation-harness/tree/main/docs - Network accessline 487
- Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard (uses this harness)
bundled/skills/evaluating-llms-harness/references/api-evaluation.md
- Access to secretsline 36
[Credential-related source omitted] - Network accessline 77
lm_eval --model openai-chat-completions --model_args model=gpt-4-turbo, base_url=https://api.openai.com/v1, - Network accessline 80
base_url=https://api.openai.com/v1,\ - Access to secretsline 121
[Credential-related source omitted] - Network accessline 150
lm_eval --model anthropic-chat --model_args model=claude-3-5-sonnet-20241022, base_url=https://api.anthropic.com, - Network accessline 153
base_url=https://api.anthropic.com,\ - Network accessline 196
lm_eval --model local-completions --model_args model=meta-llama/Llama-2-7b-hf, base_url=http://localhost:8000/v1, - Network accessline 199
base_url=http://localhost:8000/v1,\ - Network accessline 216
lm_eval --model local-completions --model_args model=meta-llama/Llama-2-7b-hf, base_url=http://localhost:8080/v1 - Network accessline 219
base_url=http://localhost:8080/v1 \ - Network accessline 233
lm_eval --model local-completions --model_args model=llama2:7b, base_url=http://localhost:11434/v1 - Network accessline 236
base_url=http://localhost:11434/v1 \ - Network accessline 249
lm_eval --model local-completions --model_args model=llama2, base_url=http://localhost:8080/v1 - Network accessline 252
base_url=http://localhost:8080/v1 \ - Access to secretsline 269
[Credential-related source omitted] - Access to secretsline 271
[Credential-related source omitted] - Access to secretsline 277
[Credential-related source omitted] - Network accessline 300
model = MyCustomAPI( base_url="https://api.example.com/v1", - Network accessline 301
base_url="https://api.example.com/v1", - Access to secretsline 302
[Credential-related source omitted] - Access to secretsline 417
[Credential-related source omitted] - Access to secretsline 418
[Credential-related source omitted] - Network accessline 441
curl http://localhost:8000/v1/models - Network accessline 459
lm_eval --model local-completions --model_args base_url=http://api.example.com/v1, - Network accessline 461
base_url=http://api.example.com/v1,\ - Network accessline 468
lm_eval --model local-completions --model_args base_url=https://localhost:8000/v1, - Network accessline 470
base_url=https://localhost:8000/v1,\ - Network accessline 486
- OpenAI API: https://platform.openai.com/docs/api-reference - Network accessline 487
- Anthropic API: https://docs.anthropic.com/claude/reference
bundled/skills/evaluating-llms-harness/references/distributed-eval.md
bundled/skills/evaluating-machine-learning-models/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
bundled/skills/evaluating-machine-learning-models/assets/visualization_script.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/evaluating-machine-learning-models/scripts/data_loader.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/evaluating-machine-learning-models/scripts/evaluate_model.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/evaluating-machine-learning-models/scripts/metrics_calculator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/explaining-machine-learning-models/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
bundled/skills/explaining-machine-learning-models/scripts/data_preprocessing.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/explaining-machine-learning-models/scripts/explain_model.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/explaining-machine-learning-models/scripts/feature_importance.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/exploratory-data-analysis/references/chemistry_molecular_formats.md
- Network accessline 290
### .nc / .netcdf - Amber NetCDF Trajectory
bundled/skills/exploratory-data-analysis/references/general_scientific_formats.md
- Network accessline 376
### .nc / .netcdf - Network Common Data Form
bundled/skills/exploratory-data-analysis/scripts/eda_analyzer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/fda-database/SKILL.md
- Access to secretsline 44
[Credential-related source omitted] - Network accessline 64
Register at: https://open.fda.gov/apis/authentication/ - Access to secretsline 68
[Credential-related source omitted] - Access to secretsline 426
[Credential-related source omitted] - Network accessline 490
- **openFDA Homepage**: https://open.fda.gov/ - Network accessline 491
- **API Documentation**: https://open.fda.gov/apis/ - Network accessline 492
- **Interactive API Explorer**: https://open.fda.gov/apis/try-the-api/ - Network accessline 493
- **GitHub Repository**: https://github.com/FDA/openfda - Network accessline 494
- **Terms of Service**: https://open.fda.gov/terms/ - Network accessline 514
- **GitHub Issues**: https://github.com/FDA/openfda/issues
bundled/skills/fda-database/references/animal_veterinary.md
- Network accessline 13
**Endpoint**: `https://api.fda.gov/animalandveterinary/event.json` - Network accessline 93
[Credential-related source omitted] - Access to secretsline 93
[Credential-related source omitted] - Network accessline 94
url = "https://api.fda.gov/animalandveterinary/event.json" - Access to secretsline 98
[Credential-related source omitted] - Network accessline 103
response = requests.get(url, params=params) - Access to secretsline 110
[Credential-related source omitted] - Access to secretsline 119
[Credential-related source omitted] - Access to secretsline 128
[Credential-related source omitted] - Access to secretsline 138
[Credential-related source omitted] - Access to secretsline 147
[Credential-related source omitted] - Access to secretsline 156
[Credential-related source omitted] - Access to secretsline 182
[Credential-related source omitted] - Access to secretsline 189
[Credential-related source omitted] - Network accessline 197
url = "https://api.fda.gov/animalandveterinary/event.json" - Access to secretsline 199
[Credential-related source omitted] - Network accessline 204
response = requests.get(url, params=params) - Access to secretsline 246
[Credential-related source omitted] - Access to secretsline 252
[Credential-related source omitted] - Network accessline 261
url = "https://api.fda.gov/animalandveterinary/event.json" - Access to secretsline 263
[Credential-related source omitted] - Network accessline 268
response = requests.get(url, params=params) - Access to secretsline 299
[Credential-related source omitted] - Access to secretsline 306
[Credential-related source omitted] - Network accessline 313
url = "https://api.fda.gov/animalandveterinary/event.json" - Access to secretsline 318
[Credential-related source omitted] - Network accessline 323
response = requests.get(url, params=params) - Network accessline 373
- OpenFDA Animal & Veterinary API: https://open.fda.gov/apis/animalandveterinary/ - Network accessline 374
- FDA Center for Veterinary Medicine: https://www.fda.gov/animal-veterinary - Network accessline 375
- VeDDRA: https://www.veddra.org/
bundled/skills/fda-database/references/api_basics.md
- Network accessline 11
https://api.fda.gov/{category}/{endpoint}.json - Network accessline 14
Examples: - `https://api.fda.gov/drug/event.json` - Network accessline 15
- `https://api.fda.gov/drug/event.json` - Network accessline 16
- `https://api.fda.gov/device/510k.json` - Network accessline 17
- `https://api.fda.gov/food/enforcement.json` - Network accessline 29
**Registration**: Visit https://open.fda.gov/apis/authentication/ to sign up - Network accessline 44
[Credential-related source omitted] - Access to secretsline 44
[Credential-related source omitted] - Network accessline 45
url = "https://api.fda.gov/drug/event.json" - Access to secretsline 48
[Credential-related source omitted] - Network accessline 53
response = requests.get(url, params=params) - Network accessline 60
[Credential-related source omitted] - Access to secretsline 60
[Credential-related source omitted] - Network accessline 61
url = "https://api.fda.gov/drug/event.json" - Network accessline 68
[Credential-related source omitted] - Access to secretsline 68
[Credential-related source omitted] - Network accessline 84
response = requests.get(url, params=params) - Network accessline 104
for attempt in range(max_retries): try: response = requests.get(url, params=params) - Network accessline 105
try: response = requests.get(url, params=params) response.raise_for_status() - Network accessline 106
response = requests.get(url, params=params) - Access to secretsline 130
[Credential-related source omitted] - Access to secretsline 147
[Credential-related source omitted] - Access to secretsline 269
[Credential-related source omitted] - Access to secretsline 277
[Credential-related source omitted] - Network accessline 283
response = requests.get(url, params=params) - Network accessline 487
"""Safely call FDA API with comprehensive error handling.""" try: response = requests.get(url, params=params, timeout=30) - Network accessline 488
try: response = requests.get(url, params=params, timeout=30) response.raise_for_status() - Network accessline 489
response = requests.get(url, params=params, timeout=30) - Network accessline 582
# Make request response = requests.get(url, params=params) - Network accessline 583
response = requests.get(url, params=params) - Network accessline 610
# Remove requests older than 1 minute while self.requests and now - self.requests[0] > 60: self.requests.popleft() - Network accessline 612
self.requests.popleft() - Network accessline 617
if sleep_time > 0: time.sleep(sleep_time) self.requests.popleft() - Network accessline 619
self.requests.popleft() - Network accessline 621
self.requests.append(time.time()) - Network accessline 627
"""Make request with rate limiting.""" rate_limiter.wait_if_needed() return requests.get(url, params=params) - Network accessline 629
return requests.get(url, params=params) - Network accessline 668
"limit": 10 } results[drug] = requests.get(url, params=params).json() - Network accessline 670
results[drug] = requests.get(url, params=params).json() - Network accessline 675
- **openFDA Homepage**: https://open.fda.gov/ - Network accessline 676
- **API Documentation**: https://open.fda.gov/apis/ - Network accessline 677
- **Interactive API Explorer**: https://open.fda.gov/apis/try-the-api/ - Network accessline 678
- **Terms of Service**: https://open.fda.gov/terms/ - Network accessline 679
- **GitHub**: https://github.com/FDA/openfda - Network accessline 684
For questions or issues: - **GitHub Issues**: https://github.com/FDA/openfda/issues - Network accessline 685
- **GitHub Issues**: https://github.com/FDA/openfda/issues
bundled/skills/fda-database/references/devices.md
- Network accessline 21
**Endpoint**: `https://api.fda.gov/device/event.json` - Network accessline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Network accessline 54
url = "https://api.fda.gov/device/event.json" - Access to secretsline 58
[Credential-related source omitted] - Network accessline 63
response = requests.get(url, params=params) - Access to secretsline 70
[Credential-related source omitted] - Access to secretsline 79
[Credential-related source omitted] - Network accessline 88
**Endpoint**: `https://api.fda.gov/device/510k.json` - Access to secretsline 122
[Credential-related source omitted] - Network accessline 128
response = requests.get("https://api.fda.gov/device/510k.json", params=params) - Access to secretsline 134
[Credential-related source omitted] - Access to secretsline 143
[Credential-related source omitted] - Network accessline 151
**Endpoint**: `https://api.fda.gov/device/classification.json` - Access to secretsline 184
[Credential-related source omitted] - Network accessline 189
response = requests.get("https://api.fda.gov/device/classification.json", params=params) - Access to secretsline 195
[Credential-related source omitted] - Access to secretsline 204
[Credential-related source omitted] - Network accessline 212
**Endpoint**: `https://api.fda.gov/device/enforcement.json` - Access to secretsline 243
[Credential-related source omitted] - Network accessline 249
response = requests.get("https://api.fda.gov/device/enforcement.json", params=params) - Access to secretsline 255
[Credential-related source omitted] - Network accessline 263
**Endpoint**: `https://api.fda.gov/device/recall.json` - Access to secretsline 290
[Credential-related source omitted] - Network accessline 295
response = requests.get("https://api.fda.gov/device/recall.json", params=params) - Network accessline 300
**Endpoint**: `https://api.fda.gov/device/pma.json` - Access to secretsline 332
[Credential-related source omitted] - Network accessline 337
response = requests.get("https://api.fda.gov/device/pma.json", params=params) - Access to secretsline 343
[Credential-related source omitted] - Network accessline 351
**Endpoint**: `https://api.fda.gov/device/registrationlisting.json` - Access to secretsline 385
[Credential-related source omitted] - Network accessline 390
response = requests.get("https://api.fda.gov/device/registrationlisting.json", params=params) - Access to secretsline 396
[Credential-related source omitted] - Network accessline 404
**Endpoint**: `https://api.fda.gov/device/udi.json` - Access to secretsline 446
[Credential-related source omitted] - Network accessline 451
response = requests.get("https://api.fda.gov/device/udi.json", params=params) - Access to secretsline 457
[Credential-related source omitted] - Access to secretsline 466
[Credential-related source omitted] - Network accessline 474
**Endpoint**: `https://api.fda.gov/device/covid19serology.json` - Access to secretsline 500
[Credential-related source omitted] - Network accessline 505
response = requests.get("https://api.fda.gov/device/covid19serology.json", params=params) - Access to secretsline 511
[Credential-related source omitted] - Access to secretsline 522
[Credential-related source omitted] - Access to secretsline 528
[Credential-related source omitted] - Network accessline 535
# Search adverse events events_url = "https://api.fda.gov/device/event.json" - Network accessline 536
events_url = "https://api.fda.gov/device/event.json" - Access to secretsline 538
[Credential-related source omitted] - Network accessline 540
"limit": 10 } results["adverse_events"] = requests.get(events_url, params=events_params).json() - Network accessline 542
results["adverse_events"] = requests.get(events_url, params=events_params).json() - Network accessline 544
# Search 510(k) clearances fiveten_url = "https://api.fda.gov/device/510k.json" - Network accessline 545
fiveten_url = "https://api.fda.gov/device/510k.json" - Access to secretsline 547
[Credential-related source omitted] - Network accessline 549
"limit": 10 } results["510k_clearances"] = requests.get(fiveten_url, params=fiveten_params).json() - Network accessline 551
results["510k_clearances"] = requests.get(fiveten_url, params=fiveten_params).json() - Network accessline 553
# Search recalls recall_url = "https://api.fda.gov/device/enforcement.json" - Network accessline 554
recall_url = "https://api.fda.gov/device/enforcement.json" - Access to secretsline 556
[Credential-related source omitted] - Network accessline 558
"limit": 10 } results["recalls"] = requests.get(recall_url, params=recall_params).json() - Network accessline 560
results["recalls"] = requests.get(recall_url, params=recall_params).json() - Network accessline 562
# Search UDI udi_url = "https://api.fda.gov/device/udi.json" - Network accessline 563
udi_url = "https://api.fda.gov/device/udi.json" - Access to secretsline 565
[Credential-related source omitted] - Network accessline 567
"limit": 10 } results["udi"] = requests.get(udi_url, params=udi_params).json() - Network accessline 569
results["udi"] = requests.get(udi_url, params=udi_params).json() - Access to secretsline 577
[Credential-related source omitted] - Access to secretsline 583
[Credential-related source omitted] - Network accessline 586
Classification details dictionary """ url = "https://api.fda.gov/device/classification.json" - Network accessline 587
""" url = "https://api.fda.gov/device/classification.json" params = { - Network accessline 588
url = "https://api.fda.gov/device/classification.json" - Access to secretsline 590
[Credential-related source omitted] - Network accessline 595
response = requests.get(url, params=params) - Network accessline 628
- OpenFDA Device API Documentation: https://open.fda.gov/apis/device/ - Network accessline 629
- Device Classification Database: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpcd/classification.cfm - Network accessline 630
- GUDID: https://accessgudid.nlm.nih.gov/
bundled/skills/fda-database/references/drugs.md
- Network accessline 13
**Endpoint**: `https://api.fda.gov/drug/event.json` - Network accessline 39
[Credential-related source omitted] - Access to secretsline 39
[Credential-related source omitted] - Network accessline 40
url = "https://api.fda.gov/drug/event.json" - Access to secretsline 44
[Credential-related source omitted] - Network accessline 49
response = requests.get(url, params=params) - Access to secretsline 56
[Credential-related source omitted] - Network accessline 64
**Endpoint**: `https://api.fda.gov/drug/label.json` - Access to secretsline 95
[Credential-related source omitted] - Network accessline 100
response = requests.get("https://api.fda.gov/drug/label.json", params=params) - Access to secretsline 113
[Credential-related source omitted] - Network accessline 121
**Endpoint**: `https://api.fda.gov/drug/ndc.json` - Access to secretsline 152
[Credential-related source omitted] - Network accessline 157
response = requests.get("https://api.fda.gov/drug/ndc.json", params=params) - Access to secretsline 163
[Credential-related source omitted] - Access to secretsline 172
[Credential-related source omitted] - Network accessline 180
**Endpoint**: `https://api.fda.gov/drug/enforcement.json` - Access to secretsline 215
[Credential-related source omitted] - Network accessline 221
response = requests.get("https://api.fda.gov/drug/enforcement.json", params=params) - Access to secretsline 227
[Credential-related source omitted] - Access to secretsline 236
[Credential-related source omitted] - Network accessline 244
**Endpoint**: `https://api.fda.gov/drug/drugsfda.json` - Access to secretsline 277
[Credential-related source omitted] - Network accessline 282
response = requests.get("https://api.fda.gov/drug/drugsfda.json", params=params) - Access to secretsline 288
[Credential-related source omitted] - Access to secretsline 297
[Credential-related source omitted] - Network accessline 305
**Endpoint**: `https://api.fda.gov/drug/drugshortages.json` - Access to secretsline 333
[Credential-related source omitted] - Network accessline 338
response = requests.get("https://api.fda.gov/drug/drugshortages.json", params=params) - Access to secretsline 344
[Credential-related source omitted] - Access to secretsline 353
[Credential-related source omitted] - Network accessline 371
Args: endpoint: Full URL endpoint (e.g., "https://api.fda.gov/drug/event.json") - Network accessline 372
endpoint: Full URL endpoint (e.g., "https://api.fda.gov/drug/event.json") - Network accessline 379
for attempt in range(max_retries): try: response = requests.get(endpoint, params=params, timeout=30) - Network accessline 380
try: response = requests.get(endpoint, params=params, timeout=30) response.raise_for_status() - Network accessline 381
response = requests.get(endpoint, params=params, timeout=30) - Access to secretsline 408
[Credential-related source omitted] - Access to secretsline 415
[Credential-related source omitted] - Access to secretsline 427
[Credential-related source omitted] - Network accessline 465
- OpenFDA Drug API Documentation: https://open.fda.gov/apis/drug/ - Network accessline 466
- API Basics: See `api_basics.md` in this references directory - Python examples: See `scripts/fda_drug_query.py` - Field reference guides: Available at https://open.fda.gov/apis/drug/[endpoint]/searchable-fields/ - Network accessline 468
- Field reference guides: Available at https://open.fda.gov/apis/drug/[endpoint]/searchable-fields/
bundled/skills/fda-database/references/foods.md
- Network accessline 13
**Endpoint**: `https://api.fda.gov/food/event.json` - Network accessline 54
[Credential-related source omitted] - Access to secretsline 54
[Credential-related source omitted] - Network accessline 55
url = "https://api.fda.gov/food/event.json" - Access to secretsline 59
[Credential-related source omitted] - Network accessline 64
response = requests.get(url, params=params) - Access to secretsline 71
[Credential-related source omitted] - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 90
[Credential-related source omitted] - Network accessline 98
**Endpoint**: `https://api.fda.gov/food/enforcement.json` - Access to secretsline 146
[Credential-related source omitted] - Network accessline 152
response = requests.get("https://api.fda.gov/food/enforcement.json", params=params) - Access to secretsline 158
[Credential-related source omitted] - Access to secretsline 167
[Credential-related source omitted] - Access to secretsline 177
[Credential-related source omitted] - Access to secretsline 186
[Credential-related source omitted] - Access to secretsline 195
[Credential-related source omitted] - Access to secretsline 206
[Credential-related source omitted] - Access to secretsline 212
[Credential-related source omitted] - Network accessline 226
url = "https://api.fda.gov/food/enforcement.json" - Access to secretsline 231
[Credential-related source omitted] - Network accessline 236
response = requests.get(url, params=params) - Access to secretsline 250
[Credential-related source omitted] - Access to secretsline 256
[Credential-related source omitted] - Network accessline 264
url = "https://api.fda.gov/food/event.json" - Access to secretsline 266
[Credential-related source omitted] - Network accessline 271
response = requests.get(url, params=params) - Access to secretsline 304
[Credential-related source omitted] - Access to secretsline 310
[Credential-related source omitted] - Network accessline 319
url = "https://api.fda.gov/food/enforcement.json" - Access to secretsline 327
[Credential-related source omitted] - Network accessline 333
response = requests.get(url, params=params) - Network accessline 370
- OpenFDA Food API Documentation: https://open.fda.gov/apis/food/ - Network accessline 371
- CFSAN Adverse Event Reporting: https://www.fda.gov/food/compliance-enforcement-food/cfsan-adverse-event-reporting-system-caers - Network accessline 372
- Food Recalls: https://www.fda.gov/safety/recalls-market-withdrawals-safety-alerts
bundled/skills/fda-database/references/other.md
- Network accessline 13
**Endpoint**: `https://api.fda.gov/other/substance.json` - Network accessline 81
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Network accessline 82
url = "https://api.fda.gov/other/substance.json" - Access to secretsline 86
[Credential-related source omitted] - Network accessline 91
response = requests.get(url, params=params) - Access to secretsline 98
[Credential-related source omitted] - Access to secretsline 107
[Credential-related source omitted] - Access to secretsline 116
[Credential-related source omitted] - Access to secretsline 125
[Credential-related source omitted] - Access to secretsline 134
[Credential-related source omitted] - Network accessline 142
**Endpoint**: `https://api.fda.gov/other/nsde.json` - Access to secretsline 170
[Credential-related source omitted] - Network accessline 175
response = requests.get("https://api.fda.gov/other/nsde.json", params=params) - Access to secretsline 181
[Credential-related source omitted] - Access to secretsline 192
[Credential-related source omitted] - Access to secretsline 198
[Credential-related source omitted] - Network accessline 205
url = "https://api.fda.gov/other/substance.json" - Access to secretsline 207
[Credential-related source omitted] - Network accessline 212
response = requests.get(url, params=params) - Access to secretsline 256
[Credential-related source omitted] - Access to secretsline 262
[Credential-related source omitted] - Network accessline 269
url = "https://api.fda.gov/other/substance.json" - Access to secretsline 271
[Credential-related source omitted] - Network accessline 276
response = requests.get(url, params=params) - Access to secretsline 302
[Credential-related source omitted] - Access to secretsline 308
[Credential-related source omitted] - Network accessline 315
url = "https://api.fda.gov/other/substance.json" - Access to secretsline 317
[Credential-related source omitted] - Network accessline 322
response = requests.get(url, params=params) - Access to secretsline 351
[Credential-related source omitted] - Access to secretsline 357
[Credential-related source omitted] - Network accessline 364
# First search drug label database label_url = "https://api.fda.gov/drug/label.json" - Network accessline 365
label_url = "https://api.fda.gov/drug/label.json" - Access to secretsline 367
[Credential-related source omitted] - Network accessline 372
response = requests.get(label_url, params=label_params) - Access to secretsline 396
[Credential-related source omitted] - Network accessline 468
- FDA Substance Registration System: https://fdasis.nlm.nih.gov/srs/ - Network accessline 469
- UNII Search: https://precision.fda.gov/uniisearch - Network accessline 470
- OpenFDA Other APIs: https://open.fda.gov/apis/other/
bundled/skills/fda-database/scripts/fda_examples.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 299
[Credential-related source omitted] - Access to secretsline 301
[Credential-related source omitted] - Access to secretsline 302
[Credential-related source omitted] - Access to secretsline 304
[Credential-related source omitted] - Access to secretsline 307
[Credential-related source omitted]
bundled/skills/fda-database/scripts/fda_query.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 11
[Credential-related source omitted] - Network accessline 37
while self.requests and now - self.requests[0] > 60: self.requests.popleft() - Network accessline 38
self.requests.popleft() - Network accessline 44
print(f"Rate limit approaching. Waiting {sleep_time:.1f} seconds...") time.sleep(sleep_time) self.requests.popleft() - Network accessline 46
self.requests.popleft() - Network accessline 48
self.requests.append(time.time()) - Network accessline 87
BASE_URL = "https://api.fda.gov" - Access to secretsline 89
[Credential-related source omitted] - Access to secretsline 95
[Credential-related source omitted] - Access to secretsline 100
[Credential-related source omitted] - Access to secretsline 121
[Credential-related source omitted] - Access to secretsline 122
[Credential-related source omitted] - Network accessline 134
try: response = requests.get(url, params=params, timeout=30) - Network accessline 135
response = requests.get(url, params=params, timeout=30) - Access to secretsline 408
[Credential-related source omitted] - Access to secretsline 411
[Credential-related source omitted]
bundled/skills/figma-implement-design/LICENSE.txt
bundled/skills/figma-implement-design/SKILL.md
- Network accessline 15
- Figma MCP server must be connected and accessible - User must provide a Figma URL in the format: `https://figma.com/design/:fileKey/:fileName?node-id=1-2` - Network accessline 16
- User must provide a Figma URL in the format: `https://figma.com/design/:fileKey/:fileName?node-id=1-2` - Network accessline 30
1. Add the Figma MCP: - `codex mcp add figma --url https://mcp.figma.com/mcp` - Network accessline 31
- `codex mcp add figma --url https://mcp.figma.com/mcp` - Network accessline 47
**URL format:** `https://figma.com/design/:fileKey/:fileName?node-id=1-2` - Network accessline 58
- URL: `https://figma.com/design/kL9xQn2VwM8pYrTb4ZcHjF/DesignSystem?node-id=42-15` - Network accessline 175
User says: "Implement this Figma button component: https://figma.com/design/kL9xQn2VwM8pYrTb4ZcHjF/DesignSystem?node-id=42-15" - Network accessline 192
User says: "Build this dashboard: https://figma.com/design/pR8mNv5KqXzGwY2JtCfL4D/Dashboard?node-id=10-5" - Network accessline 264
- `references/figma-mcp-config.md` - Codex MCP config, environment, and troubleshooting reference. - `references/figma-tools-and-prompts.md` - Figma MCP tool catalog and prompt patterns. - [Figma MCP Server Documentation](https://developers - Network accessline 265
- `references/figma-tools-and-prompts.md` - Figma MCP tool catalog and prompt patterns. - [Figma MCP Server Documentation](https://developers.figma.com/docs/figma-mcp-server/) - [Figma MCP Server Tools and Prompts](https://developers.figma. - Network accessline 266
- [Figma MCP Server Documentation](https://developers.figma.com/docs/figma-mcp-server/) - Network accessline 267
- [Figma MCP Server Tools and Prompts](https://developers.figma.com/docs/figma-mcp-server/tools-and-prompts/) - Network accessline 268
- [Figma Variables and Design Tokens](https://help.figma.com/hc/en-us/articles/15339657135383-Guide-to-variables-in-Figma)
bundled/skills/figma-implement-design/agents/openai.yaml
bundled/skills/figma-implement-design/assets/figma-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/figma-implement-design/assets/icon.svg
bundled/skills/figma-implement-design/references/figma-mcp-config.md
bundled/skills/flashrag-evidence/scripts/flashrag_evidence.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/fluidsim/SKILL.md
- Network accessline 342
**Documentation**: https://fluidsim.readthedocs.io/
bundled/skills/fluidsim/references/advanced_features.md
bundled/skills/fred-economic-data/SKILL.md
- Network accessline 27
1. Create an account at https://fredaccount.stlouisfed.org - Access to secretsline 32
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Network accessline 72
[Credential-related source omitted] - Access to secretsline 72
[Credential-related source omitted] - Network accessline 73
BASE_URL = "https://api.stlouisfed.org/fred" - Network accessline 75
# Get series observations response = requests.get( - Network accessline 76
response = requests.get( - Access to secretsline 79
[Credential-related source omitted] - Network accessline 425
- **FRED Homepage**: https://fred.stlouisfed.org/ - Network accessline 426
- **API Documentation**: https://fred.stlouisfed.org/docs/api/fred/ - Network accessline 427
- **GeoFRED Maps**: https://geofred.stlouisfed.org/ - Network accessline 428
- **ALFRED (Vintage Data)**: https://alfred.stlouisfed.org/ - Network accessline 429
- **Terms of Use**: https://fred.stlouisfed.org/legal/
bundled/skills/fred-economic-data/references/api_basics.md
- Network accessline 6
https://api.stlouisfed.org/fred/ - Network accessline 11
https://api.stlouisfed.org/geofred/ - Access to secretsline 19
[Credential-related source omitted] - Network accessline 24
1. Create account at https://fredaccount.stlouisfed.org - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 128
[Credential-related source omitted] - Access to secretsline 135
[Credential-related source omitted] - Network accessline 181
response = requests.get( - Network accessline 182
"https://api.stlouisfed.org/fred/series/observations", - Access to secretsline 184
[Credential-related source omitted] - Access to secretsline 206
[Credential-related source omitted] - Access to secretsline 211
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/categories.md
- Network accessline 34
**URL:** `https://api.stlouisfed.org/fred/category` - Access to secretsline 40
[Credential-related source omitted] - Network accessline 52
# Get root category response = requests.get( - Network accessline 53
response = requests.get( - Network accessline 54
"https://api.stlouisfed.org/fred/category", - Access to secretsline 56
[Credential-related source omitted] - Network accessline 62
# Get Trade Balance category response = requests.get( - Network accessline 63
response = requests.get( - Network accessline 64
"https://api.stlouisfed.org/fred/category", - Access to secretsline 66
[Credential-related source omitted] - Network accessline 93
**URL:** `https://api.stlouisfed.org/fred/category/children` - Access to secretsline 99
[Credential-related source omitted] - Network accessline 113
# Get children of International Trade category (13) response = requests.get( - Network accessline 114
response = requests.get( - Network accessline 115
"https://api.stlouisfed.org/fred/category/children", - Access to secretsline 117
[Credential-related source omitted] - Network accessline 144
**URL:** `https://api.stlouisfed.org/fred/category/related` - Access to secretsline 150
[Credential-related source omitted] - Network accessline 166
response = requests.get( - Network accessline 167
"https://api.stlouisfed.org/fred/category/related", - Access to secretsline 169
[Credential-related source omitted] - Network accessline 193
**URL:** `https://api.stlouisfed.org/fred/category/series` - Access to secretsline 199
[Credential-related source omitted] - Network accessline 236
# Get series in Trade Balance category with monthly frequency response = requests.get( - Network accessline 237
response = requests.get( - Network accessline 238
"https://api.stlouisfed.org/fred/category/series", - Access to secretsline 240
[Credential-related source omitted] - Network accessline 280
**URL:** `https://api.stlouisfed.org/fred/category/tags` - Access to secretsline 286
[Credential-related source omitted] - Network accessline 319
# Get frequency tags for Trade Balance category response = requests.get( - Network accessline 320
response = requests.get( - Network accessline 321
"https://api.stlouisfed.org/fred/category/tags", - Access to secretsline 323
[Credential-related source omitted] - Network accessline 349
**URL:** `https://api.stlouisfed.org/fred/category/related_tags` - Access to secretsline 355
[Credential-related source omitted] - Network accessline 377
# Get tags related to 'services' and 'quarterly' in Trade Balance category response = requests.get( - Network accessline 378
response = requests.get( - Network accessline 379
"https://api.stlouisfed.org/fred/category/related_tags", - Access to secretsline 381
[Credential-related source omitted] - Access to secretsline 413
[Credential-related source omitted] - Network accessline 418
# Get children response = requests.get( - Network accessline 419
response = requests.get( - Network accessline 420
"https://api.stlouisfed.org/fred/category/children", - Access to secretsline 422
[Credential-related source omitted] - Access to secretsline 434
[Credential-related source omitted] - Access to secretsline 441
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/geofred.md
- Network accessline 15
https://api.stlouisfed.org/geofred/ - Network accessline 33
**URL:** `https://api.stlouisfed.org/geofred/shapes/file` - Access to secretsline 39
[Credential-related source omitted] - Network accessline 64
# Get US state boundaries response = requests.get( - Network accessline 65
response = requests.get( - Network accessline 66
"https://api.stlouisfed.org/geofred/shapes/file", - Access to secretsline 68
[Credential-related source omitted] - Network accessline 112
# Get shapes shapes = requests.get( - Network accessline 113
shapes = requests.get( - Network accessline 114
"https://api.stlouisfed.org/geofred/shapes/file", - Access to secretsline 115
[Credential-related source omitted] - Network accessline 118
# Get unemployment data data = requests.get( - Network accessline 119
data = requests.get( - Network accessline 120
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 122
[Credential-related source omitted] - Network accessline 152
**URL:** `https://api.stlouisfed.org/geofred/series/group` - Access to secretsline 158
[Credential-related source omitted] - Network accessline 170
# Get info about Texas employment series response = requests.get( - Network accessline 171
response = requests.get( - Network accessline 172
"https://api.stlouisfed.org/geofred/series/group", - Access to secretsline 174
[Credential-related source omitted] - Network accessline 219
**URL:** `https://api.stlouisfed.org/geofred/series/data` - Access to secretsline 225
[Credential-related source omitted] - Network accessline 241
# Get Wisconsin per capita income data response = requests.get( - Network accessline 242
response = requests.get( - Network accessline 243
"https://api.stlouisfed.org/geofred/series/data", - Access to secretsline 245
[Credential-related source omitted] - Network accessline 290
**URL:** `https://api.stlouisfed.org/geofred/regional/data` - Access to secretsline 296
[Credential-related source omitted] - Network accessline 339
response = requests.get( - Network accessline 340
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 342
[Credential-related source omitted] - Network accessline 387
response = requests.get( - Network accessline 388
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 390
[Credential-related source omitted] - Network accessline 405
response = requests.get( - Network accessline 406
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 408
[Credential-related source omitted] - Access to secretsline 438
[Credential-related source omitted] - Network accessline 449
for name, params in indicators.items(): response = requests.get( - Network accessline 450
response = requests.get( - Network accessline 451
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 453
[Credential-related source omitted] - Access to secretsline 478
[Credential-related source omitted] - Access to secretsline 487
[Credential-related source omitted] - Network accessline 490
# Get shapes shapes = requests.get( - Network accessline 491
shapes = requests.get( - Network accessline 492
f"https://api.stlouisfed.org/geofred/shapes/file", - Access to secretsline 493
[Credential-related source omitted] - Network accessline 496
# Get data response = requests.get( - Network accessline 497
response = requests.get( - Network accessline 498
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 500
[Credential-related source omitted] - Access to secretsline 533
[Credential-related source omitted] - Access to secretsline 544
[Credential-related source omitted] - Network accessline 557
response = requests.get( - Network accessline 558
"https://api.stlouisfed.org/geofred/regional/data", - Access to secretsline 560
[Credential-related source omitted] - Access to secretsline 582
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/releases.md
- Network accessline 33
**URL:** `https://api.stlouisfed.org/fred/releases` - Access to secretsline 39
[Credential-related source omitted] - Network accessline 56
response = requests.get( - Network accessline 57
"https://api.stlouisfed.org/fred/releases", - Access to secretsline 59
[Credential-related source omitted] - Network accessline 80
"name": "Advance Monthly Sales for Retail and Food Services", "press_release": true, "link": "http://www.census.gov/retail/" - Network accessline 81
"press_release": true, "link": "http://www.census.gov/retail/" }, - Network accessline 82
"link": "http://www.census.gov/retail/" - Network accessline 88
"name": "Gross Domestic Product", "press_release": true, "link": "http://www.bea.gov/national/index.htm" - Network accessline 89
"press_release": true, "link": "http://www.bea.gov/national/index.htm" } - Network accessline 90
"link": "http://www.bea.gov/national/index.htm" - Network accessline 102
**URL:** `https://api.stlouisfed.org/fred/releases/dates` - Access to secretsline 108
[Credential-related source omitted] - Network accessline 134
response = requests.get( - Network accessline 135
"https://api.stlouisfed.org/fred/releases/dates", - Access to secretsline 137
[Credential-related source omitted] - Network accessline 176
**URL:** `https://api.stlouisfed.org/fred/release` - Access to secretsline 182
[Credential-related source omitted] - Network accessline 196
# Get GDP release info response = requests.get( - Network accessline 197
response = requests.get( - Network accessline 198
"https://api.stlouisfed.org/fred/release", - Access to secretsline 200
[Credential-related source omitted] - Network accessline 218
"name": "Gross Domestic Product", "press_release": true, "link": "http://www.bea.gov/national/index.htm" - Network accessline 219
"press_release": true, "link": "http://www.bea.gov/national/index.htm" } - Network accessline 220
"link": "http://www.bea.gov/national/index.htm" - Network accessline 232
**URL:** `https://api.stlouisfed.org/fred/release/dates` - Access to secretsline 238
[Credential-related source omitted] - Network accessline 256
# Get historical GDP release dates response = requests.get( - Network accessline 257
response = requests.get( - Network accessline 258
"https://api.stlouisfed.org/fred/release/dates", - Access to secretsline 260
[Credential-related source omitted] - Network accessline 292
**URL:** `https://api.stlouisfed.org/fred/release/series` - Access to secretsline 298
[Credential-related source omitted] - Network accessline 335
# Get quarterly series from GDP release response = requests.get( - Network accessline 336
response = requests.get( - Network accessline 337
"https://api.stlouisfed.org/fred/release/series", - Access to secretsline 339
[Credential-related source omitted] - Network accessline 389
**URL:** `https://api.stlouisfed.org/fred/release/sources` - Access to secretsline 395
[Credential-related source omitted] - Network accessline 409
response = requests.get( - Network accessline 410
"https://api.stlouisfed.org/fred/release/sources", - Access to secretsline 412
[Credential-related source omitted] - Network accessline 429
"realtime_end": "2023-08-14", "name": "U.S. Department of Commerce: Bureau of Economic Analysis", "link": "http://www.bea.gov/" - Network accessline 430
"name": "U.S. Department of Commerce: Bureau of Economic Analysis", "link": "http://www.bea.gov/" }, - Network accessline 431
"link": "http://www.bea.gov/" - Network accessline 436
"realtime_end": "2023-08-14", "name": "U.S. Department of Commerce: Census Bureau", "link": "http://www.census.gov/" - Network accessline 437
"name": "U.S. Department of Commerce: Census Bureau", "link": "http://www.census.gov/" } - Network accessline 438
"link": "http://www.census.gov/" - Network accessline 450
**URL:** `https://api.stlouisfed.org/fred/release/tags` - Access to secretsline 456
[Credential-related source omitted] - Network accessline 477
response = requests.get( - Network accessline 478
"https://api.stlouisfed.org/fred/release/tags", - Access to secretsline 480
[Credential-related source omitted] - Network accessline 494
**URL:** `https://api.stlouisfed.org/fred/release/related_tags` - Access to secretsline 500
[Credential-related source omitted] - Network accessline 523
**URL:** `https://api.stlouisfed.org/fred/release/tables` - Access to secretsline 529
[Credential-related source omitted] - Network accessline 555
# Get GDP release table structure response = requests.get( - Network accessline 556
response = requests.get( - Network accessline 557
"https://api.stlouisfed.org/fred/release/tables", - Access to secretsline 559
[Credential-related source omitted] - Access to secretsline 611
[Credential-related source omitted] - Network accessline 616
response = requests.get( - Network accessline 617
"https://api.stlouisfed.org/fred/releases/dates", - Access to secretsline 619
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/series.md
- Network accessline 24
**URL:** `https://api.stlouisfed.org/fred/series` - Access to secretsline 30
[Credential-related source omitted] - Network accessline 59
response = requests.get( - Network accessline 60
"https://api.stlouisfed.org/fred/series", - Access to secretsline 62
[Credential-related source omitted] - Network accessline 96
**URL:** `https://api.stlouisfed.org/fred/series/observations` - Access to secretsline 102
[Credential-related source omitted] - Network accessline 161
# Get quarterly GDP with percent change transformation response = requests.get( - Network accessline 162
response = requests.get( - Network accessline 163
"https://api.stlouisfed.org/fred/series/observations", - Access to secretsline 165
[Credential-related source omitted] - Network accessline 213
**URL:** `https://api.stlouisfed.org/fred/series/categories` - Access to secretsline 219
[Credential-related source omitted] - Network accessline 225
response = requests.get( - Network accessline 226
"https://api.stlouisfed.org/fred/series/categories", - Access to secretsline 228
[Credential-related source omitted] - Network accessline 252
**URL:** `https://api.stlouisfed.org/fred/series/release` - Access to secretsline 258
[Credential-related source omitted] - Network accessline 264
response = requests.get( - Network accessline 265
"https://api.stlouisfed.org/fred/series/release", - Access to secretsline 267
[Credential-related source omitted] - Network accessline 281
"name": "Gross Domestic Product", "press_release": true, "link": "http://www.bea.gov/national/index.htm" - Network accessline 282
"press_release": true, "link": "http://www.bea.gov/national/index.htm" } - Network accessline 283
"link": "http://www.bea.gov/national/index.htm" - Network accessline 295
**URL:** `https://api.stlouisfed.org/fred/series/search` - Access to secretsline 301
[Credential-related source omitted] - Network accessline 338
# Search for inflation-related series response = requests.get( - Network accessline 339
response = requests.get( - Network accessline 340
"https://api.stlouisfed.org/fred/series/search", - Access to secretsline 342
[Credential-related source omitted] - Network accessline 380
**URL:** `https://api.stlouisfed.org/fred/series/tags` - Access to secretsline 386
[Credential-related source omitted] - Network accessline 400
response = requests.get( - Network accessline 401
"https://api.stlouisfed.org/fred/series/tags", - Access to secretsline 403
[Credential-related source omitted] - Network accessline 428
**URL:** `https://api.stlouisfed.org/fred/series/updates` - Access to secretsline 434
[Credential-related source omitted] - Network accessline 452
response = requests.get( - Network accessline 453
"https://api.stlouisfed.org/fred/series/updates", - Access to secretsline 455
[Credential-related source omitted] - Network accessline 469
**URL:** `https://api.stlouisfed.org/fred/series/vintagedates` - Access to secretsline 475
[Credential-related source omitted] - Network accessline 492
response = requests.get( - Network accessline 493
"https://api.stlouisfed.org/fred/series/vintagedates", - Access to secretsline 495
[Credential-related source omitted] - Network accessline 521
**URL:** `https://api.stlouisfed.org/fred/series/search/tags` - Access to secretsline 527
[Credential-related source omitted] - Network accessline 549
**URL:** `https://api.stlouisfed.org/fred/series/search/related_tags` - Access to secretsline 555
[Credential-related source omitted] - Network accessline 575
response = requests.get( - Network accessline 576
"https://api.stlouisfed.org/fred/series/search/related_tags", - Access to secretsline 578
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/sources.md
- Network accessline 27
**URL:** `https://api.stlouisfed.org/fred/sources` - Access to secretsline 33
[Credential-related source omitted] - Network accessline 50
response = requests.get( - Network accessline 51
"https://api.stlouisfed.org/fred/sources", - Access to secretsline 53
[Credential-related source omitted] - Network accessline 73
"realtime_end": "2023-08-14", "name": "Board of Governors of the Federal Reserve System (US)", "link": "http://www.federalreserve.gov/" - Network accessline 74
"name": "Board of Governors of the Federal Reserve System (US)", "link": "http://www.federalreserve.gov/" }, - Network accessline 75
"link": "http://www.federalreserve.gov/" - Network accessline 80
"realtime_end": "2023-08-14", "name": "Federal Reserve Bank of Philadelphia", "link": "http://www.philadelphiafed.org/" - Network accessline 81
"name": "Federal Reserve Bank of Philadelphia", "link": "http://www.philadelphiafed.org/" }, - Network accessline 82
"link": "http://www.philadelphiafed.org/" - Network accessline 87
"realtime_end": "2023-08-14", "name": "U.S. Department of Commerce: Bureau of Economic Analysis", "link": "http://www.bea.gov/" - Network accessline 88
"name": "U.S. Department of Commerce: Bureau of Economic Analysis", "link": "http://www.bea.gov/" }, - Network accessline 89
"link": "http://www.bea.gov/" - Network accessline 94
"realtime_end": "2023-08-14", "name": "U.S. Bureau of Labor Statistics", "link": "http://www.bls.gov/" - Network accessline 95
"name": "U.S. Bureau of Labor Statistics", "link": "http://www.bls.gov/" } - Network accessline 96
"link": "http://www.bls.gov/" - Network accessline 108
**URL:** `https://api.stlouisfed.org/fred/source` - Access to secretsline 114
[Credential-related source omitted] - Network accessline 128
# Get Federal Reserve Board info response = requests.get( - Network accessline 129
response = requests.get( - Network accessline 130
"https://api.stlouisfed.org/fred/source", - Access to secretsline 132
[Credential-related source omitted] - Network accessline 149
"realtime_end": "2023-08-14", "name": "Board of Governors of the Federal Reserve System (US)", "link": "http://www.federalreserve.gov/" - Network accessline 150
"name": "Board of Governors of the Federal Reserve System (US)", "link": "http://www.federalreserve.gov/" } - Network accessline 151
"link": "http://www.federalreserve.gov/" - Network accessline 163
**URL:** `https://api.stlouisfed.org/fred/source/releases` - Access to secretsline 169
[Credential-related source omitted] - Network accessline 187
# Get releases from the Federal Reserve Board response = requests.get( - Network accessline 188
response = requests.get( - Network accessline 189
"https://api.stlouisfed.org/fred/source/releases", - Access to secretsline 191
[Credential-related source omitted] - Network accessline 213
"name": "G.17 Industrial Production and Capacity Utilization", "press_release": true, "link": "http://www.federalreserve.gov/releases/g17/" - Network accessline 214
"press_release": true, "link": "http://www.federalreserve.gov/releases/g17/" }, - Network accessline 215
"link": "http://www.federalreserve.gov/releases/g17/" - Network accessline 221
"name": "G.19 Consumer Credit", "press_release": true, "link": "http://www.federalreserve.gov/releases/g19/" - Network accessline 222
"press_release": true, "link": "http://www.federalreserve.gov/releases/g19/" }, - Network accessline 223
"link": "http://www.federalreserve.gov/releases/g19/" - Network accessline 229
"name": "H.3 Aggregate Reserves of Depository Institutions", "press_release": true, "link": "http://www.federalreserve.gov/releases/h3/" - Network accessline 230
"press_release": true, "link": "http://www.federalreserve.gov/releases/h3/" }, - Network accessline 231
"link": "http://www.federalreserve.gov/releases/h3/" - Network accessline 237
"name": "H.6 Money Stock Measures", "press_release": true, "link": "http://www.federalreserve.gov/releases/h6/" - Network accessline 238
"press_release": true, "link": "http://www.federalreserve.gov/releases/h6/" } - Network accessline 239
"link": "http://www.federalreserve.gov/releases/h6/" - Access to secretsline 272
[Credential-related source omitted] - Network accessline 275
# Get source info source_info = requests.get( - Network accessline 276
source_info = requests.get( - Network accessline 277
"https://api.stlouisfed.org/fred/source", - Access to secretsline 279
[Credential-related source omitted] - Network accessline 285
# Get all releases from this source releases = requests.get( - Network accessline 286
releases = requests.get( - Network accessline 287
"https://api.stlouisfed.org/fred/source/releases", - Access to secretsline 289
[Credential-related source omitted] - Access to secretsline 301
[Credential-related source omitted] - Access to secretsline 307
[Credential-related source omitted] - Network accessline 311
for sid in source_ids: response = requests.get( - Network accessline 312
response = requests.get( - Network accessline 313
"https://api.stlouisfed.org/fred/source/releases", - Access to secretsline 315
[Credential-related source omitted] - Network accessline 322
# Get source name source_resp = requests.get( - Network accessline 323
source_resp = requests.get( - Network accessline 324
"https://api.stlouisfed.org/fred/source", - Access to secretsline 326
[Credential-related source omitted] - Access to secretsline 342
[Credential-related source omitted] - Access to secretsline 348
[Credential-related source omitted] - Network accessline 351
response = requests.get( - Network accessline 352
"https://api.stlouisfed.org/fred/sources", - Access to secretsline 354
[Credential-related source omitted] - Network accessline 362
for source in sources: # Get releases for each source releases_resp = requests.get( - Network accessline 363
# Get releases for each source releases_resp = requests.get( "https://api.stlouisfed.org/fred/source/releases", - Network accessline 364
releases_resp = requests.get( - Network accessline 365
"https://api.stlouisfed.org/fred/source/releases", - Access to secretsline 367
[Credential-related source omitted]
bundled/skills/fred-economic-data/references/tags.md
- Network accessline 32
**URL:** `https://api.stlouisfed.org/fred/tags` - Access to secretsline 38
[Credential-related source omitted] - Network accessline 58
response = requests.get( - Network accessline 59
"https://api.stlouisfed.org/fred/tags", - Access to secretsline 61
[Credential-related source omitted] - Network accessline 111
response = requests.get( - Network accessline 112
"https://api.stlouisfed.org/fred/tags", - Access to secretsline 114
[Credential-related source omitted] - Network accessline 126
# Find tags related to inflation response = requests.get( - Network accessline 127
response = requests.get( - Network accessline 128
"https://api.stlouisfed.org/fred/tags", - Access to secretsline 130
[Credential-related source omitted] - Network accessline 145
**URL:** `https://api.stlouisfed.org/fred/related_tags` - Access to secretsline 151
[Credential-related source omitted] - Network accessline 172
response = requests.get( - Network accessline 173
"https://api.stlouisfed.org/fred/related_tags", - Access to secretsline 175
[Credential-related source omitted] - Network accessline 220
response = requests.get( - Network accessline 221
"https://api.stlouisfed.org/fred/related_tags", - Access to secretsline 223
[Credential-related source omitted] - Network accessline 239
**URL:** `https://api.stlouisfed.org/fred/tags/series` - Access to secretsline 245
[Credential-related source omitted] - Network accessline 279
response = requests.get( - Network accessline 280
"https://api.stlouisfed.org/fred/tags/series", - Access to secretsline 282
[Credential-related source omitted] - Network accessline 328
response = requests.get( - Network accessline 329
"https://api.stlouisfed.org/fred/tags/series", - Access to secretsline 331
[Credential-related source omitted] - Network accessline 344
response = requests.get( - Network accessline 345
"https://api.stlouisfed.org/fred/tags/series", - Access to secretsline 347
[Credential-related source omitted] - Access to secretsline 408
[Credential-related source omitted] - Network accessline 411
# Step 1: Find tags matching the topic response = requests.get( - Network accessline 412
response = requests.get( - Network accessline 413
"https://api.stlouisfed.org/fred/tags", - Access to secretsline 415
[Credential-related source omitted] - Network accessline 428
# Step 2: Find related tags top_tag = initial_tags[0]["name"] response = requests.get( - Network accessline 429
top_tag = initial_tags[0]["name"] response = requests.get( "https://api.stlouisfed.org/fred/related_tags", - Network accessline 430
response = requests.get( - Network accessline 431
"https://api.stlouisfed.org/fred/related_tags", - Access to secretsline 433
[Credential-related source omitted] - Access to secretsline 449
[Credential-related source omitted] - Access to secretsline 455
[Credential-related source omitted] - Network accessline 464
response = requests.get( - Network accessline 465
"https://api.stlouisfed.org/fred/tags/series", - Access to secretsline 467
[Credential-related source omitted] - Access to secretsline 480
[Credential-related source omitted]
bundled/skills/fred-economic-data/scripts/fred_examples.py
- Executable scriptline 1
Executable file - Access to secretsline 321
[Credential-related source omitted] - Access to secretsline 322
[Credential-related source omitted] - Network accessline 323
[Credential-related source omitted] - Access to secretsline 323
[Credential-related source omitted] - Network accessline 324
print("\nTo get an API key:") print(" 1. Create account at https://fredaccount.stlouisfed.org") print(" 2. Request API key from your account dashboard") - Network accessline 325
print(" 1. Create account at https://fredaccount.stlouisfed.org") - Access to secretsline 328
[Credential-related source omitted]
bundled/skills/fred-economic-data/scripts/fred_query.py
- Executable scriptline 1
Executable file - Access to secretsline 19
[Credential-related source omitted] - Network accessline 24
BASE_URL = "https://api.stlouisfed.org/fred" - Network accessline 25
GEOFRED_URL = "https://api.stlouisfed.org/geofred" - Access to secretsline 29
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted] - Access to secretsline 43
[Credential-related source omitted] - Access to secretsline 44
[Credential-related source omitted] - Access to secretsline 46
[Credential-related source omitted] - Access to secretsline 62
[Credential-related source omitted] - Network accessline 73
for attempt in range(self.max_retries): try: response = requests.get(url, params=params, timeout=30) - Network accessline 75
response = requests.get(url, params=params, timeout=30) - Access to secretsline 561
[Credential-related source omitted] - Access to secretsline 567
[Credential-related source omitted] - Access to secretsline 573
[Credential-related source omitted] - Access to secretsline 581
[Credential-related source omitted] - Access to secretsline 582
[Credential-related source omitted] - Access to secretsline 583
[Credential-related source omitted] - Access to secretsline 590
[Credential-related source omitted]
bundled/skills/generate-image/SKILL.md
- Access to secretsline 51
[Credential-related source omitted] - Network accessline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 54
[Credential-related source omitted] - Network accessline 55
- Get an API key from: https://openrouter.ai/keys - Access to secretsline 120
[Credential-related source omitted] - Network accessline 166
- For image editing, the input image is encoded as base64 and sent to the model - Supported input image formats: PNG, JPEG, GIF, WebP - Check OpenRouter pricing for cost information: https://openrouter.ai/models - Network accessline 168
- Check OpenRouter pricing for cost information: https://openrouter.ai/models
bundled/skills/generate-image/scripts/generate_image.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 23
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 27
[Credential-related source omitted] - Access to secretsline 31
[Credential-related source omitted] - Access to secretsline 32
[Credential-related source omitted] - Access to secretsline 33
[Credential-related source omitted] - Access to secretsline 34
[Credential-related source omitted] - Possible obfuscationline 70
image_data = base64.b64decode(base64_data) - Access to secretsline 79
[Credential-related source omitted] - Access to secretsline 89
[Credential-related source omitted] - Access to secretsline 102
[Credential-related source omitted] - Access to secretsline 103
[Credential-related source omitted] - Access to secretsline 105
[Credential-related source omitted] - Access to secretsline 106
[Credential-related source omitted] - Access to secretsline 107
[Credential-related source omitted] - Access to secretsline 108
[Credential-related source omitted] - Network accessline 109
[Credential-related source omitted] - Network accessline 110
[Credential-related source omitted] - Access to secretsline 110
[Credential-related source omitted] - Network accessline 111
print("\nGet your API key from: https://openrouter.ai/keys") - Network accessline 144
response = requests.post( - Network accessline 145
url="https://openrouter.ai/api/v1/chat/completions", - Access to secretsline 147
[Credential-related source omitted] - Access to secretsline 266
[Credential-related source omitted] - Access to secretsline 275
[Credential-related source omitted]
bundled/skills/generating-test-reports/scripts/aggregate_results.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/generating-test-reports/scripts/analyze_trends.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/generating-test-reports/scripts/generate_report.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/geo-database/SKILL.md
- Network accessline 398
**Using wget or curl for Downloads:** - Network accessline 401
# Download series matrix file wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/matrix/GSE123456_series_matrix.txt.gz - Network accessline 402
wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/matrix/GSE123456_series_matrix.txt.gz - Network accessline 404
# Download all supplementary files for a series wget -r -np -nd ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/suppl/ - Network accessline 405
wget -r -np -nd ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/suppl/ - Network accessline 407
# Download SOFT format family file wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/soft/GSE123456_family.soft.gz - Network accessline 408
wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE123nnn/GSE123456/soft/GSE123456_family.soft.gz - Network accessline 673
# Optional: Set API key for increased rate limits # Get your API key from: https://www.ncbi.nlm.nih.gov/account/ - Network accessline 674
# Get your API key from: https://www.ncbi.nlm.nih.gov/account/ - Access to secretsline 675
[Credential-related source omitted] - Network accessline 725
- Web-based statistical analysis tool integrated into GEO - Accessible at: https://www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSExxxxx - Network accessline 726
- Accessible at: https://www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSExxxxx - Network accessline 739
- No rate limits for FTP downloads - Preferred method for bulk downloads - Can download entire directories with wget -r - Network accessline 741
- Can download entire directories with wget -r - Network accessline 805
- **GEO Website:** https://www.ncbi.nlm.nih.gov/geo/ - Network accessline 806
- **GEO Submission Guidelines:** https://www.ncbi.nlm.nih.gov/geo/info/submission.html - Network accessline 807
- **GEOparse Documentation:** https://geoparse.readthedocs.io/ - Network accessline 808
- **E-utilities Documentation:** https://www.ncbi.nlm.nih.gov/books/NBK25501/ - Network accessline 809
- **GEO FTP Site:** ftp://ftp.ncbi.nlm.nih.gov/geo/ - **GEO2R Tool:** https://www.ncbi.nlm.nih.gov/geo/geo2r/ - **NCBI API Keys:** https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/ - Network accessline 810
- **GEO2R Tool:** https://www.ncbi.nlm.nih.gov/geo/geo2r/ - Network accessline 811
- **NCBI API Keys:** https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/ - Network accessline 812
- **Biopython Tutorial:** https://biopython.org/DIST/docs/tutorial/Tutorial.html
bundled/skills/geo-database/references/geo_reference.md
- Network accessline 12
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ - Network accessline 23
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi - Network accessline 68
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi - Network accessline 108
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi - Network accessline 138
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi - Network accessline 173
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/epost.fcgi - Network accessline 202
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/einfo.fcgi - Network accessline 293
!Database_name = Gene Expression Omnibus (GEO) !Database_institute = NCBI NLM NIH !Database_web_link = http://www.ncbi.nlm.nih.gov/geo - Network accessline 294
!Database_institute = NCBI NLM NIH !Database_web_link = http://www.ncbi.nlm.nih.gov/geo !Database_email = geo@ncbi.nlm.nih.gov - Network accessline 295
!Database_web_link = http://www.ncbi.nlm.nih.gov/geo - Network accessline 433
<?xml version="1.0" encoding="UTF-8"?> <MINiML xmlns="http://www.ncbi.nlm.nih.gov/geo/info/MINiML" - Network accessline 434
<MINiML xmlns="http://www.ncbi.nlm.nih.gov/geo/info/MINiML" - Network accessline 435
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
bundled/skills/geomaster/SKILL.md
bundled/skills/geomaster/references/big-data.md
- Network accessline 141
# Search catalog catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", - Network accessline 142
catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", modifier=planetary_computer.sign_inplace, - Network accessline 143
"https://planetarycomputer.microsoft.com/api/stac/v1",
bundled/skills/geomaster/references/data-sources.md
- Network accessline 9
| Platform | Resolution | Coverage | Access | |----------|------------|----------|--------| | **Sentinel-2** | 10-60m | Global | https://scihub.copernicus.eu/ | - Network accessline 10
|----------|------------|----------|--------| | **Sentinel-2** | 10-60m | Global | https://scihub.copernicus.eu/ | | **Sentinel-1** | 5-40m (SAR) | Global | https://scihub.copernicus.eu/ | - Network accessline 11
| **Sentinel-2** | 10-60m | Global | https://scihub.copernicus.eu/ | - Network accessline 12
| **Sentinel-1** | 5-40m (SAR) | Global | https://scihub.copernicus.eu/ | - Network accessline 13
| **Sentinel-3** | 300m-1km | Global | https://scihub.copernicus.eu/ | - Network accessline 14
| **Sentinel-5P** | Various | Global | https://scihub.copernicus.eu/ | - Network accessline 20
api = SentinelAPI('user', 'password', 'https://scihub.copernicus.eu/dhus') - Network accessline 34
| Platform | Resolution | Coverage | Access | |----------|------------|----------|--------| | **Landsat 9** | 30m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 35
|----------|------------|----------|--------| | **Landsat 9** | 30m | Global | https://earthexplorer.usgs.gov/ | | **Landsat 8** | 30m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 36
| **Landsat 9** | 30m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 37
| **Landsat 8** | 30m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 38
| **Landsat 7** | 15-60m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 39
| **Landsat 5-7** | 30-60m | Global | https://earthexplorer.usgs.gov/ | - Network accessline 52
| Dataset | Resolution | Coverage | Source | |---------|------------|----------|--------| | **AW3D30** | 30m | Global | https://www.eorc.jaxa.jp/ALOS/en/aw3d30/ | - Network accessline 53
|---------|------------|----------|--------| | **AW3D30** | 30m | Global | https://www.eorc.jaxa.jp/ALOS/en/aw3d30/ | | **SRTM** | 30m | 56°S-60°N | https://www.usgs.gov/ | - Network accessline 54
| **AW3D30** | 30m | Global | https://www.eorc.jaxa.jp/ALOS/en/aw3d30/ | - Network accessline 55
| **SRTM** | 30m | 56°S-60°N | https://www.usgs.gov/ | - Network accessline 56
| **ASTER GDEM** | 30m | 83°S-83°N | https://asterweb.jpl.nasa.gov/ | - Network accessline 57
| **Copernicus DEM** | 30m | Global | https://copernicus.eu/ | - Network accessline 58
| **ArcticDEM** | 2-10m | Arctic | https://www.pgc.umn.edu/ | - Network accessline 73
| Dataset | Resolution | Classes | Source | |---------|------------|---------|--------| | **ESA WorldCover** | 10m | 11 classes | https://worldcover2021.esa.int/ | - Network accessline 74
|---------|------------|---------|--------| | **ESA WorldCover** | 10m | 11 classes | https://worldcover2021.esa.int/ | | **ESRI Land Cover** | 10m | 10 classes | https://www.esri.com/ | - Network accessline 75
| **ESA WorldCover** | 10m | 11 classes | https://worldcover2021.esa.int/ | - Network accessline 76
| **ESRI Land Cover** | 10m | 10 classes | https://www.esri.com/ | - Network accessline 77
| **Copernicus Global** | 100m | 23 classes | https://land.copernicus.eu/ | - Network accessline 78
| **MODIS MCD12Q1** | 500m | 17 classes | https://lpdaac.usgs.gov/ | - Network accessline 79
| **NLCD (US)** | 30m | 20 classes | https://www.mrlc.gov/ | - Network accessline 85
| Dataset | Resolution | Temporal | Access | |---------|------------|----------|--------| | **ERA5** | 31km | Hourly (1979+) | https://cds.climate.copernicus.eu/ | - Network accessline 86
|---------|------------|----------|--------| | **ERA5** | 31km | Hourly (1979+) | https://cds.climate.copernicus.eu/ | | **MERRA-2** | 50km | Hourly (1980+) | https://gmao.gsfc.nasa.gov/ | - Network accessline 87
| **ERA5** | 31km | Hourly (1979+) | https://cds.climate.copernicus.eu/ | - Network accessline 88
| **MERRA-2** | 50km | Hourly (1980+) | https://gmao.gsfc.nasa.gov/ | - Network accessline 89
| **JRA-55** | 55km | 3-hourly (1958+) | https://jra.kishou.go.jp/ | - Network accessline 133
overpass_url = "http://overpass-api.de/api/interpreter" - Network accessline 140
response = requests.get(overpass_url, params={'data': query}) - Network accessline 151
# Admin boundaries (scale: 10m, 50m, 110m) countries = gpd.read_file('https://naturalearth.s3.amazonaws.com/10m_cultural/ne_10m_admin_0_countries.zip') - Network accessline 152
countries = gpd.read_file('https://naturalearth.s3.amazonaws.com/10m_cultural/ne_10m_admin_0_countries.zip') - Network accessline 153
urban_areas = gpd.read_file('https://naturalearth.s3.amazonaws.com/10m_cultural/ne_10m_urban_areas.zip') - Network accessline 154
ports = gpd.read_file('https://naturalearth.s3.amazonaws.com/10m_cultural/ne_10m_ports.zip') - Network accessline 159
| Dataset | Type | Access | |---------|------|--------| | **GADM** | Admin boundaries | https://gadm.org/ | - Network accessline 160
|---------|------|--------| | **GADM** | Admin boundaries | https://gadm.org/ | | **HydroSHEDS** | Rivers, basins | https://www.hydrosheds.org/ | - Network accessline 161
| **GADM** | Admin boundaries | https://gadm.org/ | - Network accessline 162
| **HydroSHEDS** | Rivers, basins | https://www.hydrosheds.org/ | - Network accessline 163
| **Global Power Plant** | Power plants | https://datasets.wri.org/ | - Network accessline 164
| **WorldPop** | Population | https://www.worldpop.org/ | - Network accessline 165
| **GPW** | Population | https://sedac.ciesin.columbia.edu/ | - Network accessline 166
| **HDX** | Humanitarian data | https://data.humdata.org/ | - Network accessline 175
# Geocoding url = "https://maps.googleapis.com/maps/api/geocode/json" - Network accessline 176
url = "https://maps.googleapis.com/maps/api/geocode/json" - Access to secretsline 179
[Credential-related source omitted] - Network accessline 182
response = requests.get(url, params=params) - Network accessline 193
url = "https://api.mapbox.com/geocoding/v5/mapbox.places/Golden%20Gate%20Bridge.json" - Access to secretsline 194
[Credential-related source omitted] - Network accessline 196
response = requests.get(url, params=params) - Network accessline 203
# Current weather url = "https://api.openweathermap.org/data/2.5/weather" - Network accessline 204
url = "https://api.openweathermap.org/data/2.5/weather" - Access to secretsline 208
[Credential-related source omitted] - Network accessline 211
response = requests.get(url, params=params) - Network accessline 222
# Connect to STAC catalog catalog = pystac_client.Client.open("https://earth-search.aws.element84.com/v1") - Network accessline 223
catalog = pystac_client.Client.open("https://earth-search.aws.element84.com/v1") - Network accessline 242
catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", - Network accessline 243
"https://planetarycomputer.microsoft.com/api/stac/v1", - Network accessline 265
""" # Initialize API api = SentinelAPI('user', 'password', 'https://scihub.copernicus.eu/dhus') - Network accessline 267
api = SentinelAPI('user', 'password', 'https://scihub.copernicus.eu/dhus')
bundled/skills/geomaster/references/programming-languages.md
- Network accessline 234
// Add tile layer L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', { - Network accessline 235
L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', { - Network accessline 239
// Add GeoJSON layer fetch('data.geojson') - Network accessline 240
fetch('data.geojson')
bundled/skills/geomaster/references/remote-sensing.md
- Network accessline 27
# Search Sentinel-2 collection catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", - Network accessline 28
catalog = pystac_client.Client.open( "https://planetarycomputer.microsoft.com/api/stac/v1", modifier=planetary_computer.sign_inplace, - Network accessline 29
"https://planetarycomputer.microsoft.com/api/stac/v1",
bundled/skills/geopandas/references/data-io.md
- Network accessline 15
# Read from URL gdf = gpd.read_file("https://example.com/data.geojson") - Network accessline 16
gdf = gpd.read_file("https://example.com/data.geojson") - Network accessline 163
# HTTP/HTTPS gdf = gpd.read_file("https://example.com/data.geojson") - Network accessline 164
gdf = gpd.read_file("https://example.com/data.geojson")
bundled/skills/get-available-resources/scripts/detect_resources.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/gh-address-comments/LICENSE.txt
bundled/skills/gh-address-comments/assets/github-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/gh-address-comments/scripts/fetch_comments.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/gh-fix-ci/LICENSE.txt
bundled/skills/gh-fix-ci/SKILL.md
- Network accessline 66
Usage examples: - `python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "123"` - `python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "https://github.com/org/repo/pull/123" --json` - Network accessline 67
- `python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "123"` - `python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "https://github.com/org/repo/pull/123" --json` - `python "<path-to-skill>/scripts/inspe - Network accessline 68
- `python "<path-to-skill>/scripts/inspect_pr_checks.py" --repo "." --pr "https://github.com/org/repo/pull/123" --json`
bundled/skills/gh-fix-ci/assets/github-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/gh-fix-ci/scripts/inspect_pr_checks.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/gradient-methods/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/hedgefundmonitor/SKILL.md
- Network accessline 13
**Base URL:** `https://data.financialresearch.gov/hf/v1` - Network accessline 21
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 23
# List all available datasets resp = requests.get(f"{BASE}/series/dataset") - Network accessline 24
resp = requests.get(f"{BASE}/series/dataset") - Network accessline 28
# Search for series by keyword resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 29
resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 33
# Fetch a single time series resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 34
resp = requests.get(f"{BASE}/series/timeseries", params={
bundled/skills/hedgefundmonitor/references/api-overview.md
- Network accessline 6
https://data.financialresearch.gov/hf/v1
bundled/skills/hedgefundmonitor/references/endpoints-combined.md
- Network accessline 5
**URL:** `GET https://data.financialresearch.gov/hf/v1/series/full` - Network accessline 41
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 43
resp = requests.get(f"{BASE}/series/full", params={ - Network accessline 64
**URL:** `GET https://data.financialresearch.gov/hf/v1/series/multifull` - Network accessline 83
# Fetch multiple leverage series at once resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 84
resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 107
**URL:** `GET https://data.financialresearch.gov/hf/v1/series/dataset` - Network accessline 130
# List all available datasets resp = requests.get(f"{BASE}/series/dataset") - Network accessline 131
resp = requests.get(f"{BASE}/series/dataset") - Network accessline 135
# Download full FPF dataset (recent data only) resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 136
resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 144
# Annual data with custom periodicity resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 145
resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 153
# Only final vintage resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 154
resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 164
**URL:** `GET https://data.financialresearch.gov/hf/v1/categories` - Network accessline 188
# Download leverage category as CSV resp = requests.get(f"{BASE}/categories", params={"category": "leverage"}) - Network accessline 189
resp = requests.get(f"{BASE}/categories", params={"category": "leverage"}) - Network accessline 194
# Also accessible via direct URL: # https://data.financialresearch.gov/hf/v1/categories?category=leverage - Network accessline 195
# https://data.financialresearch.gov/hf/v1/categories?category=leverage
bundled/skills/hedgefundmonitor/references/endpoints-metadata.md
- Network accessline 5
**URL:** `GET https://data.financialresearch.gov/hf/v1/metadata/mnemonics` - Network accessline 19
import requests BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 20
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 22
# All mnemonics (flat list) resp = requests.get(f"{BASE}/metadata/mnemonics") - Network accessline 23
resp = requests.get(f"{BASE}/metadata/mnemonics") - Network accessline 27
# Mnemonics for a single dataset with names resp = requests.get(f"{BASE}/metadata/mnemonics", params={"dataset": "fpf"}) - Network accessline 28
resp = requests.get(f"{BASE}/metadata/mnemonics", params={"dataset": "fpf"}) - Network accessline 31
# All mnemonics grouped by dataset resp = requests.get(f"{BASE}/metadata/mnemonics", params={"output": "by_dataset"}) - Network accessline 32
resp = requests.get(f"{BASE}/metadata/mnemonics", params={"output": "by_dataset"}) - Network accessline 41
**URL:** `GET https://data.financialresearch.gov/hf/v1/metadata/query` - Network accessline 66
# Full metadata resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 67
resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 75
# Specific subfield only resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 76
resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 82
# Multiple fields resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 83
resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 93
**URL:** `GET https://data.financialresearch.gov/hf/v1/metadata/search` - Network accessline 118
# Find series containing "leverage" anywhere resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 119
resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 124
# Find series starting with "Fund" resp = requests.get(f"{BASE}/metadata/search", params={"query": "Fund*"}) - Network accessline 125
resp = requests.get(f"{BASE}/metadata/search", params={"query": "Fund*"}) - Network accessline 127
# Find by exact dataset name resp = requests.get(f"{BASE}/metadata/search", params={"query": "FICC*"}) - Network accessline 128
resp = requests.get(f"{BASE}/metadata/search", params={"query": "FICC*"}) - Network accessline 130
# Search for stress test series resp = requests.get(f"{BASE}/metadata/search", params={"query": "*stress*"}) - Network accessline 131
resp = requests.get(f"{BASE}/metadata/search", params={"query": "*stress*"})
bundled/skills/hedgefundmonitor/references/endpoints-series-data.md
- Network accessline 5
**URL:** `GET https://data.financialresearch.gov/hf/v1/series/timeseries` - Network accessline 41
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 43
# Full history for a series resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 44
resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 51
# Filtered date range with null removal resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 52
resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 59
# Annual frequency (calendar year end) resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 60
resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 66
# Epoch milliseconds for charting libraries resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 67
resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 77
**URL:** `GET https://data.financialresearch.gov/hf/v1/calc/spread` - Network accessline 109
# Spread between two repo rates resp = requests.get(f"{BASE}/calc/spread", params={ - Network accessline 110
resp = requests.get(f"{BASE}/calc/spread", params={ - Network accessline 119
# Annual spread with mean aggregation resp = requests.get(f"{BASE}/calc/spread", params={ - Network accessline 120
resp = requests.get(f"{BASE}/calc/spread", params={
bundled/skills/hedgefundmonitor/references/examples.md
- Network accessline 15
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 17
# List all datasets resp = requests.get(f"{BASE}/series/dataset") - Network accessline 18
resp = requests.get(f"{BASE}/series/dataset") - Network accessline 22
# List all mnemonics for FPF with names resp = requests.get(f"{BASE}/metadata/mnemonics", params={"dataset": "fpf"}) - Network accessline 23
resp = requests.get(f"{BASE}/metadata/mnemonics", params={"dataset": "fpf"}) - Network accessline 27
# Search for leverage-related series resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 28
resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"}) - Network accessline 42
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 44
# Fetch overall leverage ratio resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 45
resp = requests.get(f"{BASE}/series/timeseries", params={ - Network accessline 52
# Get metadata meta_resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 53
meta_resp = requests.get(f"{BASE}/metadata/query", params={ - Network accessline 76
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 85
resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 112
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 114
# Download entire FPF dataset, recent data only resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 115
resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 146
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 156
resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 184
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 186
resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 219
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 221
# Download the leverage category as a DataFrame resp = requests.get(f"{BASE}/categories", params={"category": "leverage"}) - Network accessline 222
resp = requests.get(f"{BASE}/categories", params={"category": "leverage"}) - Network accessline 235
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 240
resp = requests.get(f"{BASE}/series/multifull", params={ - Network accessline 267
BASE = "https://data.financialresearch.gov/hf/v1" - Network accessline 270
"""Fetch only the most recent FPF observations (for periodic refreshes).""" start = (datetime.today() - timedelta(days=days_back)).strftime("%Y-%m-%d") resp = requests.get(f"{BASE}/series/dataset", params={ - Network accessline 271
start = (datetime.today() - timedelta(days=days_back)).strftime("%Y-%m-%d") resp = requests.get(f"{BASE}/series/dataset", params={ "dataset": "fpf", - Network accessline 272
resp = requests.get(f"{BASE}/series/dataset", params={
bundled/skills/hive-mind-advanced/SKILL.md
- Network accessline 702
- [Hive Mind Documentation](https://github.com/ruvnet/claude-flow/docs/hive-mind) - Network accessline 703
- [Collective Intelligence Patterns](https://github.com/ruvnet/claude-flow/docs/patterns) - Network accessline 704
- [Byzantine Consensus](https://github.com/ruvnet/claude-flow/docs/consensus) - Network accessline 705
- [Memory Optimization](https://github.com/ruvnet/claude-flow/docs/memory)
bundled/skills/hypothesis-generation/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/hypothesis-generation/references/literature_search_strategies.md
- Network accessline 45
**Example searches:** - `https://pubmed.ncbi.nlm.nih.gov/?term=wound+healing+diabetes+review` - Network accessline 46
- `https://pubmed.ncbi.nlm.nih.gov/?term=wound+healing+diabetes+review` - Network accessline 47
- `https://pubmed.ncbi.nlm.nih.gov/?term=gut+microbiome+cognition+systematic+review` - Network accessline 104
https://pubmed.ncbi.nlm.nih.gov/?term=(mechanism+OR+pathway)+AND+[phenomenon]+AND+(molecular+OR+cellular) - Network accessline 109
https://pubmed.ncbi.nlm.nih.gov/?term=[exposure]+AND+[outcome]+AND+(randomized+controlled+trial+OR+cohort+study) - Network accessline 114
https://pubmed.ncbi.nlm.nih.gov/?term=[biomarker]+AND+[disease]+AND+(association+OR+correlation+OR+prediction) - Network accessline 119
https://pubmed.ncbi.nlm.nih.gov/?term=[intervention]+AND+[condition]+AND+(efficacy+OR+effectiveness+OR+clinical+trial)
bundled/skills/hypothesis-testing/SKILL.md
- Possible obfuscationline 744
decoded = base64.b64decode(encoded) - Network accessline 856
- **Hypothesis Documentation**: https://hypothesis.readthedocs.io/ - Network accessline 857
- **Hypothesis for Property-Based Testing**: https://increment.com/testing/in-praise-of-property-based-testing/ - Network accessline 858
- **PBT vs Example-Based**: https://hypothesis.works/articles/what-is-property-based-testing/ - Network accessline 859
- **Hypothesis Strategies**: https://hypothesis.readthedocs.io/en/latest/data.html - Network accessline 860
- **Stateful Testing**: https://hypothesis.readthedocs.io/en/latest/stateful.html
bundled/skills/imagegen/LICENSE.txt
bundled/skills/imagegen/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Network accessline 51
If the key is missing, give the user these steps: 1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Network accessline 52
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 62
[Credential-related source omitted]
bundled/skills/imagegen/assets/imagegen-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/imagegen/references/cli.md
bundled/skills/imagegen/scripts/image_gen.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 48
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Possible obfuscationline 227
out_path.write_bytes(base64.b64decode(image_b64)) - Possible obfuscationline 290
raw = base64.b64decode(image_b64)
bundled/skills/imaging-data-commons/SKILL.md
- Network accessline 8
idc-index: "0.11.9" idc-data-version: "v23" repository: https://github.com/ImagingDataCommons/idc-claude-skill - Network accessline 9
idc-data-version: "v23" repository: https://github.com/ImagingDataCommons/idc-claude-skill --- - Network accessline 10
repository: https://github.com/ImagingDataCommons/idc-claude-skill - Network accessline 25
**Primary tool:** `idc-index` ([GitHub](https://github.com/imagingdatacommons/idc-index)) - Network accessline 126
**Complete index table documentation:** Use https://idc-index.readthedocs.io/en/latest/indices_reference.html for quick check of available tables and columns without executing any code. - Network accessline 547
**License types in IDC:** - **CC BY 4.0** / **CC BY 3.0** (~97% of data) - Allows commercial use with attribution - **CC BY-NC 4.0** / **CC BY-NC 3.0** (~3% of data) - Non-commercial use only - Network accessline 548
- **CC BY 4.0** / **CC BY 3.0** (~97% of data) - Allows commercial use with attribution - **CC BY-NC 4.0** / **CC BY-NC 3.0** (~3% of data) - Non-commercial use only - **Custom licenses** (rare) - Some collections have specific terms (e.g., - Network accessline 549
- **CC BY-NC 4.0** / **CC BY-NC 3.0** (~3% of data) - Non-commercial use only - Network accessline 649
**Before using BigQuery**, always check if a specialized index table already has the metadata you need: 1. Use `client.indices_overview` or the [idc-index indices reference](https://idc-index.readthedocs.io/en/latest/indices_reference.html) - Network accessline 650
1. Use `client.indices_overview` or the [idc-index indices reference](https://idc-index.readthedocs.io/en/latest/indices_reference.html) to discover all available tables and their columns 2. Fetch the relevant index: `client.fetch_index("ta - Network accessline 659
|------|------|-----------| | Programmatic queries & downloads | `idc-index` | This document | | Interactive exploration | IDC Portal | https://portal.imaging.datacommons.cancer.gov/ | - Network accessline 660
| Programmatic queries & downloads | `idc-index` | This document | | Interactive exploration | IDC Portal | https://portal.imaging.datacommons.cancer.gov/ | | Complex metadata queries | BigQuery | `references/bigquery_guide.md` | - Network accessline 661
| Interactive exploration | IDC Portal | https://portal.imaging.datacommons.cancer.gov/ | - Network accessline 663
| 3D visualization & analysis | SlicerIDCBrowser | https://github.com/ImagingDataCommons/SlicerIDCBrowser | - Network accessline 748
- **Estimate size first** - Check collection size before downloading - some collection sizes are in terabytes! - **Save manifests** - Always save query results with Series UIDs for reproducibility and data provenance - **Read documentation* - Network accessline 749
- **Save manifests** - Always save query results with Series UIDs for reproducibility and data provenance - **Read documentation** - IDC data structure and metadata fields are documented at https://learn.canceridc.dev/ - **Use IDC forum** - - Network accessline 750
- **Read documentation** - IDC data structure and metadata fields are documented at https://learn.canceridc.dev/ - Network accessline 751
- **Use IDC forum** - Search for questons/answers and ask your questions to the IDC maintainers and users at https://discourse.canceridc.dev/ - Network accessline 832
- **[indices_reference](https://idc-index.readthedocs.io/en/latest/indices_reference.html)** - External documentation for index tables (may be ahead of the installed version) - Network accessline 836
- **IDC Portal**: https://portal.imaging.datacommons.cancer.gov/explore/ - Network accessline 837
- **Documentation**: https://learn.canceridc.dev/ - Network accessline 838
- **Tutorials**: https://github.com/ImagingDataCommons/IDC-Tutorials - Network accessline 839
- **User Forum**: https://discourse.canceridc.dev/ - Network accessline 840
- **idc-index GitHub**: https://github.com/ImagingDataCommons/idc-index - Network accessline 841
- **Citation**: Fedorov, A., et al. "National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence." RadioGraphics 43.12 (2023). https://doi.org/10.1148/rg.230180 - Network accessline 845
This skill version is available in skill metadata. To check for updates: - Visit the [releases page](https://github.com/ImagingDataCommons/idc-claude-skill/releases) - Network accessline 846
- Visit the [releases page](https://github.com/ImagingDataCommons/idc-claude-skill/releases)
bundled/skills/imaging-data-commons/references/bigquery_guide.md
- Network accessline 48
### dicom_all Primary table joining complete DICOM metadata with IDC-specific columns (collection_id, gcs_url, license). Contains all DICOM tags from `dicom_metadata` plus collection and administrative metadata. See [dicom_all.sql](https:// - Network accessline 49
Primary table joining complete DICOM metadata with IDC-specific columns (collection_id, gcs_url, license). Contains all DICOM tags from `dicom_metadata` plus collection and administrative metadata. See [dicom_all.sql](https://github.com/Ima - Network accessline 333
- IDC data is de-identified; private tags containing PHI may have been removed or modified - The same tag may have different meanings across software versions - Always verify query results visually using the [IDC Viewer](https://viewer.imag - Network accessline 335
- Always verify query results visually using the [IDC Viewer](https://viewer.imaging.datacommons.cancer.gov/) before large-scale analysis - Network accessline 339
**Manufacturer DICOM Conformance Statements:** - [GE Healthcare MR](https://www.gehealthcare.com/products/interoperability/dicom/magnetic-resonance-imaging-dicom-conformance-statements) - Network accessline 340
- [GE Healthcare MR](https://www.gehealthcare.com/products/interoperability/dicom/magnetic-resonance-imaging-dicom-conformance-statements) - Network accessline 341
- [Siemens MR](https://www.siemens-healthineers.com/services/it-standards/dicom-conformance-statements-magnetic-resonance) - Network accessline 342
- [Siemens CT](https://www.siemens-healthineers.com/services/it-standards/dicom-conformance-statements-computed-tomography) - Network accessline 344
**DICOM Standard:** - [Part 5 Section 7.8 - Private Data Elements](https://dicom.nema.org/medical/dicom/current/output/chtml/part05/sect_7.8.html) - Network accessline 345
- [Part 5 Section 7.8 - Private Data Elements](https://dicom.nema.org/medical/dicom/current/output/chtml/part05/sect_7.8.html) - Network accessline 346
- [Part 15 Appendix E - De-identification Profiles](https://dicom.nema.org/medical/dicom/current/output/chtml/part15/chapter_e.html) - Network accessline 348
**Community Resources:** - [NAMIC Wiki: DWI/DTI DICOM](https://www.na-mic.org/wiki/NAMIC_Wiki:DTI:DICOM_for_DWI_and_DTI) - comprehensive vendor comparison for diffusion imaging - Network accessline 349
- [NAMIC Wiki: DWI/DTI DICOM](https://www.na-mic.org/wiki/NAMIC_Wiki:DTI:DICOM_for_DWI_and_DTI) - comprehensive vendor comparison for diffusion imaging - Network accessline 350
- [StandardizeBValue](https://github.com/nslay/StandardizeBValue) - tool to extract vendor b-values to standard tags - Network accessline 553
- [Understanding the BigQuery DICOM schema](https://docs.cloud.google.com/healthcare-api/docs/how-tos/dicom-bigquery-schema) - Network accessline 554
- [BigQuery Query Syntax](https://docs.cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax) - Network accessline 555
- [Kaggle Intro to SQL](https://www.kaggle.com/learn/intro-to-sql) - Network accessline 556
- [Sample BigQuery queries of IDC data](https://github.com/ImagingDataCommons/idc-bigquery-cookbook)
bundled/skills/imaging-data-commons/references/cli_guide.md
bundled/skills/imaging-data-commons/references/clinical_data_guide.md
- Network accessline 312
**IDC Documentation:** - [Clinical data organization](https://learn.canceridc.dev/data/organization-of-data/clinical) - How clinical data is organized in IDC - Network accessline 313
- [Clinical data organization](https://learn.canceridc.dev/data/organization-of-data/clinical) - How clinical data is organized in IDC - Network accessline 314
- [Clinical data dashboard](https://datastudio.google.com/u/0/reporting/04cf5976-4ea0-4fee-a749-8bfd162f2e87/page/p_s7mk6eybqc) - Visual summary of available clinical data - Network accessline 315
- [idc-index clinical_index documentation](https://idc-index.readthedocs.io/en/latest/column_descriptions.html#clinical-index) - Network accessline 321
**IDC Tutorials:** - [clinical_data_intro.ipynb](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/advanced_topics/clinical_data_intro.ipynb) - Network accessline 322
- [clinical_data_intro.ipynb](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/advanced_topics/clinical_data_intro.ipynb) - Network accessline 323
- [exploring_clinical_data.ipynb](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/getting_started/exploring_clinical_data.ipynb) - Network accessline 324
- [nlst_clinical_data.ipynb](https://github.com/ImagingDataCommons/IDC-Tutorials/blob/master/notebooks/collections_demos/nlst_clinical_data.ipynb)
bundled/skills/imaging-data-commons/references/cloud_storage_guide.md
- Network accessline 134
# Install s5cmd # macOS: brew install s5cmd # Linux: download from https://github.com/peak/s5cmd/releases - Network accessline 136
# Linux: download from https://github.com/peak/s5cmd/releases - Network accessline 289
- **Download defaults to AWS buckets**: request GCS if needed - **Save manifests**: Store the `series_aws_url` or `crdc_series_uuid` values for reproducibility - **Check licenses**: Query `license_short_name` before commercial use; CC-NC da - Network accessline 290
- **Save manifests**: Store the `series_aws_url` or `crdc_series_uuid` values for reproducibility - **Check licenses**: Query `license_short_name` before commercial use; CC-NC data requires non-commercial use - **Use current version unless - Network accessline 291
- **Check licenses**: Query `license_short_name` before commercial use; CC-NC data requires non-commercial use - Network accessline 314
**IDC Documentation:** - [Files and metadata](https://learn.canceridc.dev/data/organization-of-data/files-and-metadata) - Bucket organization details - Network accessline 315
- [Files and metadata](https://learn.canceridc.dev/data/organization-of-data/files-and-metadata) - Bucket organization details - Network accessline 316
- [Data versioning](https://learn.canceridc.dev/data/data-versioning) - Versioning scheme explanation - Network accessline 317
- [Resolving GUIDs and UUIDs](https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids) - CRDC UUID documentation - Network accessline 318
- [Direct loading from cloud](https://learn.canceridc.dev/data/downloading-data/direct-loading) - Python examples for cloud access - Network accessline 320
**AWS Resources:** - [NCI IDC on AWS Open Data Registry](https://registry.opendata.aws/nci-imaging-data-commons/) - Bucket ARNs and access info - Network accessline 321
- [NCI IDC on AWS Open Data Registry](https://registry.opendata.aws/nci-imaging-data-commons/) - Bucket ARNs and access info - Network accessline 322
- [s5cmd](https://github.com/peak/s5cmd) - High-performance S3 client (used internally by idc-index) - Network accessline 323
- [AWS CLI S3 commands](https://docs.aws.amazon.com/cli/latest/reference/s3/) - Standard AWS command-line interface - Network accessline 324
- [Boto3 S3 documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html) - AWS SDK for Python - Network accessline 326
**Google Cloud Resources:** - [gsutil tool](https://cloud.google.com/storage/docs/gsutil) - Google Cloud Storage command-line tool - Network accessline 327
- [gsutil tool](https://cloud.google.com/storage/docs/gsutil) - Google Cloud Storage command-line tool - Network accessline 328
- [gcloud storage commands](https://cloud.google.com/sdk/gcloud/reference/storage) - Modern GCS CLI (recommended over gsutil) - Network accessline 329
- [Google Cloud Storage Python client](https://cloud.google.com/python/docs/reference/storage/latest) - GCS SDK for Python
bundled/skills/imaging-data-commons/references/dicomweb_guide.md
- Network accessline 20
https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb - Network accessline 34
https://healthcare.googleapis.com/v1/projects/nci-idc-data/locations/us-central1/datasets/idc/dicomStores/idc-store-v{VERSION}/dicomWeb - Network accessline 123
IDC DICOMweb is provided through Google Cloud Healthcare API DICOM stores. The implementation follows DICOM PS3.18 Web Services with specific characteristics documented in the [Google Healthcare DICOM conformance statement](https://docs.clo - Network accessline 188
base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 190
# Search for a specific study study_uid = "1.3.6.1.4.1.14519.5.2.1.6450.9002.307623500513044641407722230440" response = requests.get( - Network accessline 191
study_uid = "1.3.6.1.4.1.14519.5.2.1.6450.9002.307623500513044641407722230440" response = requests.get( f"{base_url}/studies", - Network accessline 192
response = requests.get( - Network accessline 208
base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 211
response = requests.get( - Network accessline 231
base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 235
response = requests.get( - Network accessline 254
base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 258
response = requests.get( - Network accessline 294
# Use DICOMweb to stream metadata without downloading files base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 295
base_url = "https://proxy.imaging.datacommons.cancer.gov/current/viewer-only-no-downloads-see-tinyurl-dot-com-slash-3j3d9jyp/dicomWeb" - Network accessline 297
response = requests.get( - Network accessline 336
# Build authenticated request base_url = "https://healthcare.googleapis.com/v1/projects/nci-idc-data/locations/us-central1/datasets/idc/dicomStores/idc-store-v23/dicomWeb" - Network accessline 337
base_url = "https://healthcare.googleapis.com/v1/projects/nci-idc-data/locations/us-central1/datasets/idc/dicomStores/idc-store-v23/dicomWeb" - Network accessline 339
response = requests.get( - Network accessline 386
**IDC Documentation:** - [IDC DICOM Stores](https://learn.canceridc.dev/data/organization-of-data/dicom-stores) - Data coverage and bucket details - Network accessline 387
- [IDC DICOM Stores](https://learn.canceridc.dev/data/organization-of-data/dicom-stores) - Data coverage and bucket details - Network accessline 388
- [IDC DICOMweb Access](https://learn.canceridc.dev/data/downloading-data/dicomweb-access) - Endpoint usage and differences - Network accessline 389
- [IDC Proxy Policy](https://learn.canceridc.dev/portal/proxy-policy) - Quota policies and usage restrictions - Network accessline 390
- [IDC User Guide](https://learn.canceridc.dev/) - Complete documentation - Network accessline 392
**DICOMweb Standards and Tools:** - [Google Healthcare DICOM Conformance Statement](https://docs.cloud.google.com/healthcare-api/docs/dicom) - Network accessline 393
- [Google Healthcare DICOM Conformance Statement](https://docs.cloud.google.com/healthcare-api/docs/dicom) - Network accessline 394
- [DICOMweb Standard](https://www.dicomstandard.org/using/dicomweb) - Network accessline 395
- [dicomweb-client Python library](https://dicomweb-client.readthedocs.io/)
bundled/skills/imaging-data-commons/references/digital_pathology_guide.md
- Network accessline 243
**Python Libraries:** - [highdicom](https://github.com/ImagingDataCommons/highdicom) - High-level DICOM abstractions for Python. Create and read DICOM Segmentations (SEG), Structured Reports (SR), and parametric maps for pathology and radio - Network accessline 244
- [highdicom](https://github.com/ImagingDataCommons/highdicom) - High-level DICOM abstractions for Python. Create and read DICOM Segmentations (SEG), Structured Reports (SR), and parametric maps for pathology and radiology. Developed by IDC - Network accessline 245
- [wsidicom](https://github.com/imi-bigpicture/wsidicom) - Python package for reading DICOM WSI datasets. Parses metadata into easy-to-use dataclasses for whole slide image analysis. - Network accessline 246
- [TIA-Toolbox](https://github.com/TissueImageAnalytics/tiatoolbox) - End-to-end computational pathology library with DICOM support via `DICOMWSIReader`. Provides tile extraction, feature extraction, and pretrained deep learning models. - Network accessline 247
- [EZ-WSI-DICOMweb](https://github.com/GoogleCloudPlatform/EZ-WSI-DICOMweb) - Extract image patches from DICOM whole slide images via DICOMweb. Designed for AI/ML workflows with cloud DICOM stores. - Network accessline 249
**Viewers:** - [Slim](https://github.com/ImagingDataCommons/slim) - Web-based DICOM slide microscopy viewer and annotation tool. Supports brightfield and multiplexed immunofluorescence imaging via DICOMweb. Developed by IDC. - Network accessline 250
- [Slim](https://github.com/ImagingDataCommons/slim) - Web-based DICOM slide microscopy viewer and annotation tool. Supports brightfield and multiplexed immunofluorescence imaging via DICOMweb. Developed by IDC. - Network accessline 251
- [QuPath](https://qupath.github.io/) - Cross-platform open source software for whole slide image analysis. Supports DICOM WSI via Bio-Formats and OpenSlide (v0.4.0+). - Network accessline 253
**Conversion:** - [dicom_wsi](https://github.com/Steven-N-Hart/dicom_wsi) - Python implementation for converting proprietary WSI formats to DICOM-compliant files. - Network accessline 254
- [dicom_wsi](https://github.com/Steven-N-Hart/dicom_wsi) - Python implementation for converting proprietary WSI formats to DICOM-compliant files.
bundled/skills/imaging-data-commons/references/index_tables_guide.md
- Network accessline 7
**Complete index table documentation:** https://idc-index.readthedocs.io/en/latest/indices_reference.html - Network accessline 107
| `PatientSex` | STRING | Yes | Patient sex | | `PatientAge` | STRING | Yes | Patient age at time of study | | `license_short_name` | STRING | No | License type (CC BY 4.0, CC BY-NC 4.0, etc.) | - Network accessline 108
| `PatientAge` | STRING | Yes | Patient age at time of study | | `license_short_name` | STRING | No | License type (CC BY 4.0, CC BY-NC 4.0, etc.) | | `series_size_MB` | FLOAT | No | Size of series in megabytes | - Network accessline 109
| `license_short_name` | STRING | No | License type (CC BY 4.0, CC BY-NC 4.0, etc.) | - Network accessline 113
**DICOM = Yes**: Column value extracted from the DICOM attribute with the same name. Refer to the [DICOM standard](https://dicom.nema.org/medical/dicom/current/output/chtml/part06/chapter_6.html) for numeric tag mappings. Use standard DICOM - Network accessline 143
- Complete index table documentation: https://idc-index.readthedocs.io/en/latest/indices_reference.html
bundled/skills/imaging-data-commons/references/use_cases.md
- Network accessline 138
For additional visualization options, see the [IDC Portal getting started guide](https://learn.canceridc.dev/portal/getting-started) or [SlicerIDCBrowser](https://github.com/ImagingDataCommons/SlicerIDCBrowser) for 3D Slicer integration.
bundled/skills/infographics/SKILL.md
bundled/skills/infographics/references/color_palettes.md
- Network accessline 476
1. **Contrast Checkers:** - WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 477
- WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 478
- Coolors Contrast Checker: https://coolors.co/contrast-checker - Network accessline 480
2. **Colorblind Simulators:** - Coblis: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 481
- Coblis: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 485
3. **Palette Generators:** - Coolors: https://coolors.co/ - Network accessline 486
- Coolors: https://coolors.co/ - Network accessline 487
- Adobe Color: https://color.adobe.com/ - Network accessline 488
- Paletton: https://paletton.com/
bundled/skills/infographics/scripts/generate_infographic.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 133
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Access to secretsline 176
[Credential-related source omitted] - Access to secretsline 177
[Credential-related source omitted] - Network accessline 178
[Credential-related source omitted] - Access to secretsline 178
[Credential-related source omitted] - Network accessline 179
print("\nFor AI generation, you need an OpenRouter API key.") print("Get one at: https://openrouter.ai/keys") print("\nSet it with:") - Network accessline 180
print("Get one at: https://openrouter.ai/keys") - Access to secretsline 182
[Credential-related source omitted] - Access to secretsline 215
[Credential-related source omitted] - Access to secretsline 216
[Credential-related source omitted]
bundled/skills/infographics/scripts/generate_infographic_ai.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 13
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 55
[Credential-related source omitted] - Access to secretsline 66
[Credential-related source omitted] - Access to secretsline 339
[Credential-related source omitted] - Access to secretsline 341
[Credential-related source omitted] - Access to secretsline 343
[Credential-related source omitted] - Access to secretsline 345
[Credential-related source omitted] - Access to secretsline 347
[Credential-related source omitted] - Access to secretsline 349
[Credential-related source omitted] - Access to secretsline 350
[Credential-related source omitted] - Network accessline 351
[Credential-related source omitted] - Access to secretsline 351
[Credential-related source omitted] - Network accessline 352
[Credential-related source omitted] - Access to secretsline 352
[Credential-related source omitted] - Network accessline 353
"Get your API key from: https://openrouter.ai/keys" - Network accessline 356
self.verbose = verbose self._last_error = None self.base_url = "https://openrouter.ai/api/v1" - Network accessline 358
self.base_url = "https://openrouter.ai/api/v1" - Network accessline 432
[Credential-related source omitted] - Access to secretsline 432
[Credential-related source omitted] - Network accessline 433
"Content-Type": "application/json", "HTTP-Referer": "https://github.com/scientific-writer", "X-Title": "Infographic Research" - Network accessline 434
"HTTP-Referer": "https://github.com/scientific-writer", - Network accessline 447
response = requests.post( - Network accessline 516
[Credential-related source omitted] - Access to secretsline 516
[Credential-related source omitted] - Network accessline 517
"Content-Type": "application/json", "HTTP-Referer": "https://github.com/scientific-writer", "X-Title": "Infographic Web Search" - Network accessline 518
"HTTP-Referer": "https://github.com/scientific-writer", - Network accessline 529
response = requests.post( - Network accessline 585
[Credential-related source omitted] - Access to secretsline 585
[Credential-related source omitted] - Network accessline 586
"Content-Type": "application/json", "HTTP-Referer": "https://github.com/scientific-writer", "X-Title": "Infographic Generator" - Network accessline 587
"HTTP-Referer": "https://github.com/scientific-writer", - Network accessline 601
try: response = requests.post( - Network accessline 602
response = requests.post( - Possible obfuscationline 652
return base64.b64decode(base64_str) - Possible obfuscationline 663
return base64.b64decode(base64_str) - Possible obfuscationline 674
return base64.b64decode(base64_str) - Access to secretsline 1223
[Credential-related source omitted] - Access to secretsline 1244
[Credential-related source omitted] - Access to secretsline 1253
[Credential-related source omitted] - Access to secretsline 1254
[Credential-related source omitted] - Access to secretsline 1255
[Credential-related source omitted] - Access to secretsline 1257
[Credential-related source omitted] - Access to secretsline 1262
[Credential-related source omitted]
bundled/skills/iso-13485-certification/scripts/gap_analyzer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/jupyter-notebook/LICENSE.txt
bundled/skills/jupyter-notebook/assets/experiment-template.ipynb
- Executable scriptline 1
Executable file
bundled/skills/jupyter-notebook/assets/jupyter-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="21" fill="currentColor" viewBox="0 0 20 21">
bundled/skills/jupyter-notebook/assets/tutorial-template.ipynb
- Executable scriptline 1
Executable file
bundled/skills/jupyter-notebook/scripts/new_notebook.py
- Executable scriptline 1
Executable file
bundled/skills/knowledge-steward/SKILL.md
bundled/skills/knowledge-steward/assets/setup-guide.md
- Network accessline 15
1. **Git for Windows** - 下载：https://git-scm.com/download/win - Network accessline 16
- 下载：https://git-scm.com/download/win - Network accessline 20
2. **GitHub 账号** - 注册：https://github.com/signup - Network accessline 21
- 注册：https://github.com/signup - Network accessline 50
1. 访问 https://github.com/new - Network accessline 103
访问您的 GitHub 仓库确认文件已上传： - https://github.com/你的用户名/knowledge-base - Network accessline 104
- https://github.com/你的用户名/knowledge-base - Network accessline 125
**Personal Access Token (如果需要)：** 如果 GitHub 要求使用 Token 而不是密码： 1. 访问 https://github.com/settings/tokens - Network accessline 126
如果 GitHub 要求使用 Token 而不是密码： 1. 访问 https://github.com/settings/tokens 2. 点击 "Generate new token (classic)" - Network accessline 127
1. 访问 https://github.com/settings/tokens - Access to secretsline 146
[Credential-related source omitted] - Access to secretsline 150
[Credential-related source omitted] - Network accessline 152
4. 添加到 GitHub： - 访问 https://github.com/settings/keys - Network accessline 153
- 访问 https://github.com/settings/keys - Network accessline 174
repositories: knowledge_base: url: "https://github.com/username/knowledge-base.git" - Network accessline 175
knowledge_base: url: "https://github.com/username/knowledge-base.git" enabled: true - Network accessline 176
url: "https://github.com/username/knowledge-base.git" - Network accessline 210
git clone https://github.com/username/knowledge-base.git "D:\Documents\ai技能外置大脑\Claude_Insights" - Network accessline 215
git clone https://github.com/username/claude-skill-knowledge-steward.git "C:\Users\羽裳\.claude\skills\knowledge-steward" - Network accessline 239
git credential-manager erase https://github.com
bundled/skills/knowledge-steward/config.example.yaml
- Network accessline 17
knowledge_base: # Replace 'username' with your GitHub username url: "https://github.com/username/knowledge-base.git" - Network accessline 18
# Replace 'username' with your GitHub username url: "https://github.com/username/knowledge-base.git" enabled: true - Network accessline 19
url: "https://github.com/username/knowledge-base.git" - Network accessline 25
skill_code: # Replace 'username' with your GitHub username url: "https://github.com/username/claude-skill-knowledge-steward.git" - Network accessline 26
# Replace 'username' with your GitHub username url: "https://github.com/username/claude-skill-knowledge-steward.git" enabled: true - Network accessline 27
url: "https://github.com/username/claude-skill-knowledge-steward.git"
bundled/skills/knowledge-steward/scripts/distill_experience.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/knowledge-steward/scripts/git_sync.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/knowledge-steward/scripts/init_git_repos.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/knowledge-steward/scripts/parse_workflow_report.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/knowledge-steward/scripts/save_to_obsidian.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/knowledge-steward/scripts/setup_github.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 79
print("(Please manually create the GitHub repository)") print("\n步骤:") print(f"1. 访问: https://github.com/new") - Network accessline 80
print("\n步骤:") print(f"1. 访问: https://github.com/new") print(f"2. Repository name: {repo_name}") - Network accessline 81
print(f"1. 访问: https://github.com/new") - Network accessline 120
else: print("✗ SSH 认证失败") print("请配置 SSH 密钥: https://docs.github.com/en/authentication/connecting-to-github-with-ssh") - Network accessline 121
print("✗ SSH 认证失败") print("请配置 SSH 密钥: https://docs.github.com/en/authentication/connecting-to-github-with-ssh") return False - Network accessline 122
print("请配置 SSH 密钥: https://docs.github.com/en/authentication/connecting-to-github-with-ssh") - Network accessline 144
config['repositories']['skill_code']['url'] = f"git@github.com:{username}/claude-skill-knowledge-steward.git" else: config['repositories']['knowledge_base']['url'] = f"https://github.com/{username}/knowledge-base.git" - Network accessline 145
else: config['repositories']['knowledge_base']['url'] = f"https://github.com/{username}/knowledge-base.git" config['repositories']['skill_code']['url'] = f"https://github.com/{username}/claude-skill-knowledge-steward.git" - Network accessline 146
config['repositories']['knowledge_base']['url'] = f"https://github.com/{username}/knowledge-base.git" - Network accessline 147
config['repositories']['skill_code']['url'] = f"https://github.com/{username}/claude-skill-knowledge-steward.git" - Network accessline 163
if not check_git(): print("✗ 未检测到 Git") print("请安装 Git for Windows: https://git-scm.com/download/win") - Network accessline 164
print("✗ 未检测到 Git") print("请安装 Git for Windows: https://git-scm.com/download/win") return 1 - Network accessline 165
print("请安装 Git for Windows: https://git-scm.com/download/win")
bundled/skills/knowledge-steward/scripts/sync_skill_code.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/lamindb/SKILL.md
- Network accessline 380
- **Official Documentation**: https://docs.lamin.ai - Network accessline 381
- **API Reference**: https://docs.lamin.ai/api - Network accessline 382
- **GitHub Repository**: https://github.com/laminlabs/lamindb - Network accessline 383
- **Tutorial**: https://docs.lamin.ai/tutorial - Network accessline 384
- **FAQ**: https://docs.lamin.ai/faq
bundled/skills/lamindb/references/integrations.md
- Network accessline 45
# Initialize with custom S3 endpoint lamin init --storage 's3://bucket?endpoint_url=http://minio.example.com:9000' - Network accessline 46
lamin init --storage 's3://bucket?endpoint_url=http://minio.example.com:9000' - Access to secretsline 50
[Credential-related source omitted] - Network accessline 70
# Access remote files without copying artifact = ln.Artifact( "https://example.com/data.csv", - Network accessline 71
artifact = ln.Artifact( "https://example.com/data.csv", key="remote/data.csv" - Network accessline 72
"https://example.com/data.csv", - Access to secretsline 111
[Credential-related source omitted] - Access to secretsline 120
[Credential-related source omitted] - Access to secretsline 140
[Credential-related source omitted] - Network accessline 490
# Configure git sync export LAMINDB_SYNC_GIT_REPO=https://github.com/user/repo.git - Network accessline 491
export LAMINDB_SYNC_GIT_REPO=https://github.com/user/repo.git - Network accessline 493
# Or programmatically ln.settings.sync_git_repo = "https://github.com/user/repo.git" - Network accessline 494
ln.settings.sync_git_repo = "https://github.com/user/repo.git" - Network accessline 534
# Fetch from API response = requests.get("https://api.example.com/data") - Network accessline 535
response = requests.get("https://api.example.com/data") - Access to secretsline 613
[Credential-related source omitted]
bundled/skills/lamindb/references/setup-deployment.md
- Network accessline 66
1. Visit https://lamin.ai - Network accessline 117
# S3-compatible (MinIO, Cloudflare R2) lamin init --storage 's3://bucket?endpoint_url=http://endpoint:9000' - Network accessline 118
lamin init --storage 's3://bucket?endpoint_url=http://endpoint:9000' - Access to secretsline 206
[Credential-related source omitted] - Access to secretsline 258
[Credential-related source omitted] - Network accessline 260
lamin init --storage 's3://my-bucket?endpoint_url=http://minio.example.com:9000' - Access to secretsline 264
[Credential-related source omitted] - Network accessline 266
lamin init --storage 's3://bucket?endpoint_url=https://account-id.r2.cloudflarestorage.com' - Dangerous shell operationline 351
sudo mkdir -p /system/settings - Dangerous shell operationline 352
sudo nano /system/settings/system.env - Dangerous shell operationline 362
sudo chmod 755 /shared/cache/lamindb - Dangerous shell operationline 363
sudo chown -R shared-user:shared-group /shared/cache/lamindb - Network accessline 406
# Configure git sync lamin settings set sync-git-repo https://github.com/user/repo.git - Network accessline 407
lamin settings set sync-git-repo https://github.com/user/repo.git - Network accessline 422
# Git sync export LAMINDB_SYNC_GIT_REPO=https://github.com/user/repo.git - Network accessline 423
export LAMINDB_SYNC_GIT_REPO=https://github.com/user/repo.git
bundled/skills/latchbio-integration/SKILL.md
- Network accessline 338
- **Official Documentation**: https://docs.latch.bio - Network accessline 339
- **GitHub Repository**: https://github.com/latchbio/latch - Network accessline 340
- **Slack Community**: Join Latch SDK workspace - **API Reference**: https://docs.latch.bio/api/latch.html - **Blog**: https://blog.latch.bio - Network accessline 341
- **API Reference**: https://docs.latch.bio/api/latch.html - Network accessline 342
- **Blog**: https://blog.latch.bio
bundled/skills/latchbio-integration/references/data-management.md
- Access to secretsline 380
[Credential-related source omitted]
bundled/skills/latchbio-integration/references/verified-workflows.md
- Network accessline 439
- **Documentation**: https://docs.latch.bio
bundled/skills/latchbio-integration/references/workflow-creation.md
bundled/skills/latex-posters/README.md
- Network accessline 386
### Online Tools - **Color contrast checker**: https://webaim.org/resources/contrastchecker/ - Network accessline 387
- **Color contrast checker**: https://webaim.org/resources/contrastchecker/ - Network accessline 388
- **Color blindness simulator**: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 389
- **Color palette generator**: https://coolors.co/
bundled/skills/latex-posters/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 256
% Link to paper, code repository, or supplementary materials \qrcode[height=2cm]{https://github.com/username/project} - Network accessline 257
\qrcode[height=2cm]{https://github.com/username/project} - Network accessline 259
% QR code with caption \begin{center} \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ - Network accessline 260
\begin{center} \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ \small Scan for full paper - Network accessline 261
\qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ - Network accessline 519
- [ ] Text-background contrast ratio ≥ 4.5:1 (WCAG AA) - [ ] Important elements contrast ratio ≥ 7:1 (WCAG AAA) - Test online: https://webaim.org/resources/contrastchecker/ - Network accessline 521
- Test online: https://webaim.org/resources/contrastchecker/
bundled/skills/latex-posters/assets/baposter_template.tex
- Network accessline 220
\headerbox{Scan for More}{name=qr,column=2,above=bottom}{ \begin{center} \qrcode[height=4cm]{https://doi.org/10.1234/your-paper}\\ - Network accessline 221
\begin{center} \qrcode[height=4cm]{https://doi.org/10.1234/your-paper}\\ \vspace{0.3cm} - Network accessline 222
\qrcode[height=4cm]{https://doi.org/10.1234/your-paper}\\
bundled/skills/latex-posters/assets/beamerposter_template.tex
- Network accessline 233
\begin{column}{.2\linewidth} \centering \qrcode[height=3.5cm]{https://doi.org/10.1234/your-paper}\\ - Network accessline 234
\centering \qrcode[height=3.5cm]{https://doi.org/10.1234/your-paper}\\ \tiny Scan for full paper - Network accessline 235
\qrcode[height=3.5cm]{https://doi.org/10.1234/your-paper}\\
bundled/skills/latex-posters/assets/poster_quality_checklist.md
- Network accessline 202
### Color Contrast Test at: https://webaim.org/resources/contrastchecker/ - Network accessline 203
Test at: https://webaim.org/resources/contrastchecker/ - Network accessline 209
### Color Blindness Test with simulator: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 210
Test with simulator: https://www.color-blindness.com/coblis-color-blindness-simulator/
bundled/skills/latex-posters/assets/tikzposter_template.tex
- Network accessline 209
\block{Scan for More}{ \begin{center} \qrcode[height=5cm]{https://doi.org/10.1234/your-paper}\\ - Network accessline 210
\begin{center} \qrcode[height=5cm]{https://doi.org/10.1234/your-paper}\\ \vspace{0.5cm} - Network accessline 211
\qrcode[height=5cm]{https://doi.org/10.1234/your-paper}\\
bundled/skills/latex-posters/references/latex_poster_packages.md
bundled/skills/latex-posters/references/poster_design_principles.md
bundled/skills/latex-posters/references/poster_layout_design.md
- Network accessline 508
\begin{column}{0.25\linewidth} \centering \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ - Network accessline 509
\centering \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ \tiny Scan for full paper - Network accessline 510
\qrcode[height=3cm]{https://doi.org/10.1234/paper}\\
bundled/skills/latex-posters/scripts/review_poster.sh
- Executable scriptline 1
#!/bin/bash
bundled/skills/latex-submission-pipeline/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/literature-review/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 278
- Date filters: `2020:2024[Publication Date]` - Boolean operators: AND, OR, NOT - See MeSH browser: https://meshb.nlm.nih.gov/search - Network accessline 280
- See MeSH browser: https://meshb.nlm.nih.gov/search - Network accessline 349
### APA (7th Edition) - In-text: (Smith et al., 2023) - Reference: Smith, J. D., Johnson, M. L., & Williams, K. R. (2023). Title. *Journal*, *22*(4), 301-318. https://doi.org/10.xxx/yyy - Network accessline 351
- Reference: Smith, J. D., Johnson, M. L., & Williams, K. R. (2023). Title. *Journal*, *22*(4), 301-318. https://doi.org/10.xxx/yyy - Network accessline 528
**Guidelines:** - PRISMA (Systematic Reviews): http://www.prisma-statement.org/ - Network accessline 529
- PRISMA (Systematic Reviews): http://www.prisma-statement.org/ - Network accessline 530
- Cochrane Handbook: https://training.cochrane.org/handbook - Network accessline 531
- AMSTAR 2 (Review Quality): https://amstar.ca/ - Network accessline 533
**Tools:** - MeSH Browser: https://meshb.nlm.nih.gov/search - Network accessline 534
- MeSH Browser: https://meshb.nlm.nih.gov/search - Network accessline 535
- PubMed Advanced Search: https://pubmed.ncbi.nlm.nih.gov/advanced/ - Network accessline 536
- Boolean Search Guide: https://www.ncbi.nlm.nih.gov/books/NBK3827/ - Network accessline 538
**Citation Styles:** - APA Style: https://apastyle.apa.org/ - Network accessline 539
- APA Style: https://apastyle.apa.org/ - Network accessline 540
- Nature Portfolio: https://www.nature.com/nature-portfolio/editorial-policies/reporting-standards - Network accessline 541
- NLM/Vancouver: https://www.nlm.nih.gov/bsd/uniform_requirements.html
bundled/skills/literature-review/assets/review_template.md
- Network accessline 272
APA: Author, A. A., & Author, B. B. (Year). Title. *Journal*, *volume*(issue), pages. https://doi.org/xx.xxxx - Network accessline 404
**Resources:** - PRISMA 2020: http://prisma-statement.org/ - Network accessline 405
- PRISMA 2020: http://prisma-statement.org/ - Network accessline 406
- PROSPERO: https://www.crd.york.ac.uk/prospero/ - Network accessline 407
- Cochrane Handbook: https://training.cochrane.org/handbook - Network accessline 408
- GRADE: https://www.gradeworkinggroup.org/
bundled/skills/literature-review/references/citation_styles.md
- Network accessline 9
**Format**: Author, A. A., Author, B. B., & Author, C. C. (Year). Title of article. *Title of Periodical*, *volume*(issue), page range. https://doi.org/xx.xxx/yyyy - Network accessline 11
**Example**: Smith, J. D., Johnson, M. L., & Williams, K. R. (2023). Machine learning approaches in drug discovery. *Nature Reviews Drug Discovery*, *22*(4), 301-318. https://doi.org/10.1038/nrd.2023.001 - Network accessline 15
**Format**: Author, A. A. (Year). *Title of work: Capital letter also for subtitle*. Publisher Name. https://doi.org/xxxx - Network accessline 27
**Format**: Author, A. A., & Author, B. B. (Year). Title of preprint. *Repository Name*. https://doi.org/xxxx - Network accessline 29
**Example**: Zhang, Y., Chen, L., & Wang, H. (2024). Novel therapeutic targets in Alzheimer's disease. *bioRxiv*. https://doi.org/10.1101/2024.01.001 - Network accessline 33
**Format**: Author, A. A. (Year, Month day-day). Title of paper. In E. E. Editor (Ed.), *Title of conference proceedings* (pp. xx-xx). Publisher. https://doi.org/xxxx - Network accessline 56
**Example**: Zhang, Y. et al. Novel therapeutic targets in Alzheimer's disease. *bioRxiv* https://doi.org/10.1101/2024.01.001 (2024). - Network accessline 64
**Format**: Author, First Name Middle Initial. Year. "Article Title." *Journal Title* volume, no. issue (Month): page range. https://doi.org/xxxx. - Network accessline 66
**Example**: Smith, John D., Mary L. Johnson, and Karen R. Williams. 2023. "Machine Learning Approaches in Drug Discovery." *Nature Reviews Drug Discovery* 22, no. 4 (April): 301-318. https://doi.org/10.1038/nrd.2023.001. - Network accessline 128
1. **Always verify DOIs**: Use the verify_citations.py script to check all DOIs 2. **Format as URLs**: https://doi.org/10.xxxx/yyyy (preferred over doi:10.xxxx/yyyy) - Network accessline 129
2. **Format as URLs**: https://doi.org/10.xxxx/yyyy (preferred over doi:10.xxxx/yyyy)
bundled/skills/literature-review/references/database_strategies.md
- Network accessline 444
### MeSH Browser https://meshb.nlm.nih.gov/search - Network accessline 445
https://meshb.nlm.nih.gov/search - Network accessline 447
### Boolean Search Tutorial https://www.ncbi.nlm.nih.gov/books/NBK3827/ - Network accessline 448
https://www.ncbi.nlm.nih.gov/books/NBK3827/ - Network accessline 453
### PRISMA Guidelines Preferred Reporting Items for Systematic Reviews and Meta-Analyses: http://www.prisma-statement.org/ - Network accessline 455
http://www.prisma-statement.org/
bundled/skills/literature-review/scripts/generate_pdf.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/literature-review/scripts/search_databases.py
bundled/skills/literature-review/scripts/verify_citations.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 14
class CitationVerifier: def __init__(self): self.session = requests.Session() - Network accessline 15
def __init__(self): self.session = requests.Session() self.session.headers.update({ - Network accessline 16
self.session = requests.Session() - Network accessline 31
try: url = f"https://doi.org/api/handles/{doi}" - Network accessline 32
url = f"https://doi.org/api/handles/{doi}" - Network accessline 46
try: url = f"https://api.crossref.org/works/{doi}" - Network accessline 47
url = f"https://api.crossref.org/works/{doi}" - Network accessline 155
citation += f", {pages}" if doi: citation += f". https://doi.org/{doi}" - Network accessline 157
citation += f". https://doi.org/{doi}"
bundled/skills/local-vco-roles/scripts/new-run.ps1
- Executable scriptline 1
Executable file
bundled/skills/manuscript-as-code/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/markdown-mermaid-writing/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 13
metadata: skill-author: Clayton Young / Superior Byte Works, LLC (@borealBytes) skill-source: https://github.com/SuperiorByteWorks-LLC/agent-project - Network accessline 14
skill-author: Clayton Young / Superior Byte Works, LLC (@borealBytes) skill-source: https://github.com/SuperiorByteWorks-LLC/agent-project skill-version: "1.0.0" - Network accessline 15
skill-source: https://github.com/SuperiorByteWorks-LLC/agent-project - Network accessline 324
- **Source**: https://github.com/SuperiorByteWorks-LLC/agent-project - Network accessline 332
[^1]: GitHub Blog. (2022). "Include diagrams in your Markdown files with Mermaid." https://github.blog/2022-02-14-include-diagrams-markdown-files-mermaid/ - Network accessline 334
[^2]: Mermaid. "Mermaid Diagramming and Charting Tool." https://mermaid.js.org/
bundled/skills/markdown-mermaid-writing/assets/examples/example-research-report.md
- Network accessline 215
[^1]: Ran, F.A. et al. (2013). "Genome engineering using the CRISPR-Cas9 system." _Nature Protocols_, 8(11), 2281–2308. https://doi.org/10.1038/nprot.2013.143 - Network accessline 217
[^2]: ATCC. (2024). "Cell Line Authentication and Quality Control." https://www.atcc.org/resources/technical-documents/cell-line-authentication - Network accessline 219
[^3]: Moreno-Mateos, M.A. et al. (2015). "CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo." _Nature Methods_, 12(10), 982–988. https://doi.org/10.1038/nmeth.3543 - Network accessline 221
[^4]: Molla, K.A. & Yang, Y. (2019). "CRISPR/Cas-Mediated Base Editing: Technical Considerations and Practical Applications." _Trends in Biotechnology_, 37(10), 1121–1142. https://doi.org/10.1016/j.tibtech.2019.03.008
bundled/skills/markdown-mermaid-writing/references/diagrams/architecture.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/block.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/c4.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/class.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/complex_examples.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/er.md
bundled/skills/markdown-mermaid-writing/references/diagrams/flowchart.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/gantt.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/git_graph.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/kanban.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/mindmap.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/packet.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/pie.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/quadrant.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/radar.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/requirement.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/sankey.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/sequence.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/state.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/timeline.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/treemap.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/user_journey.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/xy_chart.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/diagrams/zenuml.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/references/markdown_style_guide.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 197
- **Meaningful link text** — `[Mermaid Style Guide]` not `[click here]` or `[link]` - **Relative paths** for internal links — `[Guide](./README.md)` not absolute URLs - **Full URLs** for external links — always `https://` - Network accessline 199
- **Full URLs** for external links — always `https://` - Network accessline 210
[^1]: Gruber, J. (2004). "Markdown." _Daring Fireball_. https://daringfireball.net/projects/markdown/ - Network accessline 212
[^2]: GitHub Blog. (2022). "Include diagrams in your Markdown files with Mermaid." https://github.blog/2022-02-14-include-diagrams-markdown-files-mermaid/ - Network accessline 218
[^N]: Author/Org. (Year). "Title." *Publication*. https://full-url - Network accessline 237
[mermaid-docs]: https://mermaid.js.org/ 'Mermaid Documentation' - Network accessline 365
- Transition to next topic - **Bold** emphasis works inside details - [Links](https://example.com) work too - Network accessline 367
- [Links](https://example.com) work too - Possible obfuscationline 529
<U+200E>```mermaid - Possible obfuscationline 543
<U+200E>``` - Network accessline 677
[^1]: Stack Overflow. (2024). "Developer Survey Results." https://survey.stackoverflow.co/2024 - Network accessline 733
- [GitHub Flavored Markdown Spec](https://github.github.com/gfm/) · [Mermaid Style Guide](mermaid_style_guide.md) · [GitHub Basic Formatting](https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatti
bundled/skills/markdown-mermaid-writing/references/mermaid_style_guide.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 448
1. **GitHub:** Push to branch → toggle Profile → Settings → Appearance → Theme 2. **VS Code:** "Markdown Preview Mermaid Support" extension → `Cmd/Ctrl + Shift + V` 3. **Live editor:** [mermaid.live](https://mermaid.live/) — paste and toggl - Network accessline 449
2. **VS Code:** "Markdown Preview Mermaid Support" extension → `Cmd/Ctrl + Shift + V` 3. **Live editor:** [mermaid.live](https://mermaid.live/) — paste and toggle themes 4. **Screen reader:** Verify `accTitle`/`accDescr` announced (VoiceOve - Network accessline 450
3. **Live editor:** [mermaid.live](https://mermaid.live/) — paste and toggle themes - Network accessline 457
- [Markdown Style Guide](markdown_style_guide.md) — Formatting, citations, and document structure for the markdown that wraps your diagrams - [Mermaid Docs](https://mermaid.js.org/) · [Live Editor](https://mermaid.live/) · [Accessibility](h - Network accessline 458
- [Mermaid Docs](https://mermaid.js.org/) · [Live Editor](https://mermaid.live/) · [Accessibility](https://mermaid.js.org/config/accessibility.html) · [GitHub Support](https://github.blog/2022-02-14-include-diagrams-markdown-files-mermaid/)
bundled/skills/markdown-mermaid-writing/templates/decision_record.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 197
- [Related ADR or RFC](../adr/ADR-001-agent-optimized-documentation-system.md) - [External documentation or benchmark](https://example.com) - Network accessline 198
- [External documentation or benchmark](https://example.com)
bundled/skills/markdown-mermaid-writing/templates/how_to_guide.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 71
| Requirement | Version | Verify with | Install link | | ---------------- | ----------- | --------------------- | ------------------------------------ | | [Tool/Runtime] | ≥ [version] | `[command - Network accessline 72
| ---------------- | ----------- | --------------------- | ------------------------------------ | | [Tool/Runtime] | ≥ [version] | `[command] --version` | [Install guide](https://example.com) | | [Dependency] | ≥ [version] | `[command - Network accessline 73
| [Tool/Runtime] | ≥ [version] | `[command] --version` | [Install guide](https://example.com) | - Network accessline 74
| [Dependency] | ≥ [version] | `[command] --version` | [Install guide](https://example.com) | - Network accessline 75
| [Account/Access] | — | [How to verify] | [Sign up](https://example.com) | - Network accessline 270
- [Official documentation](https://example.com) — [Which section is most relevant] - Network accessline 271
- [Source repository](https://github.com/SuperiorByteWorks-LLC) — [For bug reports and contributions]
bundled/skills/markdown-mermaid-writing/templates/issue.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 180
- [Related issues](../../docs/project/issues/issue-00000001-agentic-documentation-system.md) - [Relevant documentation](https://example.com) - Network accessline 181
- [Relevant documentation](https://example.com) - Network accessline 182
- [Monitoring dashboard or alert](https://example.com) - Network accessline 296
- [User feedback or support tickets](https://example.com) - [Competitive analysis](https://example.com) - [Related feature requests](../../docs/project/issues/issue-00000001-agentic-documentation-system.md) - Network accessline 297
- [Competitive analysis](https://example.com) - [Related feature requests](../../docs/project/issues/issue-00000001-agentic-documentation-system.md) - [Design document or ADR](../adr/ADR-001-agent-optimized-documentation-system.md)
bundled/skills/markdown-mermaid-writing/templates/kanban.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->
bundled/skills/markdown-mermaid-writing/templates/presentation.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 290
[^1]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 294
- [Resource title](https://example.com) — Why this is useful - Network accessline 295
- [Resource title](https://example.com) — What it provides - Network accessline 299
- [Tool name](https://example.com) — Purpose and how to access
bundled/skills/markdown-mermaid-writing/templates/project_documentation.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 37
[]() []() - Network accessline 67
# Clone the repository git clone https://github.com/[org]/[repo].git - Network accessline 68
git clone https://github.com/[org]/[repo].git - Access to secretsline 75
[Credential-related source omitted] - Access to secretsline 76
[Credential-related source omitted] - Network accessline 85
curl http://localhost:[port]/health - Network accessline 374
# Fork and clone git clone https://github.com/[your-fork]/[repo].git - Network accessline 375
git clone https://github.com/[your-fork]/[repo].git - Network accessline 406
- [Official framework docs](https://example.com) — [What version and which sections are most relevant] - Network accessline 407
- [API specification](https://example.com) — [OpenAPI/Swagger link if applicable]
bundled/skills/markdown-mermaid-writing/templates/pull_request.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 28
- **Naming:** `pr-` + PR number zero-padded to 8 digits + `-` + short lowercase hyphenated description - **Cross-reference:** Link to the live PR in the metadata table - **GitHub PR body:** Use only the full branch URL to this file (for exa - Network accessline 30
- **GitHub PR body:** Use only the full branch URL to this file (for example, `https://github.com/<org>/<repo>/blob/<branch>/docs/project/pr/pr-00000123-fix-auth-timeout.md`) - Network accessline 313
- [Design document or ADR](../adr/ADR-001-agent-optimized-documentation-system.md) - [Related issue](../../docs/project/issues/issue-00000001-agentic-documentation-system.md) - [Relevant documentation](https://example.com) - Network accessline 315
- [Relevant documentation](https://example.com)
bundled/skills/markdown-mermaid-writing/templates/research_paper.md
- Network accessline 1
<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) --> - Network accessline 288
[^1]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 290
[^2]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 292
[^3]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 294
[^4]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 296
[^5]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 298
[^6]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com> - Network accessline 300
[^7]: [Author/Org]. ([Year]). "[Title]." _[Publication]_. <https://example.com>
bundled/skills/markdown-mermaid-writing/templates/status_report.md
bundled/skills/market-research-reports/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/market-research-reports/scripts/generate_market_visuals.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/markitdown/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 85
# Or from source git clone https://github.com/microsoft/markitdown.git - Network accessline 86
git clone https://github.com/microsoft/markitdown.git - Network accessline 135
[Credential-related source omitted] - Network accessline 136
[Credential-related source omitted] - Access to secretsline 136
[Credential-related source omitted] - Network accessline 137
base_url="https://openrouter.ai/api/v1" - Network accessline 258
[Credential-related source omitted] - Network accessline 259
[Credential-related source omitted] - Access to secretsline 259
[Credential-related source omitted] - Network accessline 260
base_url="https://openrouter.ai/api/v1" - Network accessline 308
# Convert YouTube video to transcript result = md.convert("https://www.youtube.com/watch?v=VIDEO_ID") - Network accessline 309
result = md.convert("https://www.youtube.com/watch?v=VIDEO_ID") - Network accessline 415
[Credential-related source omitted] - Network accessline 416
[Credential-related source omitted] - Access to secretsline 416
[Credential-related source omitted] - Network accessline 417
base_url="https://openrouter.ai/api/v1" - Dangerous shell operationline 461
sudo apt-get install tesseract-ocr - Network accessline 480
- **MarkItDown GitHub**: https://github.com/microsoft/markitdown - Network accessline 481
- **PyPI**: https://pypi.org/project/markitdown/ - Network accessline 482
- **OpenRouter**: https://openrouter.ai (for AI-enhanced conversions) - Network accessline 483
- **OpenRouter API Keys**: https://openrouter.ai/keys - Network accessline 484
- **OpenRouter Models**: https://openrouter.ai/models
bundled/skills/markitdown/assets/example_usage.md
- Network accessline 129
[Credential-related source omitted] - Network accessline 130
[Credential-related source omitted] - Access to secretsline 130
[Credential-related source omitted] - Network accessline 131
base_url="https://openrouter.ai/api/v1" - Network accessline 162
[Credential-related source omitted] - Network accessline 163
[Credential-related source omitted] - Access to secretsline 163
[Credential-related source omitted] - Network accessline 164
base_url="https://openrouter.ai/api/v1" - Network accessline 320
# Get transcript video_url = "https://www.youtube.com/watch?v=VIDEO_ID" - Network accessline 321
video_url = "https://www.youtube.com/watch?v=VIDEO_ID"
bundled/skills/markitdown/references/api_reference.md
- Network accessline 230
[Credential-related source omitted] - Network accessline 231
[Credential-related source omitted] - Access to secretsline 231
[Credential-related source omitted] - Network accessline 232
base_url="https://openrouter.ai/api/v1" - Network accessline 252
See https://openrouter.ai/models for the complete list. - Network accessline 287
md = MarkItDown( docintel_endpoint="https://YOUR-RESOURCE.cognitiveservices.azure.com/" - Network accessline 288
docintel_endpoint="https://YOUR-RESOURCE.cognitiveservices.azure.com/" - Access to secretsline 298
[Credential-related source omitted] - Network accessline 393
[Credential-related source omitted] - Access to secretsline 393
[Credential-related source omitted] - Network accessline 395
| `AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT` | Azure DI endpoint | `https://...` |
bundled/skills/markitdown/references/file_formats.md
bundled/skills/markitdown/scripts/batch_convert.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/markitdown/scripts/convert_literature.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/markitdown/scripts/convert_with_ai.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 73
[Credential-related source omitted] - Access to secretsline 84
[Credential-related source omitted] - Network accessline 94
[Credential-related source omitted] - Network accessline 95
[Credential-related source omitted] - Access to secretsline 95
[Credential-related source omitted] - Network accessline 96
base_url="https://openrouter.ai/api/v1" - Access to secretsline 163
[Credential-related source omitted] - Access to secretsline 167
[Credential-related source omitted] - Access to secretsline 179
[Credential-related source omitted] - Access to secretsline 214
[Credential-related source omitted] - Network accessline 215
[Credential-related source omitted] - Access to secretsline 215
[Credential-related source omitted] - Network accessline 216
[Credential-related source omitted] - Access to secretsline 216
[Credential-related source omitted] - Network accessline 217
print("Get your API key at: https://openrouter.ai/keys") - Access to secretsline 229
[Credential-related source omitted]
bundled/skills/matchms/references/importing_exporting.md
- Network accessline 406
For detailed format specifications: - **MGF**: http://www.matrixscience.com/help/data_file_help.html - Network accessline 407
- **MGF**: http://www.matrixscience.com/help/data_file_help.html - Network accessline 408
- **MSP**: https://chemdata.nist.gov/mass-spc/ms-search/ - Network accessline 409
- **mzML**: http://www.psidev.info/mzML - Network accessline 410
- **GNPS JSON**: https://gnps.ucsd.edu/ - Network accessline 414
For complete API documentation: https://matchms.readthedocs.io/en/latest/api/matchms.importing.html - Network accessline 415
https://matchms.readthedocs.io/en/latest/api/matchms.importing.html - Network accessline 416
https://matchms.readthedocs.io/en/latest/api/matchms.exporting.html
bundled/skills/matchms/references/similarity.md
bundled/skills/matchms/references/workflows.md
bundled/skills/math-tools/references/api_reference.md
- Dangerous shell operationline 370
python math_calculator.py eval "sqrt(2)"
bundled/skills/math-tools/scripts/math_calculator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/math/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/matlab/SKILL.md
- Network accessline 2
name: matlab description: MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processin - Network accessline 3
description: MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differenti - Network accessline 4
license: For MATLAB (https://www.mathworks.com/pricing-licensing.html) and for Octave (GNU General Public License version 3) - Dangerous shell operationline 35
sudo apt install octave - Network accessline 37
# Windows - download from https://octave.org/download - Network accessline 373
- MATLAB Documentation: https://www.mathworks.com/help/matlab/ - Network accessline 374
- GNU Octave Manual: https://docs.octave.org/latest/ - Network accessline 375
- MATLAB Onramp (free course): https://www.mathworks.com/learn/tutorials/matlab-onramp.html - Network accessline 376
- File Exchange: https://www.mathworks.com/matlabcentral/fileexchange/
bundled/skills/matlab/references/octave-compatibility.md
- Dangerous shell operationline 24
sudo apt install octave - Dangerous shell operationline 27
sudo dnf install octave - Network accessline 29
# Windows # Download installer from https://octave.org/download - Network accessline 30
# Download installer from https://octave.org/download - Network accessline 493
% Install from URL pkg install 'http://example.com/package.tar.gz' - Network accessline 494
pkg install 'http://example.com/package.tar.gz'
bundled/skills/matlab/references/python-integration.md
bundled/skills/matplotlib/SKILL.md
- Network accessline 352
- Official documentation: https://matplotlib.org/ - Network accessline 353
- Gallery: https://matplotlib.org/stable/gallery/index.html - Network accessline 354
- Cheatsheets: https://matplotlib.org/cheatsheets/ - Network accessline 355
- Tutorials: https://matplotlib.org/stable/tutorials/index.html
bundled/skills/matplotlib/references/api_reference.md
bundled/skills/matplotlib/scripts/plot_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/matplotlib/scripts/style_configurator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/mcp-integration/SKILL.md
- Network accessline 102
"asana": { "type": "sse", "url": "https://mcp.asana.com/sse" - Network accessline 103
"type": "sse", "url": "https://mcp.asana.com/sse" } - Network accessline 104
"url": "https://mcp.asana.com/sse" - Network accessline 127
"api-service": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 128
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 129
"url": "https://api.example.com/mcp", - Access to secretsline 131
[Credential-related source omitted] - Access to secretsline 182
[Credential-related source omitted] - Network accessline 248
{ "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 249
"type": "sse", "url": "https://mcp.example.com/sse" } - Network accessline 250
"url": "https://mcp.example.com/sse" - Network accessline 261
{ "type": "http", "url": "https://api.example.com", - Network accessline 262
"type": "http", "url": "https://api.example.com", "headers": { - Network accessline 263
"url": "https://api.example.com", - Access to secretsline 265
[Credential-related source omitted] - Access to secretsline 282
[Credential-related source omitted] - Network accessline 329
"github": { "type": "sse", "url": "https://mcp.github.com/sse" - Network accessline 330
"type": "sse", "url": "https://mcp.github.com/sse" }, - Network accessline 331
"url": "https://mcp.github.com/sse" - Network accessline 333
"jira": { "type": "sse", "url": "https://mcp.jira.com/sse" - Network accessline 334
"type": "sse", "url": "https://mcp.jira.com/sse" } - Network accessline 335
"url": "https://mcp.jira.com/sse" - Network accessline 349
✅ "url": "https://mcp.example.com/sse" - Network accessline 350
❌ "url": "http://mcp.example.com/sse" - Network accessline 535
- **Official MCP Docs**: https://modelcontextprotocol.io/ - Network accessline 536
- **Claude Code MCP Docs**: https://docs.claude.com/en/docs/claude-code/mcp
bundled/skills/mcp-integration/examples/http-server.json
- Network accessline 3
"rest-api": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 4
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 5
"url": "https://api.example.com/mcp", - Access to secretsline 7
[Credential-related source omitted] - Network accessline 12
"internal-service": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 13
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 14
"url": "https://api.example.com/mcp", - Access to secretsline 16
[Credential-related source omitted]
bundled/skills/mcp-integration/examples/sse-server.json
- Network accessline 3
"asana": { "type": "sse", "url": "https://mcp.asana.com/sse" - Network accessline 4
"type": "sse", "url": "https://mcp.asana.com/sse" }, - Network accessline 5
"url": "https://mcp.asana.com/sse" - Network accessline 7
"github": { "type": "sse", "url": "https://mcp.github.com/sse" - Network accessline 8
"type": "sse", "url": "https://mcp.github.com/sse" }, - Network accessline 9
"url": "https://mcp.github.com/sse" - Network accessline 11
"custom-service": { "type": "sse", "url": "https://mcp.example.com/sse", - Network accessline 12
"type": "sse", "url": "https://mcp.example.com/sse", "headers": { - Network accessline 13
"url": "https://mcp.example.com/sse",
bundled/skills/mcp-integration/examples/stdio-server.json
- Access to secretsline 22
[Credential-related source omitted]
bundled/skills/mcp-integration/references/authentication.md
- Network accessline 26
"service": { "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 27
"type": "sse", "url": "https://mcp.example.com/sse" } - Network accessline 28
"url": "https://mcp.example.com/sse" - Network accessline 37
**Known OAuth-enabled MCP servers:** - Asana: `https://mcp.asana.com/sse` - Network accessline 38
- Asana: `https://mcp.asana.com/sse` - Network accessline 89
"api": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 90
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 91
"url": "https://api.example.com/mcp", - Access to secretsline 93
[Credential-related source omitted] - Access to secretsline 101
[Credential-related source omitted] - Network accessline 111
"api": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 112
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 113
"url": "https://api.example.com/mcp", - Access to secretsline 115
[Credential-related source omitted] - Access to secretsline 116
[Credential-related source omitted] - Network accessline 129
"service": { "type": "sse", "url": "https://mcp.example.com/sse", - Network accessline 130
"type": "sse", "url": "https://mcp.example.com/sse", "headers": { - Network accessline 131
"url": "https://mcp.example.com/sse", - Access to secretsline 133
[Credential-related source omitted] - Access to secretsline 153
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Network accessline 159
1. Visit https://api.example.com/tokens - Access to secretsline 223
[Credential-related source omitted] - Network accessline 235
"api": { "type": "sse", "url": "https://api.example.com", - Network accessline 236
"type": "sse", "url": "https://api.example.com", "headersHelper": "${CLAUDE_PLUGIN_ROOT}/scripts/get-headers.sh" - Network accessline 237
"url": "https://api.example.com", - Access to secretsline 275
[Credential-related source omitted] - Network accessline 318
"api": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 319
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 320
"url": "https://api.example.com/mcp", - Access to secretsline 322
[Credential-related source omitted] - Network accessline 332
"api": { "type": "http", "url": "https://${TENANT_ID}.api.example.com/mcp" - Network accessline 333
"type": "http", "url": "https://${TENANT_ID}.api.example.com/mcp" } - Network accessline 334
"url": "https://${TENANT_ID}.api.example.com/mcp" - Access to secretsline 367
[Credential-related source omitted] - Access to secretsline 370
[Credential-related source omitted] - Network accessline 397
[Credential-related source omitted] - Network accessline 398
[Credential-related source omitted] - Access to secretsline 398
[Credential-related source omitted] - Network accessline 399
https://api.example.com/mcp/health - Access to secretsline 421
[Credential-related source omitted] - Network accessline 446
{ "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 447
"type": "sse", "url": "https://mcp.example.com/sse" } - Network accessline 448
"url": "https://mcp.example.com/sse" - Network accessline 472
[Credential-related source omitted] - Access to secretsline 472
[Credential-related source omitted] - Network accessline 473
"env": { "API_URL": "https://secure.example.com" } - Network accessline 474
"API_URL": "https://secure.example.com" - Access to secretsline 509
[Credential-related source omitted] - Access to secretsline 515
[Credential-related source omitted] - Access to secretsline 538
[Credential-related source omitted]
bundled/skills/mcp-integration/references/server-types.md
- Access to secretsline 30
[Credential-related source omitted] - Network accessline 112
"hosted-service": { "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 113
"type": "sse", "url": "https://mcp.example.com/sse" } - Network accessline 114
"url": "https://mcp.example.com/sse" - Network accessline 122
"service": { "type": "sse", "url": "https://mcp.example.com/sse", - Network accessline 123
"type": "sse", "url": "https://mcp.example.com/sse", "headers": { - Network accessline 124
"url": "https://mcp.example.com/sse", - Network accessline 146
"asana": { "type": "sse", "url": "https://mcp.asana.com/sse" - Network accessline 147
"type": "sse", "url": "https://mcp.asana.com/sse" } - Network accessline 148
"url": "https://mcp.asana.com/sse" - Network accessline 162
"service": { "type": "sse", "url": "https://mcp.example.com/sse", - Network accessline 163
"type": "sse", "url": "https://mcp.example.com/sse", "headers": { - Network accessline 164
"url": "https://mcp.example.com/sse", - Access to secretsline 166
[Credential-related source omitted] - Network accessline 174
**Official Services:** - Asana: `https://mcp.asana.com/sse` - Network accessline 175
- Asana: `https://mcp.asana.com/sse` - Network accessline 176
- GitHub: `https://mcp.github.com/sse` - Network accessline 215
"api": { "type": "http", "url": "https://api.example.com/mcp" - Network accessline 216
"type": "http", "url": "https://api.example.com/mcp" } - Network accessline 217
"url": "https://api.example.com/mcp" - Network accessline 225
"api": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 226
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 227
"url": "https://api.example.com/mcp", - Access to secretsline 229
[Credential-related source omitted] - Access to secretsline 250
[Credential-related source omitted] - Access to secretsline 259
[Credential-related source omitted] - Access to secretsline 268
[Credential-related source omitted] - Network accessline 427
"hosted-server": { "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 428
"type": "sse", "url": "https://mcp.example.com/sse" } - Network accessline 429
"url": "https://mcp.example.com/sse" - Network accessline 439
"api": { "type": "http", "url": "https://api.example.com/mcp" - Network accessline 440
"type": "http", "url": "https://api.example.com/mcp" } - Network accessline 441
"url": "https://api.example.com/mcp" - Network accessline 470
"cloud-api": { "type": "sse", "url": "https://mcp.example.com/sse" - Network accessline 471
"type": "sse", "url": "https://mcp.example.com/sse" }, - Network accessline 472
"url": "https://mcp.example.com/sse" - Network accessline 474
"internal-service": { "type": "http", "url": "https://api.example.com/mcp", - Network accessline 475
"type": "http", "url": "https://api.example.com/mcp", "headers": { - Network accessline 476
"url": "https://api.example.com/mcp", - Access to secretsline 478
[Credential-related source omitted] - Access to secretsline 494
[Credential-related source omitted] - Network accessline 500
Set different values for dev/prod: - Dev: `API_URL=http://localhost:8080/mcp` - Network accessline 501
- Dev: `API_URL=http://localhost:8080/mcp` - Network accessline 502
- Prod: `API_URL=https://api.production.com/mcp`
bundled/skills/medchem/SKILL.md
bundled/skills/medchem/scripts/filter_molecules.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/metabolomics-workbench-database/SKILL.md
- Network accessline 32
# Get compound information by PubChem CID response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/pubchem_cid/5281365/all/json') - Network accessline 33
response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/pubchem_cid/5281365/all/json') - Network accessline 35
# Download molecular structure as PNG response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/11/png') - Network accessline 36
response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/11/png') - Network accessline 38
# Get compound name by registry number response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/11/name/json') - Network accessline 39
response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/11/name/json') - Network accessline 55
# List all available public studies response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST/available/json') - Network accessline 56
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST/available/json') - Network accessline 58
# Get study summary response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/summary/json') - Network accessline 59
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/summary/json') - Network accessline 61
# Retrieve experimental data response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/data/json') - Network accessline 62
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/data/json') - Network accessline 64
# Find studies containing a specific metabolite response = requests.get('https://www.metabolomicsworkbench.org/rest/study/refmet_name/Tyrosine/summary/json') - Network accessline 65
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/refmet_name/Tyrosine/summary/json') - Network accessline 80
# Standardize a metabolite name response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/match/citrate/name/json') - Network accessline 81
response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/match/citrate/name/json') - Network accessline 83
# Query by molecular formula response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/formula/C12H24O2/all/json') - Network accessline 84
response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/formula/C12H24O2/all/json') - Network accessline 86
# Get all metabolites in a specific class response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/main_class/Fatty%20Acids/all/json') - Network accessline 87
response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/main_class/Fatty%20Acids/all/json') - Network accessline 89
# Retrieve complete RefMet database response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/all/json') - Network accessline 90
response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/all/json') - Network accessline 105
# Search by m/z value with M+H adduct response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/MB/635.52/M+H/0.5/json') - Network accessline 106
response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/MB/635.52/M+H/0.5/json') - Network accessline 108
# Calculate exact mass for a metabolite with specific adduct response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/exactmass/PC(34:1)/M+H/json') - Network accessline 109
response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/exactmass/PC(34:1)/M+H/json') - Network accessline 111
# Search across RefMet database response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/REFMET/200.15/M-H/0.3/json') - Network accessline 112
response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/REFMET/200.15/M-H/0.3/json') - Network accessline 128
# Find human blood studies on diabetes using LC-MS response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/LCMS;POSITIVE;HILIC;Human;Blood;Diabetes/json') - Network accessline 129
response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/LCMS;POSITIVE;HILIC;Human;Blood;Diabetes/json') - Network accessline 131
# Find all human blood studies containing tyrosine response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/;;;Human;Blood;;;Tyrosine/json') - Network accessline 132
response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/;;;Human;Blood;;;Tyrosine/json') - Network accessline 134
# Filter by analytical method only response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/GCMS;;;;;;/json') - Network accessline 135
response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/GCMS;;;;;;/json') - Network accessline 150
# Get gene information by symbol response = requests.get('https://www.metabolomicsworkbench.org/rest/gene/gene_symbol/ACACA/all/json') - Network accessline 151
response = requests.get('https://www.metabolomicsworkbench.org/rest/gene/gene_symbol/ACACA/all/json') - Network accessline 153
# Retrieve protein data by UniProt ID response = requests.get('https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/all/json') - Network accessline 154
response = requests.get('https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/all/json') - Network accessline 165
response = requests.get('https://www.metabolomicsworkbench.org/rest/refmet/match/glucose/name/json') - Network accessline 170
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/refmet_name/Glucose/summary/json') - Network accessline 175
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/data/json') - Network accessline 184
response = requests.get('https://www.metabolomicsworkbench.org/rest/moverz/MB/180.06/M+H/0.5/json') - Network accessline 191
response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/{regno}/all/json') - Network accessline 196
response = requests.get('https://www.metabolomicsworkbench.org/rest/compound/regno/{regno}/png') - Network accessline 205
response = requests.get('https://www.metabolomicsworkbench.org/rest/metstat/LCMS;POSITIVE;;Human;;Cancer/json') - Network accessline 212
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST{ID}/summary/json') - Network accessline 217
response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST{ID}/data/json')
bundled/skills/metabolomics-workbench-database/references/api_reference.md
- Network accessline 7
https://www.metabolomicsworkbench.org/rest/ - Network accessline 69
# Get all compound data by PubChem CID curl "https://www.metabolomicsworkbench.org/rest/compound/pubchem_cid/5281365/all/json" - Network accessline 70
curl "https://www.metabolomicsworkbench.org/rest/compound/pubchem_cid/5281365/all/json" - Network accessline 72
# Get compound name by registry number curl "https://www.metabolomicsworkbench.org/rest/compound/regno/11/name/json" - Network accessline 73
curl "https://www.metabolomicsworkbench.org/rest/compound/regno/11/name/json" - Network accessline 75
# Download structure as PNG curl "https://www.metabolomicsworkbench.org/rest/compound/regno/11/png" -o structure.png - Network accessline 76
curl "https://www.metabolomicsworkbench.org/rest/compound/regno/11/png" -o structure.png - Network accessline 78
# Get compound by KEGG ID curl "https://www.metabolomicsworkbench.org/rest/compound/kegg_id/C00031/all/json" - Network accessline 79
curl "https://www.metabolomicsworkbench.org/rest/compound/kegg_id/C00031/all/json" - Network accessline 81
# Get compound by molecular formula curl "https://www.metabolomicsworkbench.org/rest/compound/formula/C6H12O6/all/json" - Network accessline 82
curl "https://www.metabolomicsworkbench.org/rest/compound/formula/C6H12O6/all/json" - Network accessline 125
# List all publicly available studies curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST/available/json" - Network accessline 126
curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST/available/json" - Network accessline 128
# Get study summary curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/summary/json" - Network accessline 129
curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/summary/json" - Network accessline 131
# Get experimental data curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/data/json" - Network accessline 132
curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/data/json" - Network accessline 134
# Get study factors curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/factors/json" - Network accessline 135
curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/factors/json" - Network accessline 137
# Find studies containing a specific metabolite curl "https://www.metabolomicsworkbench.org/rest/study/refmet_name/Tyrosine/summary/json" - Network accessline 138
curl "https://www.metabolomicsworkbench.org/rest/study/refmet_name/Tyrosine/summary/json" - Network accessline 140
# Search studies by investigator curl "https://www.metabolomicsworkbench.org/rest/study/last_name/Smith/summary/json" - Network accessline 141
curl "https://www.metabolomicsworkbench.org/rest/study/last_name/Smith/summary/json" - Network accessline 143
# Download complete study in mwTab format curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/mwtab/txt" - Network accessline 144
curl "https://www.metabolomicsworkbench.org/rest/study/study_id/ST000001/mwtab/txt" - Network accessline 186
# Standardize a metabolite name curl "https://www.metabolomicsworkbench.org/rest/refmet/match/citrate/name/json" - Network accessline 187
curl "https://www.metabolomicsworkbench.org/rest/refmet/match/citrate/name/json" - Network accessline 189
# Get all RefMet data for a metabolite curl "https://www.metabolomicsworkbench.org/rest/refmet/name/Glucose/all/json" - Network accessline 190
curl "https://www.metabolomicsworkbench.org/rest/refmet/name/Glucose/all/json" - Network accessline 192
# Query by molecular formula curl "https://www.metabolomicsworkbench.org/rest/refmet/formula/C6H12O6/all/json" - Network accessline 193
curl "https://www.metabolomicsworkbench.org/rest/refmet/formula/C6H12O6/all/json" - Network accessline 195
# Get all metabolites in a main class curl "https://www.metabolomicsworkbench.org/rest/refmet/main_class/Fatty%20Acids/all/json" - Network accessline 196
curl "https://www.metabolomicsworkbench.org/rest/refmet/main_class/Fatty%20Acids/all/json" - Network accessline 198
# Query by exact mass curl "https://www.metabolomicsworkbench.org/rest/refmet/exactmass/180.0634/all/json" - Network accessline 199
curl "https://www.metabolomicsworkbench.org/rest/refmet/exactmass/180.0634/all/json" - Network accessline 201
# Download complete RefMet database curl "https://www.metabolomicsworkbench.org/rest/refmet/all/json" - Network accessline 202
curl "https://www.metabolomicsworkbench.org/rest/refmet/all/json" - Network accessline 242
# Human blood diabetes studies with LC-MS HILIC positive mode curl "https://www.metabolomicsworkbench.org/rest/metstat/LCMS;POSITIVE;HILIC;Human;Blood;Diabetes/json" - Network accessline 243
curl "https://www.metabolomicsworkbench.org/rest/metstat/LCMS;POSITIVE;HILIC;Human;Blood;Diabetes/json" - Network accessline 245
# All human blood studies containing tyrosine curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;Human;Blood;;;Tyrosine/json" - Network accessline 246
curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;Human;Blood;;;Tyrosine/json" - Network accessline 248
# All GC-MS studies regardless of other parameters curl "https://www.metabolomicsworkbench.org/rest/metstat/GCMS;;;;;;/json" - Network accessline 249
curl "https://www.metabolomicsworkbench.org/rest/metstat/GCMS;;;;;;/json" - Network accessline 251
# Mouse liver studies curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;Mouse;Liver;;/json" - Network accessline 252
curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;Mouse;Liver;;/json" - Network accessline 254
# All studies measuring glucose curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;;;;;Glucose/json" - Network accessline 255
curl "https://www.metabolomicsworkbench.org/rest/metstat/;;;;;;;Glucose/json" - Network accessline 318
# Search for compounds with m/z 635.52 (M+H) in MB database curl "https://www.metabolomicsworkbench.org/rest/moverz/MB/635.52/M+H/0.5/json" - Network accessline 319
curl "https://www.metabolomicsworkbench.org/rest/moverz/MB/635.52/M+H/0.5/json" - Network accessline 321
# Search in RefMet with negative mode curl "https://www.metabolomicsworkbench.org/rest/moverz/REFMET/200.15/M-H/0.3/json" - Network accessline 322
curl "https://www.metabolomicsworkbench.org/rest/moverz/REFMET/200.15/M-H/0.3/json" - Network accessline 324
# Search lipids database curl "https://www.metabolomicsworkbench.org/rest/moverz/LIPIDS/760.59/M+Na/0.5/json" - Network accessline 325
curl "https://www.metabolomicsworkbench.org/rest/moverz/LIPIDS/760.59/M+Na/0.5/json" - Network accessline 327
# Calculate exact mass for known metabolite curl "https://www.metabolomicsworkbench.org/rest/moverz/exactmass/PC(34:1)/M+H/json" - Network accessline 328
curl "https://www.metabolomicsworkbench.org/rest/moverz/exactmass/PC(34:1)/M+H/json" - Network accessline 330
# High-resolution MS search (tight tolerance) curl "https://www.metabolomicsworkbench.org/rest/moverz/MB/180.0634/M+H/0.01/json" - Network accessline 331
curl "https://www.metabolomicsworkbench.org/rest/moverz/MB/180.0634/M+H/0.01/json" - Network accessline 369
# Get gene information by symbol curl "https://www.metabolomicsworkbench.org/rest/gene/gene_symbol/ACACA/all/json" - Network accessline 370
curl "https://www.metabolomicsworkbench.org/rest/gene/gene_symbol/ACACA/all/json" - Network accessline 372
# Get gene by NCBI Gene ID curl "https://www.metabolomicsworkbench.org/rest/gene/gene_id/31/all/json" - Network accessline 373
curl "https://www.metabolomicsworkbench.org/rest/gene/gene_id/31/all/json" - Network accessline 375
# Search by gene name curl "https://www.metabolomicsworkbench.org/rest/gene/gene_name/carboxylase/summary/json" - Network accessline 376
curl "https://www.metabolomicsworkbench.org/rest/gene/gene_name/carboxylase/summary/json" - Network accessline 424
# Get protein information by UniProt ID curl "https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/all/json" - Network accessline 425
curl "https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/all/json" - Network accessline 427
# Get protein by gene symbol curl "https://www.metabolomicsworkbench.org/rest/protein/gene_symbol/ACACA/all/json" - Network accessline 428
curl "https://www.metabolomicsworkbench.org/rest/protein/gene_symbol/ACACA/all/json" - Network accessline 430
# Get protein sequence curl "https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/seq/json" - Network accessline 431
curl "https://www.metabolomicsworkbench.org/rest/protein/uniprot_id/Q13085/seq/json" - Network accessline 433
# Search by RefSeq ID curl "https://www.metabolomicsworkbench.org/rest/protein/refseq_id/NP_001084/all/json" - Network accessline 434
curl "https://www.metabolomicsworkbench.org/rest/protein/refseq_id/NP_001084/all/json" - Network accessline 458
- **Interactive REST URL Creator**: https://www.metabolomicsworkbench.org/tools/mw_rest.php - Network accessline 459
- **Official API Specification**: https://www.metabolomicsworkbench.org/tools/MWRestAPIv1.1.pdf - Network accessline 470
# 1. Standardize metabolite name using RefMet metabolite = "citrate" response = requests.get(f'https://www.metabolomicsworkbench.org/rest/refmet/match/{metabolite}/name/json') - Network accessline 471
metabolite = "citrate" response = requests.get(f'https://www.metabolomicsworkbench.org/rest/refmet/match/{metabolite}/name/json') standardized_name = response.json()['name'] - Network accessline 472
response = requests.get(f'https://www.metabolomicsworkbench.org/rest/refmet/match/{metabolite}/name/json') - Network accessline 475
# 2. Search for studies containing this metabolite response = requests.get(f'https://www.metabolomicsworkbench.org/rest/study/refmet_name/{standardized_name}/summary/json') - Network accessline 476
response = requests.get(f'https://www.metabolomicsworkbench.org/rest/study/refmet_name/{standardized_name}/summary/json') - Network accessline 479
# 3. Get detailed data from a specific study study_id = studies[0]['study_id'] response = requests.get(f'https://www.metabolomicsworkbench.org/rest/study/study_id/{study_id}/data/json') - Network accessline 480
study_id = studies[0]['study_id'] response = requests.get(f'https://www.metabolomicsworkbench.org/rest/study/study_id/{study_id}/data/json') data = response.json() - Network accessline 481
response = requests.get(f'https://www.metabolomicsworkbench.org/rest/study/study_id/{study_id}/data/json') - Network accessline 484
# 4. Perform m/z search for compound identification mz_value = 180.06 response = requests.get(f'https://www.metabolomicsworkbench.org/rest/moverz/MB/{mz_value}/M+H/0.5/json') - Network accessline 485
mz_value = 180.06 response = requests.get(f'https://www.metabolomicsworkbench.org/rest/moverz/MB/{mz_value}/M+H/0.5/json') matches = response.json() - Network accessline 486
response = requests.get(f'https://www.metabolomicsworkbench.org/rest/moverz/MB/{mz_value}/M+H/0.5/json') - Network accessline 489
# 5. Get compound structure regno = matches[0]['regno'] response = requests.get(f'https://www.metabolomicsworkbench.org/rest/compound/regno/{regno}/png') - Network accessline 490
regno = matches[0]['regno'] response = requests.get(f'https://www.metabolomicsworkbench.org/rest/compound/regno/{regno}/png') with open('structure.png', 'wb') as f: - Network accessline 491
response = requests.get(f'https://www.metabolomicsworkbench.org/rest/compound/regno/{regno}/png')
bundled/skills/metric-calculator/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Bash, Grep
bundled/skills/netlify-deploy/LICENSE.txt
bundled/skills/netlify-deploy/SKILL.md
- Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 65
[Credential-related source omitted] - Network accessline 68
Tokens can be generated at: https://app.netlify.com/user/applications#personal-access-tokens - Network accessline 86
# If Git-based, extract remote URL # Format: https://github.com/username/repo or git@github.com:username/repo.git - Network accessline 87
# Format: https://github.com/username/repo or git@github.com:username/repo.git - Network accessline 175
# Try Git-based linking first git remote show origin npx netlify link --git-remote-url https://github.com/user/repo - Network accessline 177
npx netlify link --git-remote-url https://github.com/user/repo - Network accessline 240
- Netlify CLI Docs: https://docs.netlify.com/cli/get-started/ - Network accessline 241
- netlify.toml Reference: https://docs.netlify.com/configure-builds/file-based-configuration/
bundled/skills/netlify-deploy/assets/netlify-small.svg
- Network accessline 1
<svg width="16" height="16" viewBox="0 0 128 128" fill="none" xmlns="http://www.w3.org/2000/svg" aria-hidden="true">
bundled/skills/netlify-deploy/references/cli-commands.md
bundled/skills/netlify-deploy/references/deployment-patterns.md
- Network accessline 54
1. Check authentication: `npx netlify status` 2. Get Git remote: `git remote show origin` 3. Extract URL (e.g., `https://github.com/user/repo.git`) - Network accessline 55
2. Get Git remote: `git remote show origin` 3. Extract URL (e.g., `https://github.com/user/repo.git`) 4. Link by remote: `npx netlify link --git-remote-url <URL>` - Network accessline 56
3. Extract URL (e.g., `https://github.com/user/repo.git`) - Network accessline 62
git remote show origin # * remote origin # Fetch URL: https://github.com/user/my-app.git - Network accessline 64
# Fetch URL: https://github.com/user/my-app.git - Network accessline 66
npx netlify link --git-remote-url https://github.com/user/my-app.git - Network accessline 85
npx netlify deploy # Draft deploy URL: https://507f1f77bcf86cd799439011-my-app.netlify.app - Network accessline 86
# Draft deploy URL: https://507f1f77bcf86cd799439011-my-app.netlify.app - Access to secretsline 149
[Credential-related source omitted] - Access to secretsline 152
[Credential-related source omitted] - Network accessline 301
- Netlify CLI Documentation: https://docs.netlify.com/cli/get-started/ - Network accessline 302
- Framework Integration Guides: https://docs.netlify.com/frameworks/ - Network accessline 303
- Build Configuration: https://docs.netlify.com/configure-builds/
bundled/skills/netlify-deploy/references/netlify-toml.md
- Network accessline 98
[[redirects]] from = "/api/*" to = "https://api.example.com/:splat" - Network accessline 99
from = "/api/*" to = "https://api.example.com/:splat" status = 200 - Network accessline 100
to = "https://api.example.com/:splat" - Network accessline 174
[plugins.inputs] baseUrl = "https://example.com" - Network accessline 175
baseUrl = "https://example.com" - Network accessline 258
- Full configuration reference: https://docs.netlify.com/configure-builds/file-based-configuration/ - Network accessline 259
- Framework-specific guides: https://docs.netlify.com/frameworks/
bundled/skills/networkx/SKILL.md
- Network accessline 428
- **Official Documentation**: https://networkx.org/documentation/latest/ - Network accessline 429
- **Tutorial**: https://networkx.org/documentation/latest/tutorial.html - Network accessline 430
- **Gallery**: https://networkx.org/documentation/latest/auto_examples/index.html - Network accessline 431
- **GitHub**: https://github.com/networkx/networkx
bundled/skills/neurokit2/SKILL.md
- Network accessline 276
uv pip install https://github.com/neuropsychology/NeuroKit/zipball/dev - Network accessline 348
- Official Documentation: https://neuropsychology.github.io/NeuroKit/ - Network accessline 349
- GitHub Repository: https://github.com/neuropsychology/NeuroKit - Network accessline 350
- Publication: Makowski et al. (2021). NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior Research Methods. https://doi.org/10.3758/s13428-020-01516-y
bundled/skills/neuropixels-analysis/SKILL.md
- Network accessline 345
- **SpikeInterface Docs**: https://spikeinterface.readthedocs.io/ - Network accessline 346
- **Neuropixels Tutorial**: https://spikeinterface.readthedocs.io/en/stable/how_to/analyze_neuropixels.html - Network accessline 347
- **Kilosort4 GitHub**: https://github.com/MouseLand/Kilosort - Network accessline 348
- **IBL Neuropixel Tools**: https://github.com/int-brain-lab/ibl-neuropixel - Network accessline 349
- **Allen Institute ecephys**: https://github.com/AllenInstitute/ecephys_spike_sorting - Network accessline 350
- **Bombcell (Automated QC)**: https://github.com/Julie-Fabre/bombcell - Network accessline 351
- **SpikeAgent (AI Curation)**: https://github.com/SpikeAgent/SpikeAgent
bundled/skills/neuropixels-analysis/assets/analysis_template.py
- Executable scriptline 1
#!/usr/bin/env python
bundled/skills/neuropixels-analysis/references/AI_CURATION.md
- Access to secretsline 299
[Credential-related source omitted] - Access to secretsline 308
[Credential-related source omitted] - Network accessline 343
- [SpikeAgent](https://github.com/SpikeAgent/SpikeAgent) - AI-powered spike sorting assistant - Network accessline 344
- [Anthropic Vision API](https://docs.anthropic.com/en/docs/vision) - Network accessline 345
- [GPT-4 Vision](https://platform.openai.com/docs/guides/vision)
bundled/skills/neuropixels-analysis/references/AUTOMATED_CURATION.md
- Network accessline 39
# Or development version git clone https://github.com/Julie-Fabre/bombcell.git - Network accessline 40
git clone https://github.com/Julie-Fabre/bombcell.git - Network accessline 192
pip install unitmatch # Or from source git clone https://github.com/EnnyvanBeest/UnitMatch.git - Network accessline 194
git clone https://github.com/EnnyvanBeest/UnitMatch.git - Network accessline 354
- [Bombcell GitHub](https://github.com/Julie-Fabre/bombcell) - Network accessline 355
- [UnitMatch GitHub](https://github.com/EnnyvanBeest/UnitMatch) - Network accessline 356
- [SpikeInterface Curation](https://spikeinterface.readthedocs.io/en/stable/modules/curation.html)
bundled/skills/neuropixels-analysis/references/MOTION_CORRECTION.md
- Network accessline 320
- [SpikeInterface Motion Correction Docs](https://spikeinterface.readthedocs.io/en/stable/modules/motion_correction.html) - Network accessline 321
- [Handle Drift Tutorial](https://spikeinterface.readthedocs.io/en/stable/how_to/handle_drift.html) - Network accessline 322
- [DREDge GitHub](https://github.com/evarol/DREDge)
bundled/skills/neuropixels-analysis/references/QUALITY_METRICS.md
bundled/skills/neuropixels-analysis/scripts/compute_metrics.py
- Executable scriptline 1
#!/usr/bin/env python
bundled/skills/neuropixels-analysis/scripts/explore_recording.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/neuropixels-analysis/scripts/export_to_phy.py
- Executable scriptline 1
#!/usr/bin/env python
bundled/skills/neuropixels-analysis/scripts/neuropixels_pipeline.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 10
References: - https://spikeinterface.readthedocs.io/en/stable/how_to/analyze_neuropixels.html - Network accessline 11
- https://spikeinterface.readthedocs.io/en/stable/how_to/analyze_neuropixels.html - Network accessline 12
- https://github.com/AllenInstitute/ecephys_spike_sorting
bundled/skills/neuropixels-analysis/scripts/preprocess_recording.py
- Executable scriptline 1
#!/usr/bin/env python
bundled/skills/neuropixels-analysis/scripts/run_sorting.py
- Executable scriptline 1
#!/usr/bin/env python
bundled/skills/nowait-reasoning-optimizer/scripts/nowait_processor.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/omero-integration/SKILL.md
- Network accessline 240
- **Official Documentation**: https://omero.readthedocs.io/en/stable/developers/Python.html - Network accessline 241
- **BlitzGateway API**: https://omero.readthedocs.io/en/stable/developers/Python.html#omero-blitzgateway - Network accessline 242
- **OMERO Model**: https://omero.readthedocs.io/en/stable/developers/Model.html - Network accessline 243
- **Community Forum**: https://forum.image.sc/tag/omero
bundled/skills/omero-integration/references/connection.md
bundled/skills/openai-docs/LICENSE.txt
bundled/skills/openai-docs/SKILL.md
bundled/skills/openai-docs/agents/openai.yaml
bundled/skills/openai-docs/assets/openai-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
bundled/skills/openalex-database/SKILL.md
- Network accessline 178
dois = [ "https://doi.org/10.1038/s41586-021-03819-2", - Network accessline 179
"https://doi.org/10.1038/s41586-021-03819-2", - Network accessline 180
"https://doi.org/10.1126/science.abc1234", - Network accessline 216
# Get the work work = client.get_entity('works', 'https://doi.org/10.1038/s41586-021-03819-2') - Network accessline 217
work = client.get_entity('works', 'https://doi.org/10.1038/s41586-021-03819-2') - Network accessline 219
# Get citing papers using cited_by_api_url import requests citing_response = requests.get( - Network accessline 220
import requests citing_response = requests.get( work['cited_by_api_url'], - Network accessline 221
citing_response = requests.get( - Network accessline 403
# DOI for works work = client.get_entity('works', 'https://doi.org/10.7717/peerj.4375') - Network accessline 404
work = client.get_entity('works', 'https://doi.org/10.7717/peerj.4375') - Network accessline 406
# ORCID for authors author = client.get_entity('authors', 'https://orcid.org/0000-0003-1613-5981') - Network accessline 407
author = client.get_entity('authors', 'https://orcid.org/0000-0003-1613-5981') - Network accessline 409
# ROR for institutions institution = client.get_entity('institutions', 'https://ror.org/02y3ad647') - Network accessline 410
institution = client.get_entity('institutions', 'https://ror.org/02y3ad647')
bundled/skills/openalex-database/references/api_guide.md
- Network accessline 5
**Base URL:** `https://api.openalex.org` - Network accessline 15
https://api.openalex.org/works?sample=20&seed=123 - Network accessline 51
for attempt in range(max_retries): try: response = requests.get(url) - Network accessline 52
try: response = requests.get(url) if response.status_code == 200: - Network accessline 53
response = requests.get(url) - Network accessline 127
# Small sample https://api.openalex.org/works?sample=20&seed=42 - Network accessline 128
https://api.openalex.org/works?sample=20&seed=42 - Network accessline 130
# Large sample (10k+) - make multiple requests https://api.openalex.org/works?sample=1000&seed=1 - Network accessline 131
https://api.openalex.org/works?sample=1000&seed=1 - Network accessline 132
https://api.openalex.org/works?sample=1000&seed=2 - Network accessline 138
# Simple search https://api.openalex.org/works?search=machine+learning - Network accessline 139
https://api.openalex.org/works?search=machine+learning - Network accessline 141
# Search specific field https://api.openalex.org/works?filter=title.search:CRISPR - Network accessline 142
https://api.openalex.org/works?filter=title.search:CRISPR - Network accessline 144
# Search + filter https://api.openalex.org/works?search=climate&filter=publication_year:2023 - Network accessline 145
https://api.openalex.org/works?search=climate&filter=publication_year:2023 - Network accessline 150
# Step 1: Get author ID https://api.openalex.org/authors?search=Heather+Piwowar - Network accessline 151
https://api.openalex.org/authors?search=Heather+Piwowar - Network accessline 152
# Returns: "id": "https://openalex.org/A5023888391" - Network accessline 154
# Step 2: Get their works https://api.openalex.org/works?filter=authorships.author.id:A5023888391 - Network accessline 155
https://api.openalex.org/works?filter=authorships.author.id:A5023888391 - Network accessline 160
# Step 1: Get institution ID https://api.openalex.org/institutions?search=MIT - Network accessline 161
https://api.openalex.org/institutions?search=MIT - Network accessline 162
# Returns: "id": "https://openalex.org/I136199984" - Network accessline 164
# Step 2: Get their works https://api.openalex.org/works?filter=authorships.institutions.id:I136199984 - Network accessline 165
https://api.openalex.org/works?filter=authorships.institutions.id:I136199984 - Network accessline 170
https://api.openalex.org/works?filter=publication_year:>2020&sort=cited_by_count:desc&per-page=200 - Network accessline 175
# All OA https://api.openalex.org/works?filter=is_oa:true - Network accessline 176
https://api.openalex.org/works?filter=is_oa:true - Network accessline 178
# Gold OA only https://api.openalex.org/works?filter=open_access.oa_status:gold - Network accessline 179
https://api.openalex.org/works?filter=open_access.oa_status:gold - Network accessline 184
# Recent OA works about COVID from top institutions https://api.openalex.org/works?filter=publication_year:2022,is_oa:true,title.search:covid,authorships.institutions.id:I136199984|I27837315 - Network accessline 185
https://api.openalex.org/works?filter=publication_year:2022,is_oa:true,title.search:covid,authorships.institutions.id:I136199984|I27837315 - Network accessline 190
# Get specific works by DOI (up to 50 per request) https://api.openalex.org/works?filter=doi:https://doi.org/10.1371/journal.pone.0266781|https://doi.org/10.1371/journal.pone.0267149&per-page=50 - Network accessline 191
https://api.openalex.org/works?filter=doi:https://doi.org/10.1371/journal.pone.0266781|https://doi.org/10.1371/journal.pone.0267149&per-page=50 - Network accessline 196
# Top topics https://api.openalex.org/works?group_by=topics.id - Network accessline 197
https://api.openalex.org/works?group_by=topics.id - Network accessline 199
# Papers per year https://api.openalex.org/works?group_by=publication_year - Network accessline 200
https://api.openalex.org/works?group_by=publication_year - Network accessline 202
# Most prolific institutions https://api.openalex.org/works?group_by=authorships.institutions.id - Network accessline 203
https://api.openalex.org/works?group_by=authorships.institutions.id - Network accessline 208
# First page https://api.openalex.org/works?filter=publication_year:2023&per-page=200 - Network accessline 209
https://api.openalex.org/works?filter=publication_year:2023&per-page=200 - Network accessline 211
# Next pages https://api.openalex.org/works?filter=publication_year:2023&per-page=200&page=2 - Network accessline 212
https://api.openalex.org/works?filter=publication_year:2023&per-page=200&page=2 - Network accessline 234
https://api.openalex.org/works/W2741809807 - Network accessline 242
"group_by": [ { "key": "https://openalex.org/T10001", - Network accessline 243
{ "key": "https://openalex.org/T10001", "key_display_name": "Artificial Intelligence", - Network accessline 244
"key": "https://openalex.org/T10001", - Network accessline 280
DOI: /works/https://doi.org/10.7717/peerj.4375 - Network accessline 286
ORCID: /authors/https://orcid.org/0000-0003-1613-5981 - Network accessline 291
ROR: /institutions/https://ror.org/02y3ad647 - Network accessline 319
for attempt in range(max_retries): try: response = requests.get(url, timeout=30) - Network accessline 320
try: response = requests.get(url, timeout=30) if response.status_code == 200: - Network accessline 321
response = requests.get(url, timeout=30) - Network accessline 367
- Full documentation: https://docs.openalex.org - Network accessline 368
- API Overview: https://docs.openalex.org/how-to-use-the-api/api-overview - Network accessline 369
- Entity schemas: https://docs.openalex.org/api-entities - Network accessline 370
- Help: https://openalex.org/help - Network accessline 371
- User group: https://groups.google.com/g/openalex-users
bundled/skills/openalex-database/references/common_queries.md
- Network accessline 149
dois = [ "https://doi.org/10.1371/journal.pone.0266781", - Network accessline 150
"https://doi.org/10.1371/journal.pone.0266781", - Network accessline 151
"https://doi.org/10.1371/journal.pone.0267149", - Network accessline 152
"https://doi.org/10.1038/s41586-021-03819-2", - Network accessline 286
# Get the work doi = "https://doi.org/10.1038/s41586-021-03819-2" - Network accessline 287
doi = "https://doi.org/10.1038/s41586-021-03819-2" - Network accessline 293
# Extract just the query part and use it import requests response = requests.get(cited_by_url, params={'mailto': client.email}) - Network accessline 294
import requests response = requests.get(cited_by_url, params={'mailto': client.email}) citing_works = response.json() - Network accessline 295
response = requests.get(cited_by_url, params={'mailto': client.email})
bundled/skills/openalex-database/scripts/openalex_client.py
bundled/skills/openalex-database/scripts/query_helpers.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/paper-2-web/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 106
git clone https://github.com/YuhangChen1/Paper2All.git - Access to secretsline 115
[Credential-related source omitted] - Access to secretsline 116
[Credential-related source omitted] - Network accessline 438
**External Resources**: - GitHub Repository: https://github.com/YuhangChen1/Paper2All - Network accessline 439
- GitHub Repository: https://github.com/YuhangChen1/Paper2All
bundled/skills/paper-2-web/references/installation.md
- Network accessline 20
git clone https://github.com/YuhangChen1/Paper2All.git - Dangerous shell operationline 39
sudo apt-get install libreoffice poppler-utils - Network accessline 47
**Windows:** - Download and install LibreOffice from https://www.libreoffice.org/ - Network accessline 48
- Download and install LibreOffice from https://www.libreoffice.org/ - Network accessline 49
- Download and install Poppler from https://github.com/oschwartz10612/poppler-windows - Access to secretsline 59
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted] - Access to secretsline 71
[Credential-related source omitted] - Access to secretsline 131
[Credential-related source omitted]
bundled/skills/pathml/references/data_management.md
- Network accessline 738
- **HDF5 Documentation:** https://www.hdfgroup.org/solutions/hdf5/ - Network accessline 739
- **h5py:** https://docs.h5py.org/ - Network accessline 740
- **DVC (Data Version Control):** https://dvc.org/ - Network accessline 741
- **Dask:** https://docs.dask.org/ - Network accessline 742
- **PathML Data Management API:** https://pathml.readthedocs.io/en/latest/api_data_reference.html
bundled/skills/pathml/references/graphs.md
bundled/skills/pathml/references/image_loading.md
- Network accessline 445
- **PathML Documentation:** https://pathml.readthedocs.io/ - Network accessline 446
- **OpenSlide:** https://openslide.org/ (underlying library for WSI formats) - Network accessline 447
- **Bio-Formats:** https://www.openmicroscopy.org/bio-formats/ (alternative backend) - Network accessline 448
- **DICOM Standard:** https://www.dicomstandard.org/
bundled/skills/pathml/references/machine_learning.md
- Network accessline 721
- **PathML ML API:** https://pathml.readthedocs.io/en/latest/api_ml_reference.html - Network accessline 722
- **HoVer-Net Paper:** Graham et al., "HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images," Medical Image Analysis, 2019 - **PanNuke Dataset:** https://warwick.ac.uk/fac/cross_fac/tia/data/pan - Network accessline 723
- **PanNuke Dataset:** https://warwick.ac.uk/fac/cross_fac/tia/data/pannuke - Network accessline 724
- **PyTorch Lightning:** https://www.pytorchlightning.ai/ - Network accessline 725
- **ONNX Runtime:** https://onnxruntime.ai/
bundled/skills/pathml/references/multiparametric.md
- Network accessline 173
cytoplasm_channel='CD45', model='mesmer', api_url='https://deepcell.org/api/predict', - Network accessline 174
model='mesmer', api_url='https://deepcell.org/api/predict', timeout=300 # Timeout in seconds - Network accessline 175
api_url='https://deepcell.org/api/predict', - Network accessline 681
- **PathML Multiparametric API:** https://pathml.readthedocs.io/en/latest/api_multiparametric_reference.html - Network accessline 682
- **CODEX:** https://www.akoyabio.com/codex/ - Network accessline 683
- **Vectra:** https://www.akoyabio.com/vectra/ - Network accessline 684
- **DeepCell Mesmer:** https://www.deepcell.org/ - Network accessline 685
- **Scanpy:** https://scanpy.readthedocs.io/ (single-cell analysis) - Network accessline 686
- **Squidpy:** https://squidpy.readthedocs.io/ (spatial omics analysis)
bundled/skills/pathml/references/preprocessing.md
- Network accessline 353
cytoplasm_channel='CD45', model='mesmer', api_url='https://deepcell.org/api' - Network accessline 354
model='mesmer', api_url='https://deepcell.org/api' ) - Network accessline 355
api_url='https://deepcell.org/api' - Network accessline 718
- **PathML Preprocessing API:** https://pathml.readthedocs.io/en/latest/api_preprocessing_reference.html - Network accessline 720
- Macenko et al. 2009: "A method for normalizing histology slides for quantitative analysis" - Vahadane et al. 2016: "Structure-Preserving Color Normalization and Sparse Stain Separation" - **DeepCell Mesmer:** https://www.deepcell.org/ ( - Network accessline 722
- **DeepCell Mesmer:** https://www.deepcell.org/ (cell segmentation model)
bundled/skills/pdf/LICENSE.txt
bundled/skills/pdf/SKILL.md
- Dangerous shell operationline 44
sudo apt-get install -y poppler-utils
bundled/skills/pdf/scripts/check_bounding_boxes.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/check_bounding_boxes_test.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/check_fillable_fields.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/convert_pdf_to_images.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/create_validation_image.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/extract_form_field_info.py
- Executable scriptline 1
Executable file - Network accessline 31
# "/Off" seems to always be the unchecked value, as suggested by # https://opensource.adobe.com/dc-acrobat-sdk-docs/standards/pdfstandards/pdf/PDF32000_2008.pdf#page=448 - Network accessline 32
# https://opensource.adobe.com/dc-acrobat-sdk-docs/standards/pdfstandards/pdf/PDF32000_2008.pdf#page=448 - Network accessline 79
# Radio button options have a separate annotation for each choice; # all choices have the same field name. # See https://westhealth.github.io/exploring-fillable-forms-with-pdfrw.html - Network accessline 81
# See https://westhealth.github.io/exploring-fillable-forms-with-pdfrw.html
bundled/skills/pdf/scripts/fill_fillable_fields.py
- Executable scriptline 1
Executable file
bundled/skills/pdf/scripts/fill_pdf_form_with_annotations.py
bundled/skills/peer-review/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/peer-review/references/reporting_standards.md
- Network accessline 20
**Reference:** http://www.consort-statement.org/ - Network accessline 36
**Reference:** https://www.strobe-statement.org/ - Network accessline 53
**Reference:** http://www.prisma-statement.org/ - Network accessline 64
**Reference:** https://www.spirit-statement.org/ - Network accessline 78
**Reference:** https://www.care-statement.org/ - Network accessline 100
**Reference:** https://arriveguidelines.org/ - Network accessline 116
**Reference:** http://fged.org/projects/miame/ - Network accessline 140
**Reference:** https://gensc.org/ - Network accessline 156
**Reference:** https://www.wwpdb.org/ - Network accessline 172
**Reference:** http://www.psidev.info/ - Network accessline 187
**Reference:** https://www.humanbrainmapping.org/cobidas - Network accessline 203
**Reference:** http://flowcyt.org/ - Network accessline 217
**Reference:** https://www.miappe.org/
bundled/skills/perplexity-search/SKILL.md
- Network accessline 39
1. **Get OpenRouter API key**: - Visit https://openrouter.ai/keys - Network accessline 40
- Visit https://openrouter.ai/keys - Access to secretsline 47
[Credential-related source omitted] - Network accessline 256
3. Reserve `sonar-pro-search` for complex analysis 4. Set `--max-tokens` to limit response length 5. Monitor usage at https://openrouter.ai/activity - Network accessline 257
4. Set `--max-tokens` to limit response length 5. Monitor usage at https://openrouter.ai/activity 6. Set spending limits in OpenRouter dashboard - Network accessline 258
5. Monitor usage at https://openrouter.ai/activity - Access to secretsline 269
[Credential-related source omitted] - Network accessline 287
**Solutions**: - Wait a few seconds before retrying - Increase rate limit at https://openrouter.ai/keys - Network accessline 288
- Wait a few seconds before retrying - Increase rate limit at https://openrouter.ai/keys - Add delays between requests in batch processing - Network accessline 289
- Increase rate limit at https://openrouter.ai/keys - Network accessline 296
**Solution**: - Add credits at https://openrouter.ai/account - Network accessline 297
- Add credits at https://openrouter.ai/account - Network accessline 389
**OpenRouter:** - Dashboard: https://openrouter.ai/account - Network accessline 390
- Dashboard: https://openrouter.ai/account - Network accessline 391
- API Keys: https://openrouter.ai/keys - Network accessline 392
- Perplexity Models: https://openrouter.ai/perplexity - Network accessline 393
- Usage Monitoring: https://openrouter.ai/activity - Network accessline 394
- Documentation: https://openrouter.ai/docs - Network accessline 396
**LiteLLM:** - Documentation: https://docs.litellm.ai/ - Network accessline 397
- Documentation: https://docs.litellm.ai/ - Network accessline 398
- OpenRouter Provider: https://docs.litellm.ai/docs/providers/openrouter - Network accessline 399
- GitHub: https://github.com/BerriAI/litellm - Network accessline 401
**Perplexity:** - Official Docs: https://docs.perplexity.ai/ - Network accessline 402
- Official Docs: https://docs.perplexity.ai/ - Access to secretsline 416
[Credential-related source omitted] - Access to secretsline 426
[Credential-related source omitted]
bundled/skills/perplexity-search/references/model_comparison.md
- Access to secretsline 307
[Credential-related source omitted]
bundled/skills/perplexity-search/references/openrouter_setup.md
- Network accessline 21
1. Visit https://openrouter.ai/ - Network accessline 30
1. Navigate to https://openrouter.ai/account - Network accessline 36
**Pricing notes:** - Models have different per-token costs - See https://openrouter.ai/perplexity for Perplexity pricing - Network accessline 37
- Models have different per-token costs - See https://openrouter.ai/perplexity for Perplexity pricing - Monitor usage at https://openrouter.ai/activity - Network accessline 38
- See https://openrouter.ai/perplexity for Perplexity pricing - Network accessline 39
- Monitor usage at https://openrouter.ai/activity - Network accessline 43
1. Go to https://openrouter.ai/keys - Access to secretsline 65
[Credential-related source omitted] - Access to secretsline 71
[Credential-related source omitted] - Access to secretsline 75
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Access to secretsline 86
[Credential-related source omitted] - Access to secretsline 89
[Credential-related source omitted] - Access to secretsline 94
[Credential-related source omitted] - Access to secretsline 95
[Credential-related source omitted] - Access to secretsline 96
[Credential-related source omitted] - Access to secretsline 107
[Credential-related source omitted] - Access to secretsline 108
[Credential-related source omitted] - Access to secretsline 117
[Credential-related source omitted] - Access to secretsline 120
[Credential-related source omitted] - Access to secretsline 138
[Credential-related source omitted] - Access to secretsline 159
[Credential-related source omitted] - Network accessline 189
1. Visit https://openrouter.ai/activity 2. View requests, tokens, and costs - Network accessline 198
1. Go to https://openrouter.ai/keys 2. Click on your key 3. Set "Rate limit" (requests per minute) - Access to secretsline 227
[Credential-related source omitted] - Access to secretsline 230
[Credential-related source omitted] - Network accessline 244
**Solutions**: 1. Verify key at https://openrouter.ai/keys - Network accessline 245
1. Verify key at https://openrouter.ai/keys - Network accessline 254
**Solution**: 1. Go to https://openrouter.ai/account - Network accessline 255
1. Go to https://openrouter.ai/account - Network accessline 264
**Solutions**: 1. Wait a few seconds before retrying 2. Increase rate limit at https://openrouter.ai/keys - Network accessline 265
1. Wait a few seconds before retrying 2. Increase rate limit at https://openrouter.ai/keys 3. Implement exponential backoff in code - Network accessline 266
2. Increase rate limit at https://openrouter.ai/keys 3. Implement exponential backoff in code 4. Batch requests or reduce frequency - Network accessline 274
**Solution**: 1. Check available models at https://openrouter.ai/models - Network accessline 275
1. Check available models at https://openrouter.ai/models - Access to secretsline 306
[Credential-related source omitted] - Access to secretsline 309
[Credential-related source omitted] - Access to secretsline 312
[Credential-related source omitted] - Network accessline 322
model="openrouter/perplexity/sonar-pro", messages=[{"role": "user", "content": "query"}], api_base="https://custom-endpoint.com/v1" # Custom URL - Network accessline 323
messages=[{"role": "user", "content": "query"}], api_base="https://custom-endpoint.com/v1" # Custom URL ) - Network accessline 324
api_base="https://custom-endpoint.com/v1" # Custom URL - Network accessline 337
messages=[{"role": "user", "content": "query"}], extra_headers={ "HTTP-Referer": "https://your-app.com", - Network accessline 338
extra_headers={ "HTTP-Referer": "https://your-app.com", "X-Title": "Your App Name" - Network accessline 339
"HTTP-Referer": "https://your-app.com", - Access to secretsline 374
[Credential-related source omitted] - Access to secretsline 379
[Credential-related source omitted] - Network accessline 391
1. Go to https://openrouter.ai/keys immediately - Network accessline 402
A: Pricing varies by model. Sonar is cheapest (~$0.001-0.002 per query), Sonar Pro is moderate (~$0.002-0.005), and Sonar Pro Search is most expensive (~$0.02-0.05+ per query). See https://openrouter.ai/perplexity for exact pricing. - Network accessline 426
**Official Documentation:** - OpenRouter: https://openrouter.ai/docs - Network accessline 427
- OpenRouter: https://openrouter.ai/docs - Network accessline 428
- Perplexity Models: https://openrouter.ai/perplexity - Network accessline 429
- LiteLLM: https://docs.litellm.ai/ - Network accessline 431
**Account Management:** - Dashboard: https://openrouter.ai/account - Network accessline 432
- Dashboard: https://openrouter.ai/account - Network accessline 433
- API Keys: https://openrouter.ai/keys - Network accessline 434
- Usage: https://openrouter.ai/activity - Network accessline 435
- Billing: https://openrouter.ai/credits - Network accessline 437
**Community:** - OpenRouter Discord: https://discord.gg/openrouter - Network accessline 438
- OpenRouter Discord: https://discord.gg/openrouter - Network accessline 439
- GitHub Issues: https://github.com/OpenRouter - Network accessline 440
- LiteLLM GitHub: https://github.com/BerriAI/litellm - Network accessline 446
1. Create account at https://openrouter.ai - Network accessline 447
2. Add payment method and credits 3. Generate API key at https://openrouter.ai/keys 4. Set `OPENROUTER_API_KEY` environment variable - Network accessline 448
3. Generate API key at https://openrouter.ai/keys - Access to secretsline 449
[Credential-related source omitted]
bundled/skills/perplexity-search/scripts/perplexity_search.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 12
[Credential-related source omitted] - Access to secretsline 37
[Credential-related source omitted] - Access to secretsline 39
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Network accessline 41
[Credential-related source omitted] - Access to secretsline 41
[Credential-related source omitted] - Network accessline 42
print("\nTo set up your API key:", file=sys.stderr) print("1. Get an API key from https://openrouter.ai/keys", file=sys.stderr) print("2. Set the environment variable:", file=sys.stderr) - Network accessline 43
print("1. Get an API key from https://openrouter.ai/keys", file=sys.stderr) - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 46
[Credential-related source omitted] - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Access to secretsline 82
[Credential-related source omitted] - Access to secretsline 221
[Credential-related source omitted]
bundled/skills/perplexity-search/scripts/setup_env.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 20
[Credential-related source omitted] - Access to secretsline 22
[Credential-related source omitted] - Access to secretsline 25
[Credential-related source omitted] - Access to secretsline 26
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 57
[Credential-related source omitted] - Access to secretsline 72
[Credential-related source omitted] - Access to secretsline 73
[Credential-related source omitted] - Access to secretsline 74
[Credential-related source omitted] - Network accessline 75
print() print("To set up your API key:") print("1. Get an API key from https://openrouter.ai/keys") - Network accessline 76
print("To set up your API key:") print("1. Get an API key from https://openrouter.ai/keys") print("2. Run this script with --api-key flag:") - Network accessline 77
print("1. Get an API key from https://openrouter.ai/keys") - Access to secretsline 84
[Credential-related source omitted] - Access to secretsline 85
[Credential-related source omitted] - Access to secretsline 117
[Credential-related source omitted] - Access to secretsline 118
[Credential-related source omitted] - Network accessline 120
Get your OpenRouter API key from: https://openrouter.ai/keys - Network accessline 121
https://openrouter.ai/keys - Access to secretsline 132
[Credential-related source omitted] - Access to secretsline 133
[Credential-related source omitted] - Access to secretsline 145
[Credential-related source omitted] - Access to secretsline 149
[Credential-related source omitted] - Access to secretsline 151
[Credential-related source omitted] - Access to secretsline 157
[Credential-related source omitted]
bundled/skills/planning-with-files/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/planning-with-files/reference.md
bundled/skills/planning-with-files/scripts/check-complete.sh
- Executable scriptline 1
#!/bin/bash
bundled/skills/planning-with-files/scripts/init-session.sh
- Executable scriptline 1
#!/bin/bash
bundled/skills/planning-with-files/templates/findings.md
- Network accessline 67
WHEN: Add as you discover useful resources. EXAMPLE: - Python argparse docs: https://docs.python.org/3/library/argparse.html - Network accessline 68
EXAMPLE: - Python argparse docs: https://docs.python.org/3/library/argparse.html - Project structure: src/main.py, src/utils.py - Network accessline 69
- Python argparse docs: https://docs.python.org/3/library/argparse.html
bundled/skills/playwright/LICENSE.txt
bundled/skills/playwright/SKILL.md
- Network accessline 48
"$PWCLI" open https://playwright.dev --headed - Network accessline 74
"$PWCLI" open https://example.com - Network accessline 96
"$PWCLI" open https://example.com/form - Network accessline 107
"$PWCLI" open https://example.com --headed - Network accessline 116
"$PWCLI" tab-new https://example.com
bundled/skills/playwright/assets/playwright-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/playwright/references/cli.md
- Network accessline 22
pwcli open https://example.com - Dangerous shell operationline 36
pwcli eval "document.title" - Dangerous shell operationline 37
pwcli eval "el => el.textContent" e5 - Network accessline 83
pwcli tab-list pwcli tab-new pwcli tab-new https://example.com/page - Network accessline 84
pwcli tab-new pwcli tab-new https://example.com/page pwcli tab-close - Network accessline 85
pwcli tab-new https://example.com/page - Network accessline 107
pwcli --session todo open https://demo.playwright.dev/todomvc - Network accessline 114
export PLAYWRIGHT_CLI_SESSION=todo pwcli open https://demo.playwright.dev/todomvc - Network accessline 115
pwcli open https://demo.playwright.dev/todomvc
bundled/skills/playwright/references/workflows.md
- Network accessline 10
pwcli open https://example.com - Network accessline 19
pwcli open https://example.com/form --headed - Network accessline 31
pwcli open https://example.com - Dangerous shell operationline 33
pwcli eval "document.title" - Dangerous shell operationline 34
pwcli eval "el => el.textContent" e12 - Network accessline 60
pwcli --session marketing open https://example.com - Network accessline 62
pwcli --session checkout open https://example.com/checkout - Network accessline 68
export PLAYWRIGHT_CLI_SESSION=checkout pwcli open https://example.com/checkout - Network accessline 69
pwcli open https://example.com/checkout
bundled/skills/playwright/scripts/playwright_cli.sh
- Executable scriptline 1
#!/usr/bin/env bash
bundled/skills/plotly/SKILL.md
bundled/skills/polars/SKILL.md
- Network accessline 2
name: polars description: Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pi - Network accessline 3
description: Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, fast - Network accessline 4
license: https://github.com/pola-rs/polars/blob/main/LICENSE
bundled/skills/polars/references/io_guide.md
- Access to secretsline 270
[Credential-related source omitted] - Access to secretsline 271
[Credential-related source omitted] - Access to secretsline 272
[Credential-related source omitted] - Access to secretsline 287
[Credential-related source omitted] - Access to secretsline 288
[Credential-related source omitted] - Access to secretsline 301
[Credential-related source omitted]
bundled/skills/pptx-posters/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/pptx-posters/assets/poster_quality_checklist.md
- Network accessline 202
### Color Contrast Test at: https://webaim.org/resources/contrastchecker/ - Network accessline 203
Test at: https://webaim.org/resources/contrastchecker/ - Network accessline 209
### Color Blindness Test with simulator: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 210
Test with simulator: https://www.color-blindness.com/coblis-color-blindness-simulator/
bundled/skills/pptx-posters/references/poster_design_principles.md
bundled/skills/pptx-posters/references/poster_layout_design.md
- Network accessline 508
\begin{column}{0.25\linewidth} \centering \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ - Network accessline 509
\centering \qrcode[height=3cm]{https://doi.org/10.1234/paper}\\ \tiny Scan for full paper - Network accessline 510
\qrcode[height=3cm]{https://doi.org/10.1234/paper}\\
bundled/skills/preprocessing-data-with-automated-pipelines/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
bundled/skills/preprocessing-data-with-automated-pipelines/scripts/handle_errors.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/preprocessing-data-with-automated-pipelines/scripts/pipeline.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/preprocessing-data-with-automated-pipelines/scripts/transform_data.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/preprocessing-data-with-automated-pipelines/scripts/validate_data.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/property-based-testing/SKILL.md
- Broad permissionsline 1
Bash, Read, Edit, Write, Grep, Glob, TodoWrite - Network accessline 820
- fast-check: https://fast-check.dev/ - Network accessline 821
- Hypothesis: https://hypothesis.readthedocs.io/ - Network accessline 822
- Property-Based Testing: https://fsharpforfunandprofit.com/posts/property-based-testing/
bundled/skills/propositional-logic/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/providing-performance-optimization-advice/scripts/impact_estimator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/providing-performance-optimization-advice/scripts/optimization_suggestions.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/providing-performance-optimization-advice/scripts/performance_profiler.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/prowler-docs/SKILL.md
- Broad permissionsline 1
Read, Edit, Write, Glob, Grep, Bash, WebFetch, WebSearch, Task
bundled/skills/pubmed-database/SKILL.md
- Network accessline 127
# Step 1: Search for articles base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/" - Network accessline 128
base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/" - Network accessline 135
[Credential-related source omitted] - Access to secretsline 135
[Credential-related source omitted] - Network accessline 136
} response = requests.get(search_url, params=params) pmids = response.json()["esearchresult"]["idlist"] - Network accessline 137
response = requests.get(search_url, params=params) - Network accessline 147
[Credential-related source omitted] - Access to secretsline 147
[Credential-related source omitted] - Network accessline 148
} response = requests.get(fetch_url, params=params) abstracts = response.text - Network accessline 149
response = requests.get(fetch_url, params=params) - Network accessline 453
- **PubMed Help**: https://pubmed.ncbi.nlm.nih.gov/help/ - Network accessline 454
- **E-utilities Documentation**: https://www.ncbi.nlm.nih.gov/books/NBK25501/
bundled/skills/pubmed-database/references/api_reference.md
- Network accessline 8
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ - Access to secretsline 15
[Credential-related source omitted] - Access to secretsline 17
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 105
[Credential-related source omitted] - Access to secretsline 129
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Access to secretsline 175
[Credential-related source omitted] - Access to secretsline 195
[Credential-related source omitted] - Access to secretsline 210
[Credential-related source omitted] - Access to secretsline 242
[Credential-related source omitted] - Access to secretsline 247
[Credential-related source omitted] - Access to secretsline 248
[Credential-related source omitted] - Access to secretsline 257
[Credential-related source omitted] - Access to secretsline 260
[Credential-related source omitted] - Network accessline 295
- **API Documentation**: https://www.ncbi.nlm.nih.gov/books/NBK25501/
bundled/skills/pufferlib/SKILL.md
bundled/skills/pufferlib/scripts/env_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pufferlib/scripts/train_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pydeseq2/SKILL.md
bundled/skills/pydeseq2/scripts/run_deseq2_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pydicom/SKILL.md
- Network accessline 2
name: pydicom description: Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from med - Network accessline 3
description: Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (C - Network accessline 4
license: https://github.com/pydicom/pydicom/blob/main/LICENSE - Network accessline 431
Official pydicom documentation: https://pydicom.github.io/pydicom/dev/ - Network accessline 432
- User Guide: https://pydicom.github.io/pydicom/dev/guides/user/index.html - Network accessline 433
- Tutorials: https://pydicom.github.io/pydicom/dev/tutorials/index.html - Network accessline 434
- API Reference: https://pydicom.github.io/pydicom/dev/reference/index.html - Network accessline 435
- Examples: https://pydicom.github.io/pydicom/dev/auto_examples/index.html
bundled/skills/pydicom/references/common_tags.md
bundled/skills/pydicom/references/transfer_syntaxes.md
- Network accessline 350
- DICOM Standard Part 5 (Data Structures and Encoding): https://dicom.nema.org/medical/dicom/current/output/chtml/part05/PS3.5.html - Network accessline 351
- Pydicom Transfer Syntax Documentation: https://pydicom.github.io/pydicom/stable/guides/user/transfer_syntaxes.html - Network accessline 352
- Pydicom Compression Guide: https://pydicom.github.io/pydicom/stable/old/image_data_compression.html
bundled/skills/pydicom/scripts/anonymize_dicom.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pydicom/scripts/dicom_to_image.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pydicom/scripts/extract_metadata.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pyhealth/SKILL.md
bundled/skills/pymatgen/SKILL.md
- Access to secretsline 70
[Credential-related source omitted] - Network accessline 369
**Setup:** 1. Get API key from https://next-gen.materialsproject.org/ - Network accessline 370
1. Get API key from https://next-gen.materialsproject.org/ - Access to secretsline 371
[Credential-related source omitted] - Access to secretsline 655
[Credential-related source omitted] - Access to secretsline 657
[Credential-related source omitted] - Network accessline 675
- **Documentation**: https://pymatgen.org/ - Network accessline 676
- **Materials Project**: https://materialsproject.org/ - Network accessline 677
- **GitHub**: https://github.com/materialsproject/pymatgen - Network accessline 678
- **Forum**: https://matsci.org/ - Network accessline 679
- **Example notebooks**: https://matgenb.materialsvirtuallab.org/
bundled/skills/pymatgen/references/materials_project_api.md
- Network accessline 19
1. Visit https://next-gen.materialsproject.org/ - Access to secretsline 26
[Credential-related source omitted] - Network accessline 504
- **API Documentation**: https://docs.materialsproject.org/ - Network accessline 505
- **Materials Project Website**: https://next-gen.materialsproject.org/ - Network accessline 506
- **GitHub**: https://github.com/materialsproject/api - Network accessline 507
- **Forum**: https://matsci.org/
bundled/skills/pymatgen/scripts/phase_diagram_generator.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 37
[Credential-related source omitted] - Access to secretsline 39
[Credential-related source omitted] - Network accessline 40
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Network accessline 41
[Credential-related source omitted] - Access to secretsline 41
[Credential-related source omitted] - Network accessline 42
print("Get your API key from https://next-gen.materialsproject.org/") - Access to secretsline 43
[Credential-related source omitted] - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 56
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted] - Access to secretsline 175
[Credential-related source omitted]
bundled/skills/pymatgen/scripts/structure_analyzer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pymatgen/scripts/structure_converter.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/pymc/assets/hierarchical_model_template.py
- Executable scriptline 1
Executable file
bundled/skills/pymc/assets/linear_regression_template.py
- Executable scriptline 1
Executable file
bundled/skills/pymc/scripts/model_comparison.py
- Executable scriptline 1
Executable file
bundled/skills/pymc/scripts/model_diagnostics.py
- Executable scriptline 1
Executable file
bundled/skills/pymoo/SKILL.md
- Network accessline 563
**Documentation:** https://pymoo.org/
bundled/skills/pymoo/scripts/custom_problem_example.py
- Executable scriptline 1
Executable file
bundled/skills/pymoo/scripts/decision_making_example.py
- Executable scriptline 1
Executable file
bundled/skills/pymoo/scripts/many_objective_example.py
- Executable scriptline 1
Executable file
bundled/skills/pymoo/scripts/multi_objective_example.py
- Executable scriptline 1
Executable file
bundled/skills/pymoo/scripts/single_objective_example.py
- Executable scriptline 1
Executable file
bundled/skills/pyopenms/SKILL.md
bundled/skills/pyopenms/references/identification.md
- Possible obfuscationline 231
protein_seq = "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGTQDNLSGAEKAVQVKVKALPDAQFEVVHSLAKWKRQTLGQHDFSAGEGLYTHMKALRPDEDRLSPLHSVYVDQWDWERVMGDGERQFSTLKSTVEAIWAGIKATEAAVSEEFGLAPFLPDQIHFVHSQELLSRYPDLDAKGRERAIAKDLGAVFLVGIGGKLSDGHRHDVRAPDYDDWSTPS
bundled/skills/pytorch-lightning/references/data_module.md
bundled/skills/pytorch-lightning/references/distributed_training.md
- Access to secretsline 522
[Credential-related source omitted]
bundled/skills/pytorch-lightning/references/logging.md
- Network accessline 80
mlflow_logger = pl_loggers.MLFlowLogger( experiment_name="my_experiment", tracking_uri="http://localhost:5000", - Network accessline 81
experiment_name="my_experiment", tracking_uri="http://localhost:5000", run_name="run_1" - Network accessline 82
tracking_uri="http://localhost:5000", - Access to secretsline 103
[Credential-related source omitted] - Access to secretsline 125
[Credential-related source omitted]
bundled/skills/pytorch-lightning/scripts/quick_trainer_setup.py
- Executable scriptline 1
Executable file
bundled/skills/pytorch-lightning/scripts/template_datamodule.py
- Executable scriptline 1
Executable file
bundled/skills/pytorch-lightning/scripts/template_lightning_module.py
- Executable scriptline 1
Executable file
bundled/skills/pyzotero/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 12
Pyzotero is a Python wrapper for the [Zotero API v3](https://www.zotero.org/support/dev/web_api/v3/start). Use it to programmatically manage Zotero libraries: read items and collections, create and update references, upload attachments, man - Network accessline 16
**Required credentials** — get from https://www.zotero.org/settings/keys: - Network accessline 17
- **User ID**: shown as "Your userID for use in API calls" - **API Key**: create at https://www.zotero.org/settings/keys/new - **Library ID**: for group libraries, the integer after `/groups/` in the group URL - Network accessline 18
- **API Key**: create at https://www.zotero.org/settings/keys/new - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 43
[Credential-related source omitted]
bundled/skills/pyzotero/references/authentication.md
- Network accessline 5
Obtain from https://www.zotero.org/settings/keys: - Network accessline 9
| **User ID** | "Your userID for use in API calls" section | | **API Key** | Create new key at /settings/keys/new | | **Group Library ID** | Integer after `/groups/` in group URL (e.g. `https://www.zotero.org/groups/169947`) | - Network accessline 11
| **Group Library ID** | Integer after `/groups/` in group URL (e.g. `https://www.zotero.org/groups/169947`) | - Access to secretsline 18
[Credential-related source omitted] - Access to secretsline 31
[Credential-related source omitted] - Access to secretsline 32
[Credential-related source omitted] - Access to secretsline 33
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted] - Network accessline 86
When creating an API key at https://www.zotero.org/settings/keys/new, choose appropriate permissions:
bundled/skills/pyzotero/references/exports.md
- Network accessline 45
Pass any valid CSL style name from the [Zotero style repository](https://www.zotero.org/styles):
bundled/skills/ralph-loop/scripts/ralph-loop.ps1
- Executable scriptline 1
Executable file
bundled/skills/rdkit/scripts/molecular_properties.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/rdkit/scripts/similarity_search.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/rdkit/scripts/substructure_filter.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/report-generator/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 421
.content { display: none; padding: 10px; background: white; } </style> <script src="https://cdn.jsdelivr.net/npm/chart.js"></script> - Network accessline 422
</style> <script src="https://cdn.jsdelivr.net/npm/chart.js"></script> </head> - Network accessline 423
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
bundled/skills/report-generator/resources/html-templates.md
- Network accessline 31
<!-- Chart.js --> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 32
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 756
<title>GEO 综合报告 - yoursite.com</title> <link rel="stylesheet" href="styles.css"> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 757
<link rel="stylesheet" href="styles.css"> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> </head> - Network accessline 758
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script> - Network accessline 980
function exportExcel() { // 需要 SheetJS 库 // https://cdn.sheetjs.com/xlsx-latest/package/dist/xlsx.full.min.js - Network accessline 982
// https://cdn.sheetjs.com/xlsx-latest/package/dist/xlsx.full.min.js
bundled/skills/research-grants/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/research-grants/references/README.md
- Network accessline 247
### Official Resources - NSF: https://www.nsf.gov/funding/ - Network accessline 248
- NSF: https://www.nsf.gov/funding/ - Network accessline 249
- NIH: https://grants.nih.gov/ - Network accessline 250
- DOE: https://science.osti.gov/grants/ - Network accessline 251
- DARPA: https://www.darpa.mil/work-with-us/opportunities
bundled/skills/research-grants/references/broader_impacts.md
- Network accessline 372
### NSF Resources - **NSF Broader Impacts Website**: https://www.nsf.gov/od/oia/special/broaderimpacts/ - Network accessline 373
- **NSF Broader Impacts Website**: https://www.nsf.gov/od/oia/special/broaderimpacts/ - Network accessline 374
- **BI Examples Repository**: https://www.cmu.edu/uro/resources for undergraduate research/best practices/broader-impacts.html
bundled/skills/research-grants/references/darpa_guidelines.md
- Network accessline 11
**Website**: https://www.darpa.mil - Network accessline 620
- **DARPA Website**: https://www.darpa.mil - Network accessline 621
- **DARPA Opportunities**: https://www.darpa.mil/work-with-us/opportunities - Network accessline 622
- **BAA Listings**: https://beta.sam.gov (search "DARPA") - Network accessline 623
- **DARPA Social Media**: Twitter @DARPA (PMs often announce programs) - **SBIR/STTR**: https://www.darpa.mil/work-with-us/for-small-businesses - **Heilmeier Catechism**: https://www.darpa.mil/about-us/timeline/heilmeier-catechism - Network accessline 624
- **SBIR/STTR**: https://www.darpa.mil/work-with-us/for-small-businesses - Network accessline 625
- **Heilmeier Catechism**: https://www.darpa.mil/about-us/timeline/heilmeier-catechism
bundled/skills/research-grants/references/doe_guidelines.md
- Network accessline 9
**Website**: https://www.energy.gov - Network accessline 435
**Sources**: - **EERE Exchange**: https://eere-exchange.energy.gov - Network accessline 436
- **EERE Exchange**: https://eere-exchange.energy.gov - Network accessline 437
- **ARPA-E OPEN**: https://arpa-e.energy.gov - Network accessline 438
- **Office of Science FOAs**: https://science.osti.gov/grants/Funding-Opportunities - Network accessline 575
- **DOE Office of Science**: https://science.osti.gov - Network accessline 576
- **ARPA-E**: https://arpa-e.energy.gov - Network accessline 577
- **EERE**: https://www.energy.gov/eere - Network accessline 578
- **DOE National Laboratories**: https://www.energy.gov/national-laboratories - Network accessline 579
- **EERE Exchange**: https://eere-exchange.energy.gov - Network accessline 580
- **Grants.gov**: https://www.grants.gov - Network accessline 581
- **SAM.gov**: https://sam.gov
bundled/skills/research-grants/references/nih_guidelines.md
- Network accessline 9
**Website**: https://www.nih.gov - Network accessline 839
- **NIH Homepage**: https://www.nih.gov - Network accessline 840
- **NIH RePORTER (funded grants)**: https://reporter.nih.gov - Network accessline 841
- **Grants & Funding**: https://grants.nih.gov - Network accessline 842
- **eRA Commons**: https://commons.era.nih.gov - Network accessline 843
- **ASSIST**: https://public.era.nih.gov/assist - Network accessline 844
- **Application Forms and Instructions**: https://grants.nih.gov/grants/how-to-apply-application-guide.html - Network accessline 845
- **NIH Data Sharing Policy**: https://sharing.nih.gov - Network accessline 846
- **Rigor and Reproducibility**: https://grants.nih.gov/reproducibility/index.htm
bundled/skills/research-grants/references/nsf_guidelines.md
- Network accessline 9
**Website**: https://www.nsf.gov - Network accessline 559
- **NSF Homepage**: https://www.nsf.gov - Network accessline 560
- **Award Search**: https://www.nsf.gov/awardsearch/ - Network accessline 561
- **Proposal & Award Policies & Procedures Guide (PAPPG)**: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 562
- **FastLane**: https://www.fastlane.nsf.gov/ - Network accessline 563
- **Research.gov**: https://www.research.gov/ - Network accessline 564
- **Broader Impacts Resources**: https://www.nsf.gov/od/oia/special/broaderimpacts/ - Network accessline 565
- **NSF Funding Statistics**: https://www.nsf.gov/statistics/
bundled/skills/research-grants/references/nstc_guidelines.md
- Network accessline 7
**Official Name**: 國家科學及技術委員會 (National Science and Technology Council, NSTC) **Former Name**: 科技部 (Ministry of Science and Technology, MOST) **Official Website**: https://www.nstc.gov.tw/ - Network accessline 9
**Official Website**: https://www.nstc.gov.tw/ - Network accessline 152
**NSTC Website**: https://www.nstc.gov.tw/ - Network accessline 168
**nstc-proposal** - Professional LaTeX classes for NSTC proposals: - **GitHub**: https://github.com/L-TChen/nstc-proposal - Network accessline 169
- **GitHub**: https://github.com/L-TChen/nstc-proposal - Network accessline 184
# Or manual installation from GitHub git clone https://github.com/L-TChen/nstc-proposal.git - Network accessline 185
git clone https://github.com/L-TChen/nstc-proposal.git - Network accessline 213
**Engineering Division Template**: - GitHub: https://github.com/mcps5601/NSTC-proposal-LaTeX - Network accessline 214
- GitHub: https://github.com/mcps5601/NSTC-proposal-LaTeX - Network accessline 220
1. **audachang's CM03 Template** (Recommended for Overleaf users): - GitHub: https://github.com/audachang/taiwan-nstc-cm03-template - Network accessline 221
- GitHub: https://github.com/audachang/taiwan-nstc-cm03-template - Network accessline 733
For the most authoritative information, visit: **https://www.nstc.gov.tw/**
bundled/skills/research-lookup/README.md
bundled/skills/research-lookup/SKILL.md
bundled/skills/research-lookup/examples.py
bundled/skills/research-lookup/lookup.py
bundled/skills/research-lookup/research_lookup.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 44
[Credential-related source omitted] - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 46
[Credential-related source omitted] - Network accessline 48
self.base_url = "https://openrouter.ai/api/v1" - Network accessline 51
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Network accessline 52
"Content-Type": "application/json", "HTTP-Referer": "https://scientific-writer.local", "X-Title": "Scientific Writer Research Tool" - Network accessline 53
"HTTP-Referer": "https://scientific-writer.local", - Network accessline 101
try: response = requests.post( - Network accessline 102
response = requests.post( - Network accessline 253
# Look for DOI patterns first (most reliable) # Matches: doi:10.xxx, DOI: 10.xxx, https://doi.org/10.xxx - Network accessline 254
# Matches: doi:10.xxx, DOI: 10.xxx, https://doi.org/10.xxx - Network accessline 265
"type": "doi", "doi": doi_clean, "url": f"https://doi.org/{doi_clean}" - Network accessline 266
"doi": doi_clean, "url": f"https://doi.org/{doi_clean}" }) - Network accessline 267
"url": f"https://doi.org/{doi_clean}" - Network accessline 304
try: response = requests.get( - Network accessline 305
response = requests.get( - Access to secretsline 330
[Credential-related source omitted] - Access to secretsline 331
[Credential-related source omitted] - Access to secretsline 332
[Credential-related source omitted] - Access to secretsline 333
[Credential-related source omitted]
bundled/skills/research-lookup/scripts/research_lookup.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 44
[Credential-related source omitted] - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 46
[Credential-related source omitted] - Network accessline 48
self.base_url = "https://openrouter.ai/api/v1" - Network accessline 51
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Network accessline 52
"Content-Type": "application/json", "HTTP-Referer": "https://scientific-writer.local", "X-Title": "Scientific Writer Research Tool" - Network accessline 53
"HTTP-Referer": "https://scientific-writer.local", - Network accessline 101
try: response = requests.post( - Network accessline 102
response = requests.post( - Network accessline 253
# Look for DOI patterns first (most reliable) # Matches: doi:10.xxx, DOI: 10.xxx, https://doi.org/10.xxx - Network accessline 254
# Matches: doi:10.xxx, DOI: 10.xxx, https://doi.org/10.xxx - Network accessline 265
"type": "doi", "doi": doi_clean, "url": f"https://doi.org/{doi_clean}" - Network accessline 266
"doi": doi_clean, "url": f"https://doi.org/{doi_clean}" }) - Network accessline 267
"url": f"https://doi.org/{doi_clean}" - Network accessline 304
try: response = requests.get( - Network accessline 305
response = requests.get( - Access to secretsline 330
[Credential-related source omitted] - Access to secretsline 331
[Credential-related source omitted] - Access to secretsline 332
[Credential-related source omitted] - Access to secretsline 333
[Credential-related source omitted]
bundled/skills/rowan/SKILL.md
- Network accessline 44
Generate an API key at [labs.rowansci.com/account/api-keys](https://labs.rowansci.com/account/api-keys). - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 54
[Credential-related source omitted] - Access to secretsline 57
[Credential-related source omitted] - Possible obfuscationline 188
protein_seq = "MENFQKVEKIGEGTYGVVYKARNKLTGEVVALKKIRLDTETEGVPSTAIREISLLKELNHPNIVKLLDVIHTENKLYLVFEFLHQDLKKFMDASALTGIPLPLIKSYLFQLLQGLAFCHSHRVLHRDLKPQNLLINTEGAIKLADFGLARAFGVPVRTYTHEVVTLWYRAPEILLGCKYYSTAVDIWSLGCIFAEMVTRRALFPGDSEIDQLFRIFRTLGTPDEV - Network accessline 424
- **Web Interface**: https://labs.rowansci.com - Network accessline 425
- **Documentation**: https://docs.rowansci.com - Network accessline 426
- **Python API Docs**: https://docs.rowansci.com/api/python/v2/ - Network accessline 427
- **Tutorials**: https://docs.rowansci.com/tutorials
bundled/skills/rowan/references/api_reference.md
- Access to secretsline 325
[Credential-related source omitted]
bundled/skills/scanpy/SKILL.md
bundled/skills/scanpy/assets/analysis_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scanpy/scripts/qc_analysis.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scholar-evaluation/SKILL.md
- Network accessline 295
**Moussa, H. N., Da Silva, P. Q., Adu-Ampratwum, D., East, A., Lu, Z., Puccetti, N., Xue, M., Sun, H., Majumder, B. P., & Kumar, S. (2025).** _ScholarEval: Research Idea Evaluation Grounded in Literature_. arXiv preprint arXiv:2510.16234. [
bundled/skills/scholar-evaluation/scripts/calculate_scores.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scholarly-publishing/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/scientific-critical-thinking/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash
bundled/skills/scientific-reporting/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/scientific-schematics/SKILL.md
- Broad permissionsline 1
Bash - Access to secretsline 76
[Credential-related source omitted] - Network accessline 79
Get an API key at: https://openrouter.ai/keys - Access to secretsline 261
[Credential-related source omitted] - Network accessline 525
**Python Libraries** - Schemdraw Documentation: https://schemdraw.readthedocs.io/ - Network accessline 526
- Schemdraw Documentation: https://schemdraw.readthedocs.io/ - Network accessline 527
- NetworkX Documentation: https://networkx.org/documentation/ - Network accessline 528
- Matplotlib Documentation: https://matplotlib.org/ - Network accessline 530
**Publication Standards** - Nature Figure Guidelines: https://www.nature.com/nature/for-authors/final-submission - Network accessline 531
- Nature Figure Guidelines: https://www.nature.com/nature/for-authors/final-submission - Network accessline 532
- Science Figure Guidelines: https://www.science.org/content/page/instructions-preparing-initial-manuscript - Network accessline 533
- CONSORT Diagram: http://www.consort-statement.org/consort-statement/flow-diagram - Access to secretsline 603
[Credential-related source omitted] - Network accessline 605
# Get key at: https://openrouter.ai/keys
bundled/skills/scientific-schematics/references/QUICK_REFERENCE.md
- Network accessline 8
# Get API key from https://openrouter.ai/keys - Access to secretsline 9
[Credential-related source omitted] - Access to secretsline 12
[Credential-related source omitted] - Access to secretsline 118
[Credential-related source omitted] - Access to secretsline 136
[Credential-related source omitted] - Access to secretsline 139
[Credential-related source omitted] - Access to secretsline 193
[Credential-related source omitted] - Network accessline 204
- Implementation details: `IMPLEMENTATION_SUMMARY.md` - Example script: `example_usage.sh` - Get API key: https://openrouter.ai/keys - Network accessline 206
- Get API key: https://openrouter.ai/keys
bundled/skills/scientific-schematics/references/README.md
- Access to secretsline 13
[Credential-related source omitted] - Network accessline 58
# Get OpenRouter API key # Visit: https://openrouter.ai/keys - Network accessline 59
# Visit: https://openrouter.ai/keys - Access to secretsline 62
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted] - Access to secretsline 65
[Credential-related source omitted] - Access to secretsline 143
[Credential-related source omitted] - Access to secretsline 244
[Credential-related source omitted] - Access to secretsline 247
[Credential-related source omitted] - Access to secretsline 250
[Credential-related source omitted] - Network accessline 269
# Check API status curl https://openrouter.ai/api/v1/models - Network accessline 270
curl https://openrouter.ai/api/v1/models
bundled/skills/scientific-schematics/references/best_practices.md
- Network accessline 533
**Contrast Checking** - WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 534
- WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 535
- Colorable: https://colorable.jxnblk.com/ - Network accessline 552
- **Nature Figure Preparation**: https://www.nature.com/nature/for-authors/final-submission - Network accessline 553
- **Science Figure Guidelines**: https://www.science.org/content/page/instructions-preparing-initial-manuscript - Network accessline 554
- **WCAG Accessibility Standards**: https://www.w3.org/WAI/WCAG21/quickref/ - Network accessline 555
- **Color Universal Design (CUD)**: https://jfly.uni-koeln.de/color/ - Network accessline 556
- **ColorBrewer**: https://colorbrewer2.org/
bundled/skills/scientific-schematics/scripts/example_usage.sh
- Executable scriptline 1
#!/bin/bash - Access to secretsline 5
[Credential-related source omitted] - Access to secretsline 18
[Credential-related source omitted] - Network accessline 19
[Credential-related source omitted] - Access to secretsline 19
[Credential-related source omitted] - Network accessline 20
[Credential-related source omitted] - Network accessline 21
echo "Get an API key at: https://openrouter.ai/keys" - Access to secretsline 22
[Credential-related source omitted] - Access to secretsline 26
[Credential-related source omitted]
bundled/skills/scientific-schematics/scripts/generate_schematic.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 71
[Credential-related source omitted] - Access to secretsline 86
[Credential-related source omitted] - Access to secretsline 93
[Credential-related source omitted] - Access to secretsline 94
[Credential-related source omitted] - Network accessline 95
[Credential-related source omitted] - Access to secretsline 95
[Credential-related source omitted] - Network accessline 96
print("\nFor AI generation, you need an OpenRouter API key.") print("Get one at: https://openrouter.ai/keys") print("\nSet it with:") - Network accessline 97
print("Get one at: https://openrouter.ai/keys") - Access to secretsline 99
[Credential-related source omitted] - Access to secretsline 122
[Credential-related source omitted] - Access to secretsline 123
[Credential-related source omitted]
bundled/skills/scientific-schematics/scripts/generate_schematic_ai.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 12
[Credential-related source omitted] - Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 57
[Credential-related source omitted] - Access to secretsline 68
[Credential-related source omitted] - Access to secretsline 140
[Credential-related source omitted] - Access to secretsline 145
[Credential-related source omitted] - Access to secretsline 148
[Credential-related source omitted] - Access to secretsline 149
[Credential-related source omitted] - Access to secretsline 151
[Credential-related source omitted] - Access to secretsline 152
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Access to secretsline 156
[Credential-related source omitted] - Access to secretsline 158
[Credential-related source omitted] - Access to secretsline 159
[Credential-related source omitted] - Network accessline 160
[Credential-related source omitted] - Access to secretsline 160
[Credential-related source omitted] - Network accessline 161
[Credential-related source omitted] - Access to secretsline 161
[Credential-related source omitted] - Network accessline 162
"Get your API key from: https://openrouter.ai/keys" - Network accessline 165
self.verbose = verbose self._last_error = None # Track last error for better reporting self.base_url = "https://openrouter.ai/api/v1" - Network accessline 167
self.base_url = "https://openrouter.ai/api/v1" - Network accessline 168
# Nano Banana Pro - Google's advanced image generation model # https://openrouter.ai/google/gemini-3-pro-image-preview - Network accessline 169
# https://openrouter.ai/google/gemini-3-pro-image-preview - Network accessline 193
[Credential-related source omitted] - Access to secretsline 193
[Credential-related source omitted] - Network accessline 194
"Content-Type": "application/json", "HTTP-Referer": "https://github.com/scientific-writer", "X-Title": "Scientific Schematic Generator" - Network accessline 195
"HTTP-Referer": "https://github.com/scientific-writer", - Network accessline 209
try: response = requests.post( - Network accessline 210
response = requests.post( - Possible obfuscationline 277
return base64.b64decode(base64_str) - Possible obfuscationline 292
return base64.b64decode(base64_str) - Possible obfuscationline 304
return base64.b64decode(base64_str) - Access to secretsline 781
[Credential-related source omitted] - Access to secretsline 794
[Credential-related source omitted] - Access to secretsline 801
[Credential-related source omitted] - Access to secretsline 802
[Credential-related source omitted] - Access to secretsline 803
[Credential-related source omitted] - Access to secretsline 805
[Credential-related source omitted] - Access to secretsline 815
[Credential-related source omitted]
bundled/skills/scientific-slides/SKILL.md
bundled/skills/scientific-slides/assets/beamer_template_conference.tex
bundled/skills/scientific-slides/assets/beamer_template_seminar.tex
bundled/skills/scientific-slides/references/beamer_guide.md
- Network accessline 749
% External links \begin{frame}{Resources} Visit \url{https://example.com} for more information. - Network accessline 751
Visit \url{https://example.com} for more information. - Network accessline 753
\href{https://github.com/user/repo}{GitHub Repository} - Network accessline 762
\begin{frame}{Scan for Paper} \begin{center} \qrcode[height=3cm]{https://doi.org/10.1234/paper} - Network accessline 764
\qrcode[height=3cm]{https://doi.org/10.1234/paper} - Network accessline 996
- Beamer User Guide: `texdoc beamer` - Theme Gallery: https://deic.uab.cat/~iblanes/beamer_gallery/ - Network accessline 997
- Theme Gallery: https://deic.uab.cat/~iblanes/beamer_gallery/ - Network accessline 998
- TikZ Examples: https://texample.net/tikz/
bundled/skills/scientific-slides/references/visual_review_workflow.md
bundled/skills/scientific-slides/scripts/generate_slide_image.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 72
[Credential-related source omitted] - Access to secretsline 84
[Credential-related source omitted] - Access to secretsline 90
[Credential-related source omitted] - Access to secretsline 91
[Credential-related source omitted] - Network accessline 92
[Credential-related source omitted] - Access to secretsline 92
[Credential-related source omitted] - Network accessline 93
print("\nFor AI generation, you need an OpenRouter API key.") print("Get one at: https://openrouter.ai/keys") print("\nSet it with:") - Network accessline 94
print("Get one at: https://openrouter.ai/keys") - Access to secretsline 96
[Credential-related source omitted] - Access to secretsline 124
[Credential-related source omitted] - Access to secretsline 125
[Credential-related source omitted]
bundled/skills/scientific-slides/scripts/generate_slide_image_ai.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 18
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 57
[Credential-related source omitted] - Access to secretsline 65
[Credential-related source omitted] - Access to secretsline 76
[Credential-related source omitted] - Access to secretsline 170
[Credential-related source omitted] - Access to secretsline 175
[Credential-related source omitted] - Access to secretsline 178
[Credential-related source omitted] - Access to secretsline 180
[Credential-related source omitted] - Access to secretsline 182
[Credential-related source omitted] - Access to secretsline 184
[Credential-related source omitted] - Access to secretsline 186
[Credential-related source omitted] - Access to secretsline 187
[Credential-related source omitted] - Network accessline 188
[Credential-related source omitted] - Access to secretsline 188
[Credential-related source omitted] - Network accessline 189
[Credential-related source omitted] - Access to secretsline 189
[Credential-related source omitted] - Network accessline 190
"Get your API key from: https://openrouter.ai/keys" - Network accessline 193
self.verbose = verbose self._last_error = None self.base_url = "https://openrouter.ai/api/v1" - Network accessline 195
self.base_url = "https://openrouter.ai/api/v1" - Network accessline 210
[Credential-related source omitted] - Access to secretsline 210
[Credential-related source omitted] - Network accessline 211
"Content-Type": "application/json", "HTTP-Referer": "https://github.com/scientific-writer", "X-Title": "Scientific Slide Generator" - Network accessline 212
"HTTP-Referer": "https://github.com/scientific-writer", - Network accessline 226
try: response = requests.post( - Network accessline 227
response = requests.post( - Possible obfuscationline 277
return base64.b64decode(base64_str) - Possible obfuscationline 288
return base64.b64decode(base64_str) - Possible obfuscationline 299
return base64.b64decode(base64_str) - Access to secretsline 706
[Credential-related source omitted] - Access to secretsline 718
[Credential-related source omitted] - Access to secretsline 723
[Credential-related source omitted] - Access to secretsline 724
[Credential-related source omitted] - Access to secretsline 725
[Credential-related source omitted] - Access to secretsline 727
[Credential-related source omitted] - Access to secretsline 742
[Credential-related source omitted]
bundled/skills/scientific-slides/scripts/pdf_to_images.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scientific-slides/scripts/slides_to_pdf.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scientific-slides/scripts/validate_presentation.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scientific-visualization/assets/color_palettes.py
bundled/skills/scientific-visualization/references/color_palettes.md
- Network accessline 233
### Online Simulators - **Coblis**: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 234
- **Coblis**: https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 344
- **ColorBrewer**: http://colorbrewer2.org/ - Choose palettes by colorblind-safe option - Network accessline 345
- **Paul Tol's palettes**: https://personal.sron.nl/~pault/ - Network accessline 346
- **Okabe-Ito palette origin**: "Color Universal Design" (Okabe & Ito, 2008) - **Matplotlib colormaps**: https://matplotlib.org/stable/tutorials/colors/colormaps.html - **Seaborn palettes**: https://seaborn.pydata.org/tutorial/color_palette - Network accessline 347
- **Matplotlib colormaps**: https://matplotlib.org/stable/tutorials/colors/colormaps.html - Network accessline 348
- **Seaborn palettes**: https://seaborn.pydata.org/tutorial/color_palettes.html
bundled/skills/scientific-visualization/references/matplotlib_examples.md
bundled/skills/scientific-visualization/scripts/figure_export.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scientific-visualization/scripts/style_presets.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/scientific-writing/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/scientific-writing/references/citation_styles.md
- Network accessline 204
Author, A. A., Author, B. B., & Author, C. C. (Year). Title of article. Journal Name, Volume(Issue), page range. https://doi.org/xx.xxxx - Network accessline 209
Smith, J. D., Johnson, A. B., & Williams, C. D. (2023). Effectiveness of cognitive behavioral therapy for anxiety disorders. JAMA Psychiatry, 80(5), 456-464. https://doi.org/10.1001/jamapsychiatry.2023.0123 - Network accessline 214
Author, A. A. (Year). Book title: Subtitle (Edition). Publisher. https://doi.org/xx.xxxx - Network accessline 453
doi:10.1001/jamapsychiatry.2023.0123 or https://doi.org/10.1001/jamapsychiatry.2023.0123 - Network accessline 455
https://doi.org/10.1001/jamapsychiatry.2023.0123 - Network accessline 459
- Required by most journals for recent publications - Preferred over URLs because DOIs don't change - Look up DOIs at https://www.crossref.org/ if not provided - Network accessline 461
- Look up DOIs at https://www.crossref.org/ if not provided - Network accessline 463
### Style-specific formatting: - **AMA**: `doi:10.xxxx/xxxxx` - **APA**: `https://doi.org/10.xxxx/xxxxx` - Network accessline 464
- **AMA**: `doi:10.xxxx/xxxxx` - **APA**: `https://doi.org/10.xxxx/xxxxx` - **Vancouver**: Often omitted or added at journal's discretion - Network accessline 465
- **APA**: `https://doi.org/10.xxxx/xxxxx` - Network accessline 467
- **Chicago**: `https://doi.org/10.xxxx/xxxxx` - Network accessline 473
| **AMA** | Author AA, Author BB. Title of article. *Journal*. Year;Vol(Iss):pp. doi:xx | | **Vancouver** | Author AA, Author BB. Title of article. Journal. Year;Vol(Iss):pp. | | **APA** | Author, A. A., & Author, B. B. (Year). Title of art - Network accessline 474
| **Vancouver** | Author AA, Author BB. Title of article. Journal. Year;Vol(Iss):pp. | | **APA** | Author, A. A., & Author, B. B. (Year). Title of article. *Journal*, Vol(Iss), pp. https://doi.org/xx | | **Chicago A-D** | Author, A. A., and - Network accessline 475
| **APA** | Author, A. A., & Author, B. B. (Year). Title of article. *Journal*, Vol(Iss), pp. https://doi.org/xx | - Network accessline 499
APA: Author, A. A. (Year). Title [Preprint]. Repository Name. https://doi.org/xx.xxxx - Network accessline 519
APA: Author, A. A. (Year). Title of dataset (Version X) [Data set]. Repository. https://doi.org/xx.xxxx - Network accessline 694
### Official Manuals - AMA: https://www.amamanualofstyle.com/ - Network accessline 695
- AMA: https://www.amamanualofstyle.com/ - Network accessline 696
- Vancouver/ICMJE: http://www.icmje.org/ - Network accessline 697
- APA: https://apastyle.apa.org/ - Network accessline 698
- Chicago: https://www.chicagomanualofstyle.org/ - Network accessline 699
- IEEE: https://ieeeauthorcenter.ieee.org/ - Network accessline 701
### Journal-Specific Style Guides - Nature: https://www.nature.com/nature/for-authors/formatting-guide - Network accessline 702
- Nature: https://www.nature.com/nature/for-authors/formatting-guide - Network accessline 703
- Science: https://www.science.org/content/page/instructions-authors - Network accessline 704
- Cell: https://www.cell.com/cell/authors - Network accessline 705
- JAMA: https://jamanetwork.com/journals/jama/pages/instructions-for-authors - Network accessline 707
### Quick Reference Guides - Purdue OWL: https://owl.purdue.edu/ - Network accessline 708
- Purdue OWL: https://owl.purdue.edu/ - Network accessline 709
- Citation Machine: https://www.citationmachine.net/ - Network accessline 710
- EasyBib: https://www.easybib.com/ - Network accessline 712
### Reference Management - Zotero: https://www.zotero.org/ - Network accessline 713
- Zotero: https://www.zotero.org/ - Network accessline 714
- Mendeley: https://www.mendeley.com/ - Network accessline 715
- EndNote: https://endnote.com/ - Network accessline 718
- Journal Citation Reports (Clarivate): Lists journal citation styles - EndNote style repository: >7000 journal-specific styles - Zotero Style Repository: https://www.zotero.org/styles - Network accessline 720
- Zotero Style Repository: https://www.zotero.org/styles
bundled/skills/scientific-writing/references/reporting_guidelines.md
- Network accessline 86
**Where to access:** http://www.consort-statement.org/ - Network accessline 130
**Where to access:** https://www.strobe-statement.org/ - Network accessline 181
**Where to access:** http://www.prisma-statement.org/ - Network accessline 218
**Where to access:** https://www.spirit-statement.org/ - Network accessline 247
**Where to access:** https://www.equator-network.org/reporting-guidelines/stard/ - Network accessline 281
**Where to access:** https://www.tripod-statement.org/ - Network accessline 314
**Where to access:** https://arriveguidelines.org/ - Network accessline 338
**Where to access:** https://www.care-statement.org/ - Network accessline 356
**Where to access:** http://www.squire-statement.org/ - Network accessline 384
**Where to access:** https://www.equator-network.org/reporting-guidelines/cheers/ - Network accessline 403
**Where to access:** https://www.equator-network.org/reporting-guidelines/srqr/ - Network accessline 440
**Website:** https://www.equator-network.org/ - Network accessline 619
- **EQUATOR Network**: https://www.equator-network.org/ - Network accessline 620
- **CONSORT**: http://www.consort-statement.org/ - Network accessline 621
- **STROBE**: https://www.strobe-statement.org/ - Network accessline 622
- **PRISMA**: http://www.prisma-statement.org/ - Network accessline 623
- **SPIRIT**: https://www.spirit-statement.org/ - Network accessline 624
- **ARRIVE**: https://arriveguidelines.org/ - Network accessline 625
- **CARE**: https://www.care-statement.org/ - Network accessline 635
- **Some reference managers** can insert reporting guideline citations - **Covidence, RevMan** for systematic review reporting - **PRISMA flow diagram generator**: http://prisma.thetacollaborative.ca/ - Network accessline 637
- **PRISMA flow diagram generator**: http://prisma.thetacollaborative.ca/
bundled/skills/scikit-bio/SKILL.md
bundled/skills/scikit-learn/SKILL.md
- Network accessline 515
- Official Documentation: https://scikit-learn.org/stable/ - Network accessline 516
- User Guide: https://scikit-learn.org/stable/user_guide.html - Network accessline 517
- API Reference: https://scikit-learn.org/stable/api/index.html - Network accessline 518
- Examples Gallery: https://scikit-learn.org/stable/auto_examples/index.html
bundled/skills/scikit-learn/references/quick_reference.md
- Network accessline 429
- Official Documentation: https://scikit-learn.org/stable/ - Network accessline 430
- User Guide: https://scikit-learn.org/stable/user_guide.html - Network accessline 431
- API Reference: https://scikit-learn.org/stable/api/index.html - Network accessline 432
- Examples: https://scikit-learn.org/stable/auto_examples/index.html - Network accessline 433
- Tutorials: https://scikit-learn.org/stable/tutorial/index.html
bundled/skills/scikit-learn/scripts/classification_pipeline.py
- Executable scriptline 1
Executable file
bundled/skills/scikit-learn/scripts/clustering_analysis.py
- Executable scriptline 1
Executable file
bundled/skills/scikit-survival/SKILL.md
- Network accessline 354
- **Official Documentation**: https://scikit-survival.readthedocs.io/ - Network accessline 355
- **GitHub Repository**: https://github.com/sebp/scikit-survival - Network accessline 357
- **API Reference**: Complete list of classes and functions at https://scikit-survival.readthedocs.io/en/stable/api/index.html
bundled/skills/scrapling/SKILL.md
- Network accessline 87
scrapling extract get "https://example.com" out.md - Network accessline 92
scrapling extract get "https://example.com" out.txt --css-selector "main article" - Network accessline 97
scrapling extract get "https://example.com" out.html --css-selector "#content" - Network accessline 102
scrapling extract fetch "https://example.com" out.md --css-selector "main"
bundled/skills/scrapling/scripts/scrapling.ps1
- Executable scriptline 1
Executable file
bundled/skills/screenshot/LICENSE.txt
bundled/skills/screenshot/assets/screenshot-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/screenshot/scripts/ensure_macos_permissions.sh
- Executable scriptline 1
#!/usr/bin/env bash
bundled/skills/screenshot/scripts/take_screenshot.ps1
- Executable scriptline 1
Executable file
bundled/skills/screenshot/scripts/take_screenshot.py
- Executable scriptline 1
#!/usr/bin/env python3 - Possible obfuscationline 26
b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00\x00\x01" - Possible obfuscationline 27
b"\x08\x06\x00\x00\x00\x1f\x15\xc4\x89\x00\x00\x00\x0cIDAT\x08\xd7c" - Possible obfuscationline 28
b"\xf8\xff\xff?\x00\x05\xfe\x02\xfeA\xad\x1c\x1c\x00\x00\x00\x00IEND" - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 63
[Credential-related source omitted] - Access to secretsline 83
[Credential-related source omitted] - Access to secretsline 89
[Credential-related source omitted] - Access to secretsline 231
[Credential-related source omitted]
bundled/skills/security-best-practices/LICENSE.txt
bundled/skills/security-best-practices/references/golang-general-backend-security.md
- Access to secretsline 185
[Credential-related source omitted] - Access to secretsline 188
[Credential-related source omitted] - Access to secretsline 385
[Credential-related source omitted] - Network accessline 591
Required: - MUST set an overall timeout on `http.Client` usage (or equivalent per-request deadlines via context + transport timeouts). - MUST ensure `resp.Body.Close()` is called for all successful requests (typically `defer resp.Body.Close - Network accessline 592
- MUST set an overall timeout on `http.Client` usage (or equivalent per-request deadlines via context + transport timeouts). - MUST ensure `resp.Body.Close()` is called for all successful requests (typically `defer resp.Body.Close()` immedi - Network accessline 602
Detection hints: - Search for `http.Get(`, `http.Post(`, `client := &http.Client{}` without `Timeout`, `client.Do(` and missing closes. - Network accessline 603
- Search for `http.Get(`, `http.Post(`, `client := &http.Client{}` without `Timeout`, `client.Do(` and missing closes. - Network accessline 611
Notes: - The net/http package exposes `DefaultClient` as a zero-valued `http.Client`, which can easily lead to “no timeout” behavior unless configured. - Network accessline 612
- The net/http package exposes `DefaultClient` as a zero-valued `http.Client`, which can easily lead to “no timeout” behavior unless configured. - Network accessline 802
Primary Go documentation: - Go Security Policy — https://go.dev/doc/security/policy - Network accessline 803
- Go Security Policy — https://go.dev/doc/security/policy - Network accessline 804
- Go Release History (security fixes in patch releases) — https://go.dev/doc/devel/release - Network accessline 805
- Go 1.25 Release Notes — https://go.dev/doc/go1.25 - Network accessline 806
- net/http (server timeouts, MaxHeaderBytes, DefaultClient) — https://pkg.go.dev/net/http - Network accessline 807
- html/template (auto-escaping and trusted-template assumptions) — https://pkg.go.dev/html/template - Network accessline 808
- crypto/tls (MinVersion defaults, InsecureSkipVerify warnings) — https://pkg.go.dev/crypto/tls - Network accessline 809
- crypto/rand (secure randomness, token helpers) — https://pkg.go.dev/crypto/rand - Network accessline 810
- crypto/subtle (constant-time comparisons) — https://pkg.go.dev/crypto/subtle - Dangerous shell operationline 811
- os/exec (no shell by default; command execution guidance) — https://pkg.go.dev/os/exec - Network accessline 811
- os/exec (no shell by default; command execution guidance) — https://pkg.go.dev/os/exec - Network accessline 812
- unsafe (bypasses type safety) — https://go.dev/src/unsafe/unsafe.go - Network accessline 813
- net/http/pprof (debug endpoints) — https://pkg.go.dev/net/http/pprof - Network accessline 814
- cmd/go (module authentication via go.sum/checksum DB; env vars like GOINSECURE) — https://pkg.go.dev/cmd/go - Network accessline 815
- Module Mirror and Checksum Database Launched (Go blog) — https://go.dev/blog/module-mirror-launch - Network accessline 816
- govulncheck documentation — https://pkg.go.dev/golang.org/x/vuln/cmd/govulncheck - Network accessline 817
- Go Race Detector documentation — https://go.dev/doc/articles/race_detector - Network accessline 818
- bcrypt (password hashing) — https://pkg.go.dev/golang.org/x/crypto/bcrypt - Network accessline 819
- Go vulnerability entry example (multipart resource consumption) — https://pkg.go.dev/vuln/GO-2023-1569 - Network accessline 821
OWASP Cheat Sheet Series (general web security): - Session Management — https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html - Network accessline 822
- Session Management — https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html - Network accessline 823
- CSRF Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html - Network accessline 824
- SSRF Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html - Network accessline 825
- XSS Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html - Network accessline 826
- HTTP Security Response Headers — https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html
bundled/skills/security-best-practices/references/javascript-express-web-server-security.md
- Access to secretsline 379
[Credential-related source omitted] - Dangerous shell operationline 787
* `exec(req.query.cmd)` - Dangerous shell operationline 788
* `exec(`convert ${userPath} ...`)` - Dangerous shell operationline 794
* Search for `child_process`, `exec(`, `execSync(`, `spawn(`, `fork(`. - Network accessline 827
* `fetch(req.query.url)` - Network accessline 832
* Search for `fetch(`, `axios(`, `got(`, `request(`, `node-fetch` usage where URL originates from users/DB. - Network accessline 1109
* Express: Production Best Practices — Security: `https://expressjs.com/en/advanced/best-practice-security.html` ([Express][1]) - Network accessline 1110
* Express: Behind Proxies (`trust proxy`): `https://expressjs.com/en/guide/behind-proxies.html` ([Express][2]) - Network accessline 1111
* Express 5.x API Reference (parsers, static, sendFile, redirect, cookies): `https://expressjs.com/en/5x/api.html` ([Express][5]) - Network accessline 1112
* Express: Error Handling: `https://expressjs.com/en/guide/error-handling.html` ([Express][11]) - Network accessline 1116
* express-session docs (cookie flags, secret rotation, fixation mitigation, MemoryStore warning): `https://expressjs.com/en/resources/middleware/session.html` ([Express][1]) - Network accessline 1120
* Node.js — Security Best Practices (DoS, proxy guidance, inspector risks, request smuggling notes): `https://nodejs.org/en/learn/getting-started/security-best-practices` ([Node.js][15]) - Network accessline 1121
* npm Docs — `npm audit`: `https://docs.npmjs.com/cli/v9/commands/npm-audit/` ([npm Docs][16]) - Network accessline 1125
* Session Management: `https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][12]) - Network accessline 1126
* CSRF Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][3]) - Network accessline 1127
* XSS Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][4]) - Network accessline 1128
* Input Validation: `https://cheatsheetseries.owasp.org/cheatsheets/Input_Validation_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][17]) - Network accessline 1129
* SQL Injection Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][6]) - Network accessline 1130
* OS Command Injection Defense: `https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][14]) - Network accessline 1131
* SSRF Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][7]) - Network accessline 1132
* File Upload: `https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][13]) - Network accessline 1133
* Unvalidated Redirects: `https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][18]) - Network accessline 1134
* HTTP Headers: `https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][10]) - Network accessline 1138
* Express package version (npm): `https://www.npmjs.com/package/express` - Network accessline 1139
* Express open redirect advisory (CVE): `https://nvd.nist.gov/vuln/detail/CVE-2024-29041` ([NVD][9]) - Network accessline 1141
[1]: https://expressjs.com/en/advanced/best-practice-security.html "Security Best Practices for Express in Production" - Network accessline 1142
[2]: https://expressjs.com/en/guide/behind-proxies.html "Express behind proxies" - Network accessline 1143
[3]: https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html "Cross-Site Request Forgery Prevention - OWASP Cheat Sheet Series" - Network accessline 1144
[4]: https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html "Cross Site Scripting Prevention - OWASP Cheat Sheet Series" - Network accessline 1145
[5]: https://expressjs.com/en/5x/api.html "Express 5.x - API Reference" - Network accessline 1146
[6]: https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html "SQL Injection Prevention - OWASP Cheat Sheet Series" - Network accessline 1147
[7]: https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html "Server Side Request Forgery Prevention - OWASP Cheat Sheet Series" - Network accessline 1148
[8]: https://cheatsheetseries.owasp.org/cheatsheets/Nodejs_Security_Cheat_Sheet.html "Nodejs Security - OWASP Cheat Sheet Series" - Network accessline 1149
[9]: https://nvd.nist.gov/vuln/detail/cve-2024-29041?utm_source=chatgpt.com "CVE-2024-29041 Detail - NVD" - Network accessline 1150
[10]: https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html "HTTP Headers - OWASP Cheat Sheet Series" - Network accessline 1151
[11]: https://expressjs.com/en/guide/error-handling.html "Express error handling" - Network accessline 1152
[12]: https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html "Session Management - OWASP Cheat Sheet Series" - Network accessline 1153
[13]: https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html "File Upload - OWASP Cheat Sheet Series" - Network accessline 1154
[14]: https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html "OS Command Injection Defense - OWASP Cheat Sheet Series" - Network accessline 1155
[15]: https://nodejs.org/en/learn/getting-started/security-best-practices "Node.js — Security Best Practices" - Network accessline 1156
[16]: https://docs.npmjs.com/cli/v9/commands/npm-audit/ "npm-audit | npm Docs" - Network accessline 1157
[17]: https://cheatsheetseries.owasp.org/cheatsheets/Input_Validation_Cheat_Sheet.html "Input Validation - OWASP Cheat Sheet Series" - Network accessline 1158
[18]: https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html "Unvalidated Redirects and Forwards - OWASP Cheat Sheet Series"
bundled/skills/security-best-practices/references/javascript-general-web-frontend-security.md
- Dangerous shell operationline 219
* `eval()` - Dangerous shell operationline 227
* `eval(userInput)` - Dangerous shell operationline 233
* Search for `eval(`, `new Function`, `setTimeout("`, `setInterval("`. - Dangerous shell operationline 245
* CSP that blocks `eval()`-like APIs by default, and avoid `unsafe-eval`. ([MDN Web Docs][10]) - Network accessline 492
* `const ALLOWED = new Set(["https://app.example.com", "https://accounts.example.com"]);` - Access to secretsline 521
[Credential-related source omitted] - Network accessline 559
* Search HTML for `<script src="https://...">` and `tag manager` snippets. - Network accessline 583
* `<script src="https://cdn.example.com/lib.js"></script>` with no `integrity`. - Network accessline 588
* Search for `<script src="https://` and `<link rel="stylesheet" href="https://` without `integrity=`. - Dangerous shell operationline 645
* `eval(`, `new Function`, `setTimeout("`, `setInterval("` ([MDN Web Docs][10]) - Network accessline 670
* `<script src="https://...">` without `integrity=` - Network accessline 691
* W3C Content Security Policy Level 2 (HTML `<meta>` delivery restrictions; unsupported directives in meta CSP): `https://www.w3.org/TR/CSP2/` ([W3C][3]) - Network accessline 692
* MDN: CSP Guide (strict CSP, nonces/hashes, `unsafe-inline`/`unsafe-eval`, eval blocking): `https://developer.mozilla.org/en-US/docs/Web/HTTP/Guides/CSP` ([MDN Web Docs][10]) - Network accessline 693
* MDN: `<meta http-equiv>` (CSP via meta and warning about meta-based security headers): `https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Elements/meta/http-equiv` ([MDN Web Docs][1]) - Network accessline 694
* MDN: `frame-ancestors` (and note it’s not supported in `<meta>`): `https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/frame-ancestors` ([MDN Web Docs][18]) - Network accessline 698
* OWASP: DOM Based XSS Prevention Cheat Sheet (dangerous sinks + safe patterns like `textContent`): `https://cheatsheetseries.owasp.org/cheatsheets/DOM_based_XSS_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][2]) - Network accessline 699
* MDN: `innerHTML` (security considerations): `https://developer.mozilla.org/en-US/docs/Web/API/Element/innerHTML` ([MDN Web Docs][19]) - Network accessline 700
* MDN: `insertAdjacentHTML` (security considerations): `https://developer.mozilla.org/en-US/docs/Web/API/Element/insertAdjacentHTML` ([MDN Web Docs][20]) - Network accessline 701
* MDN: `document.write()` / `document.writeln()` (security considerations): `https://developer.mozilla.org/en-US/docs/Web/API/Document/write` and `https://developer.mozilla.org/en-US/docs/Web/API/Document/writeln` ([MDN Web Docs][13]) - Network accessline 705
* MDN: `javascript:` URLs (execution on navigation; discouraged; references `window.location`): `https://developer.mozilla.org/en-US/docs/Web/URI/Reference/Schemes/javascript` ([MDN Web Docs][4]) - Network accessline 709
* W3C: Trusted Types spec (DOM XSS sinks include `Element.innerHTML` and `Location.href` setters; goals and limitations): `https://www.w3.org/TR/trusted-types/` ([W3C][15]) - Network accessline 710
* MDN: `require-trusted-types-for` directive: `https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/require-trusted-types-for` ([MDN Web Docs][11]) - Network accessline 711
* MDN: `trusted-types` directive: `https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/trusted-types` ([MDN Web Docs][16]) - Network accessline 715
* MDN: `window.postMessage` (security guidance: specify targetOrigin; validate origin): `https://developer.mozilla.org/en-US/docs/Web/API/Window/postMessage` ([MDN Web Docs][5]) - Network accessline 716
* OWASP: HTML5 Security Cheat Sheet (Web Messaging guidance: explicit origin, strict checks, no `innerHTML`): `https://cheatsheetseries.owasp.org/cheatsheets/HTML5_Security_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][6]) - Network accessline 720
* OWASP: Third Party JavaScript Management Cheat Sheet (risks and mitigations including SRI/mirroring): `https://cheatsheetseries.owasp.org/cheatsheets/Third_Party_Javascript_Management_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][7]) - Network accessline 721
* MDN: Subresource Integrity overview: `https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity` ([MDN Web Docs][12]) - Network accessline 722
* W3C: Subresource Integrity spec: `https://www.w3.org/TR/sri-2/` ([W3C][21]) - Network accessline 726
* OWASP: DOM Clobbering Prevention Cheat Sheet (named property access risk; example attacks involving `location.assign` and `javascript:`): `https://cheatsheetseries.owasp.org/cheatsheets/DOM_Clobbering_Prevention_Cheat_Sheet.html` ([OWASP - Network accessline 728
[1]: https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Elements/meta/http-equiv "https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Elements/meta/http-equiv" - Network accessline 729
[2]: https://cheatsheetseries.owasp.org/cheatsheets/DOM_based_XSS_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/DOM_based_XSS_Prevention_Cheat_Sheet.html" - Network accessline 730
[3]: https://www.w3.org/TR/CSP2/ "Content Security Policy Level 2" - Network accessline 731
[4]: https://developer.mozilla.org/en-US/docs/Web/URI/Reference/Schemes/javascript "javascript: URLs - URIs | MDN" - Network accessline 732
[5]: https://developer.mozilla.org/en-US/docs/Web/API/Window/postMessage "https://developer.mozilla.org/en-US/docs/Web/API/Window/postMessage" - Network accessline 733
[6]: https://cheatsheetseries.owasp.org/cheatsheets/HTML5_Security_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/HTML5_Security_Cheat_Sheet.html" - Network accessline 734
[7]: https://cheatsheetseries.owasp.org/cheatsheets/Third_Party_Javascript_Management_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Third_Party_Javascript_Management_Cheat_Sheet.html" - Network accessline 735
[8]: https://cheatsheetseries.owasp.org/cheatsheets/DOM_Clobbering_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/DOM_Clobbering_Prevention_Cheat_Sheet.html" - Network accessline 736
[9]: https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel/noopener "https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel/noopener" - Network accessline 737
[10]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Guides/CSP "https://developer.mozilla.org/en-US/docs/Web/HTTP/Guides/CSP" - Network accessline 738
[11]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/require-trusted-types-for "https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/require-trusted-types-f - Network accessline 739
[12]: https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity "https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity" - Network accessline 740
[13]: https://developer.mozilla.org/en-US/docs/Web/API/Document/write "https://developer.mozilla.org/en-US/docs/Web/API/Document/write" - Network accessline 741
[14]: https://developer.mozilla.org/en-US/docs/Web/API/Document/writeln "https://developer.mozilla.org/en-US/docs/Web/API/Document/writeln" - Network accessline 742
[15]: https://www.w3.org/TR/trusted-types/ "https://www.w3.org/TR/trusted-types/" - Network accessline 743
[16]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/trusted-types "https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/trusted-types" - Network accessline 744
[18]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/frame-ancestors "https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/frame-ancestors" - Network accessline 745
[19]: https://developer.mozilla.org/en-US/docs/Web/API/Element/innerHTML "https://developer.mozilla.org/en-US/docs/Web/API/Element/innerHTML" - Network accessline 746
[20]: https://developer.mozilla.org/en-US/docs/Web/API/Element/insertAdjacentHTML "https://developer.mozilla.org/en-US/docs/Web/API/Element/insertAdjacentHTML" - Network accessline 747
[21]: https://www.w3.org/TR/sri-2/ "https://www.w3.org/TR/sri-2/"
bundled/skills/security-best-practices/references/javascript-jquery-web-frontend-security.md
- Network accessline 202
* `<script src="https://…/jquery.min.js"></script>` with no `integrity`. - Network accessline 328
* Without a selector in the URL, content is passed to `.html()` before scripts are removed, which can execute scripts. ([jQuery API][3]) * SHOULD prefer `fetch()`/XHR to retrieve data, then render with safe DOM creation or sanitize explicit - Network accessline 329
* SHOULD prefer `fetch()`/XHR to retrieve data, then render with safe DOM creation or sanitize explicitly. - Network accessline 346
* `fetch()` to retrieve JSON, then render via `.text()` / node construction, or - Network accessline 347
* `fetch()` to retrieve HTML, sanitize it, then inject. - Network accessline 613
* jQuery 4.0.0 release notes (Trusted Types/CSP changes; version info): `https://blog.jquery.com/2026/01/17/jquery-4-0-0/`. ([blog.jquery.com][7]) * Download jQuery (latest version info; CDN + SRI guidance): `https://jquery.com/download/`. - Network accessline 614
* Download jQuery (latest version info; CDN + SRI guidance): `https://jquery.com/download/`. ([jquery.com][8]) - Network accessline 615
* jQuery API: `.html()`: `https://api.jquery.com/html/`. ([jQuery API][21]) - Network accessline 616
* jQuery API: `.text()`: `https://api.jquery.com/text/`. ([jQuery API][14]) - Network accessline 617
* jQuery API: `.append()`: `https://api.jquery.com/append/`. ([jQuery API][22]) - Network accessline 618
* jQuery API: `.load()` (script execution behavior): `https://api.jquery.com/load/`. ([jQuery API][3]) - Network accessline 619
* jQuery API: `jQuery.parseHTML(…, keepScripts)`: `https://api.jquery.com/jQuery.parseHTML/`. ([jQuery API][2]) - Network accessline 620
* jQuery API: `$.ajax()` (`jsonp: false` security note): `https://api.jquery.com/jQuery.ajax/`. ([jQuery API][5]) - Network accessline 621
* jQuery API: `$.getScript()` (executes script): `https://api.jquery.com/jQuery.getScript/`. ([jQuery API][4]) - Network accessline 622
* jQuery API: `jQuery.escapeSelector()`: `https://api.jquery.com/jQuery.escapeSelector/`. ([jQuery API][20]) - Network accessline 626
* NVD CVE-2019-11358 (prototype pollution; jQuery < 3.4.0): `https://nvd.nist.gov/vuln/detail/CVE-2019-11358`. ([NVD][13]) - Network accessline 627
* NVD CVE-2020-11022 (XSS risk in DOM manipulation methods; patched in 3.5.0): `https://nvd.nist.gov/vuln/detail/CVE-2020-11022`. ([NVD][1]) - Network accessline 628
* NVD CVE-2020-11023 (XSS risk involving `<option>`; patched in 3.5.0): `https://nvd.nist.gov/vuln/detail/CVE-2020-11023`. ([NVD][23]) - Network accessline 629
* GitHub Security Advisory GHSA-gxr4-xjj5-5px2 (jQuery htmlPrefilter XSS; patched in 3.5.0): `https://github.com/jquery/jquery/security/advisories/GHSA-gxr4-xjj5-5px2`. ([GitHub][16]) - Network accessline 633
* XSS Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html`. ([OWASP Cheat Sheet Series][24]) - Network accessline 634
* DOM-based XSS Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/DOM_based_XSS_Prevention_Cheat_Sheet.html`. ([OWASP Cheat Sheet Series][25]) - Network accessline 635
* CSRF Prevention: `https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html`. ([OWASP Cheat Sheet Series][19]) - Network accessline 636
* HTTP Security Headers: `https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html`. ([OWASP Cheat Sheet Series][12]) - Network accessline 637
* Content Security Policy Cheat Sheet: `https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet.html`. ([OWASP Cheat Sheet Series][9]) - Network accessline 641
* MDN: Subresource Integrity (SRI): `https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity`. ([MDN Web Docs][26]) - Network accessline 642
* W3C: SRI specification: `https://www.w3.org/TR/sri-2/`. ([W3C][27]) - Network accessline 643
* MDN: CSP guide: `https://developer.mozilla.org/en-US/docs/Web/HTTP/Guides/CSP`. ([MDN Web Docs][28]) - Network accessline 644
* MDN: `require-trusted-types-for` directive: `https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/require-trusted-types-for`. ([MDN Web Docs][11]) - Network accessline 645
* MDN: Trusted Types API: `https://developer.mozilla.org/en-US/docs/Web/API/Trusted_Types_API`. ([MDN Web Docs][29]) - Network accessline 646
* W3C: Trusted Types specification: `https://www.w3.org/TR/trusted-types/`. ([W3C][10]) - Network accessline 647
* MDN: `javascript:` URL scheme warning: `https://developer.mozilla.org/en-US/docs/Web/URI/Reference/Schemes/javascript`. ([MDN Web Docs][6]) - Network accessline 648
* DOMPurify project documentation: `https://github.com/cure53/DOMPurify`. ([GitHub][17]) - Network accessline 650
[1]: https://nvd.nist.gov/vuln/detail/cve-2020-11022?utm_source=chatgpt.com "CVE-2020-11022 Detail - NVD" - Network accessline 651
[2]: https://api.jquery.com/jQuery.parseHTML/?utm_source=chatgpt.com "jQuery.parseHTML()" - Network accessline 652
[3]: https://api.jquery.com/load/?utm_source=chatgpt.com ".load() | jQuery API Documentation" - Network accessline 653
[4]: https://api.jquery.com/jQuery.getScript/?utm_source=chatgpt.com "jQuery.getScript()" - Network accessline 654
[5]: https://api.jquery.com/jQuery.ajax/?utm_source=chatgpt.com "jQuery.ajax()" - Network accessline 655
[6]: https://developer.mozilla.org/en-US/docs/Web/URI/Reference/Schemes/javascript?utm_source=chatgpt.com "javascript: URLs - URIs - MDN Web Docs" [7]: https://blog.jquery.com/2026/01/17/jquery-4-0-0/ "jQuery 4.0.0 | Official jQuery Blog" [ - Network accessline 656
[7]: https://blog.jquery.com/2026/01/17/jquery-4-0-0/ "jQuery 4.0.0 | Official jQuery Blog" [8]: https://jquery.com/download/ "Download jQuery | jQuery" [9]: https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet - Network accessline 657
[8]: https://jquery.com/download/ "Download jQuery | jQuery" - Network accessline 658
[9]: https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet.html?utm_source=chatgpt.com "Content Security Policy - OWASP Cheat Sheet Series" - Network accessline 659
[10]: https://www.w3.org/TR/trusted-types/?utm_source=chatgpt.com "Trusted Types" - Network accessline 660
[11]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Content-Security-Policy/require-trusted-types-for?utm_source=chatgpt.com "Content-Security-Policy: require-trusted-types-for directive" - Network accessline 661
[12]: https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html?utm_source=chatgpt.com "HTTP Security Response Headers Cheat Sheet" - Network accessline 662
[13]: https://nvd.nist.gov/vuln/detail/cve-2019-11358?utm_source=chatgpt.com "CVE-2019-11358 Detail - NVD" - Network accessline 663
[14]: https://api.jquery.com/text/?utm_source=chatgpt.com ".text() | jQuery API Documentation" - Network accessline 664
[15]: https://api.jquery.com/val/?utm_source=chatgpt.com ".val() | jQuery API Documentation" - Network accessline 665
[16]: https://github.com/jquery/jquery/security/advisories/GHSA-gxr4-xjj5-5px2 "Potential XSS vulnerability in jQuery.htmlPrefilter and related methods · Advisory · jquery/jquery · GitHub" - Network accessline 666
[17]: https://github.com/cure53/DOMPurify?utm_source=chatgpt.com "DOMPurify - a DOM-only, super-fast, uber-tolerant XSS ..." - Network accessline 667
[18]: https://developer.mozilla.org/en-US/docs/Web/API/HTML_Sanitizer_API?utm_source=chatgpt.com "HTML Sanitizer API - MDN Web Docs" - Network accessline 668
[19]: https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html?utm_source=chatgpt.com "Cross-Site Request Forgery Prevention Cheat Sheet" - Network accessline 669
[20]: https://api.jquery.com/jQuery.escapeSelector/?utm_source=chatgpt.com "jQuery.escapeSelector()" - Network accessline 670
[21]: https://api.jquery.com/html/?utm_source=chatgpt.com ".html() | jQuery API Documentation" - Network accessline 671
[22]: https://api.jquery.com/append/?utm_source=chatgpt.com ".append() | jQuery API Documentation" - Network accessline 672
[23]: https://nvd.nist.gov/vuln/detail/cve-2020-11023?utm_source=chatgpt.com "CVE-2020-11023 Detail - NVD" - Network accessline 673
[24]: https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html?utm_source=chatgpt.com "Cross Site Scripting Prevention - OWASP Cheat Sheet Series" - Network accessline 674
[25]: https://cheatsheetseries.owasp.org/cheatsheets/DOM_based_XSS_Prevention_Cheat_Sheet.html?utm_source=chatgpt.com "DOM based XSS Prevention Cheat Sheet" - Network accessline 675
[26]: https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity?utm_source=chatgpt.com "Subresource Integrity - Security - MDN Web Docs" - Network accessline 676
[27]: https://www.w3.org/TR/sri-2/?utm_source=chatgpt.com "Subresource Integrity" - Network accessline 677
[28]: https://developer.mozilla.org/en-US/docs/Web/HTTP/Guides/CSP?utm_source=chatgpt.com "Content Security Policy (CSP) - HTTP - MDN Web Docs" - Network accessline 678
[29]: https://developer.mozilla.org/en-US/docs/Web/API/Trusted_Types_API?utm_source=chatgpt.com "Trusted Types API - MDN Web Docs"
bundled/skills/security-best-practices/references/javascript-typescript-nextjs-web-server-security.md
- Network accessline 198
IMPORTANT: Any versions older than these minor versions are vulnerable to "react2shell" vulnerability (https://nextjs.org/blog/CVE-2025-66478): - Access to secretsline 228
[Credential-related source omitted] - Access to secretsline 233
[Credential-related source omitted] - Network accessline 715
* MUST treat any server-side `fetch()` to a user-provided URL as high-risk. - Network accessline 726
* `await fetch(req.query.url)` or `await fetch((await request.json()).url)` - Network accessline 731
* Search for `fetch(` in server code and trace where the URL comes from. - Dangerous shell operationline 866
* `exec("convert " + filename)` - Dangerous shell operationline 892
* `eval(req.body.code)` - Dangerous shell operationline 897
* Search for `eval(`, `new Function`, `vm.`, `require(` with non-literals. - Network accessline 977
* Blindly cloning all request headers to an outbound `fetch()` call. - Network accessline 1013
* Use a configured, allowlisted canonical app origin (e.g., `APP_ORIGIN=https://example.com`). - Network accessline 1083
* `fetch(userProvidedUrl)` from Route Handlers / Server Actions - Network accessline 1110
* Next.js Docs: Installation (system requirements / Node version) — `https://nextjs.org/docs/app/getting-started/installation` - Network accessline 1111
* Next.js Docs: Route Handlers — `https://nextjs.org/docs/app/getting-started/route-handlers` - Network accessline 1112
* Next.js Docs: API Routes (Pages Router) — `https://nextjs.org/docs/pages/building-your-application/routing/api-routes` - Network accessline 1113
* Next.js Docs: Environment Variables — `https://nextjs.org/docs/pages/guides/environment-variables` - Network accessline 1114
* Next.js Docs: Data Security — `https://nextjs.org/docs/app/guides/data-security` - Network accessline 1115
* Next.js Docs: Content Security Policy — `https://nextjs.org/docs/app/guides/content-security-policy` - Network accessline 1116
* Next.js Docs: Proxy — `https://nextjs.org/docs/app/getting-started/proxy` - Network accessline 1117
* Next.js Docs: `serverActions.allowedOrigins` and `serverActions.bodySizeLimit` — `https://nextjs.org/docs/app/api-reference/config/next-config-js/serverActions` - Network accessline 1118
* Next.js Docs: `cookies()` — `https://nextjs.org/docs/app/api-reference/functions/cookies` - Network accessline 1119
* Next.js Docs: `headers()` — `https://nextjs.org/docs/app/api-reference/functions/headers` - Network accessline 1120
* Next.js Docs: Self-hosting (reverse proxy guidance) — `https://nextjs.org/docs/pages/guides/self-hosting` - Network accessline 1121
* Next.js Docs: Support policy (supported versions/LTS) — `https://nextjs.org/docs/support-policy` - Network accessline 1125
* Next.js Blog: How to think about security in Next.js — `https://nextjs.org/blog/security-nextjs-server-components-actions` - Network accessline 1126
* GitHub Security Advisory: Next.js DoS via Server Components / Server Actions (CVE-2026-23864) — `https://github.com/advisories/GHSA-fq29-rrrv-cq2m` - Network accessline 1127
* Next.js Blog: Security update (example security advisory context) — `https://nextjs.org/blog/security-update` - Network accessline 1131
* OWASP Cheat Sheet Series (CSRF, Session Management, XSS Prevention, SSRF Prevention, File Upload, HTTP Headers) — `https://cheatsheetseries.owasp.org/` - Network accessline 1133
[1]: https://nextjs.org/docs/app/getting-started/route-handlers "Getting Started: Route Handlers | Next.js" - Network accessline 1134
[2]: https://nextjs.org/docs/app/getting-started/deploying?utm_source=chatgpt.com "Getting Started: Deploying" - Network accessline 1135
[3]: https://nextjs.org/docs/pages/building-your-application/routing/api-routes "Routing: API Routes | Next.js" - Network accessline 1136
[4]: https://nextjs.org/docs/app/api-reference/functions/headers "Functions: headers | Next.js" - Network accessline 1137
[5]: https://nextjs.org/docs/app/api-reference/config/next-config-js/serverActions "next.config.js: serverActions | Next.js" - Network accessline 1138
[6]: https://nextjs.org/blog/security-nextjs-server-components-actions "How to Think About Security in Next.js | Next.js" - Network accessline 1139
[7]: https://nextjs.org/docs/pages/guides/environment-variables "Guides: Environment Variables | Next.js" - Network accessline 1140
[8]: https://nextjs.org/docs/pages/guides/self-hosting?utm_source=chatgpt.com "Guides: Self-Hosting" - Network accessline 1141
[9]: https://nextjs.org/docs/app/api-reference/functions/cookies "Functions: cookies | Next.js" - Network accessline 1142
[10]: https://nextjs.org/blog/next-16?utm_source=chatgpt.com "Next.js 16" - Network accessline 1143
[11]: https://github.com/vercel/next.js/security/advisories/GHSA-9g9p-9gw9-jx7f?utm_source=chatgpt.com "Denial of Service in Image Optimizer · Advisory" - Network accessline 1144
[12]: https://nextjs.org/docs/pages/guides/authentication "Guides: Authentication | Next.js"
bundled/skills/security-best-practices/references/javascript-typescript-react-web-frontend-security.md
- Access to secretsline 155
[Credential-related source omitted] - Network accessline 446
* `<script src="https://cdn.example.com/lib/latest.js"></script>` with no integrity. - Network accessline 564
* `fetch('/api/transfer', { method: 'POST', credentials: 'include' })` with no CSRF token/header, relying only on cookies. - Network accessline 635
* `fetch(userProvidedUrl, { credentials: 'include' })` - Network accessline 641
* Search for `fetch(` / `axios(` where the first argument or `baseURL` is derived from: - Dangerous shell operationline 775
* `window.addEventListener('message', (e) => { eval(e.data) })` - Dangerous shell operationline 884
* `eval(`, `new Function(`, `setTimeout("`, `setInterval("` - Network accessline 922
* React 19 stable announcement — `https://react.dev/blog/2024/12/05/react-19` ([React][23]) - Network accessline 923
* React DOM docs: `dangerouslySetInnerHTML` warning — `https://react.dev/reference/react-dom/components/common#dangerouslysetting-the-inner-html` ([React][12]) - Network accessline 924
* React (legacy) JSX escaping statement — `https://legacy.reactjs.org/docs/introducing-jsx.html` ([React][14]) - Network accessline 928
* Cross Site Scripting Prevention (framework escape hatches; React `dangerouslySetInnerHTML`; URL validation notes) — `https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Seri - Network accessline 929
* Content Security Policy — `https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][2]) - Network accessline 930
* Cross-Site Request Forgery Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][6]) - Network accessline 931
* HTML5 Security (Web Storage, postMessage, tabnabbing, sandboxed frames) — `https://cheatsheetseries.owasp.org/cheatsheets/HTML5_Security_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][4]) - Network accessline 932
* Third Party JavaScript Management — `https://cheatsheetseries.owasp.org/cheatsheets/Third_Party_Javascript_Management_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][5]) - Network accessline 933
* File Upload — `https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][19]) - Network accessline 934
* NPM Security best practices — `https://cheatsheetseries.owasp.org/cheatsheets/NPM_Security_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][22]) - Network accessline 938
* Trusted Types API — `https://developer.mozilla.org/en-US/docs/Web/API/Trusted_Types_API` ([MDN Web Docs][3]) - Network accessline 939
* W3C Trusted Types spec — `https://www.w3.org/TR/trusted-types/` ([W3C][15]) - Network accessline 940
* Subresource Integrity — `https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity` ([MDN Web Docs][7]) - Network accessline 941
* Clickjacking defenses overview — `https://developer.mozilla.org/en-US/docs/Web/Security/Attacks/Clickjacking` ([MDN Web Docs][8]) - Network accessline 942
* Using Service Workers (HTTPS requirement; proxy-like behavior) — `https://developer.mozilla.org/en-US/docs/Web/API/Service_Worker_API/Using_Service_Workers` ([MDN Web Docs][10]) - Network accessline 943
* Secure contexts (powerful APIs restricted to HTTPS) — `https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Secure_Contexts` ([MDN Web Docs][18]) - Network accessline 944
* Link `rel` values (noopener/noreferrer) — `https://developer.mozilla.org/en-US/docs/Web/HTML/Attributes/rel` ([MDN Web Docs][17]) - Network accessline 948
* Create React App env variables warning — `https://create-react-app.dev/docs/adding-custom-environment-variables/` ([create-react-app.dev][1]) - Network accessline 949
* Vite env variables security notes — `https://vite.dev/guide/env-and-mode` ([vitejs][11]) - Network accessline 953
* OAuth 2.0 for Browser-Based Apps (token storage discussion) — `https://datatracker.ietf.org/doc/html/draft-ietf-oauth-browser-based-apps` ([IETF Datatracker][16]) - Network accessline 957
* npm audit docs — `https://docs.npmjs.com/cli/v10/commands/npm-audit/` ([npm Docs][20]) - Network accessline 958
* npm ci docs — `https://docs.npmjs.com/cli/v10/commands/npm-ci/` ([npm Docs][21]) - Network accessline 962
* DOMPurify — `https://github.com/cure53/DOMPurify` ([GitHub][13]) - Network accessline 964
[1]: https://create-react-app.dev/docs/adding-custom-environment-variables/ "Adding Custom Environment Variables | Create React App" - Network accessline 965
[2]: https://cheatsheetseries.owasp.org/cheatsheets/Content_Security_Policy_Cheat_Sheet.html "Content Security Policy - OWASP Cheat Sheet Series" - Network accessline 966
[3]: https://developer.mozilla.org/en-US/docs/Web/API/Trusted_Types_API "Trusted Types API - Web APIs | MDN" - Network accessline 967
[4]: https://cheatsheetseries.owasp.org/cheatsheets/HTML5_Security_Cheat_Sheet.html "HTML5 Security - OWASP Cheat Sheet Series" - Network accessline 968
[5]: https://cheatsheetseries.owasp.org/cheatsheets/Third_Party_Javascript_Management_Cheat_Sheet.html "Third Party Javascript Management - OWASP Cheat Sheet Series" - Network accessline 969
[6]: https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html "Cross-Site Request Forgery Prevention - OWASP Cheat Sheet Series" - Network accessline 970
[7]: https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity "Subresource Integrity - Security | MDN" - Network accessline 971
[8]: https://developer.mozilla.org/en-US/docs/Web/Security/Attacks/Clickjacking "Clickjacking - Security | MDN" - Network accessline 972
[9]: https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html "Cross Site Scripting Prevention - OWASP Cheat Sheet Series" - Network accessline 973
[10]: https://developer.mozilla.org/en-US/docs/Web/API/Service_Worker_API/Using_Service_Workers "Using Service Workers - Web APIs | MDN" - Network accessline 974
[11]: https://vite.dev/guide/env-and-mode "Env Variables and Modes | Vite" - Network accessline 975
[12]: https://react.dev/reference/react-dom/components/common "Common components (e.g. <div>) – React" - Network accessline 976
[13]: https://github.com/cure53/DOMPurify "GitHub - cure53/DOMPurify: DOMPurify - a DOM-only, super-fast, uber-tolerant XSS sanitizer for HTML, MathML and SVG. DOMPurify works with a secure default, but offers a lot of configurability and h - Network accessline 977
[14]: https://legacy.reactjs.org/docs/introducing-jsx.html "Introducing JSX – React" - Network accessline 978
[15]: https://www.w3.org/TR/trusted-types/ "Trusted Types" - Network accessline 979
[16]: https://datatracker.ietf.org/doc/html/draft-ietf-oauth-browser-based-apps " - Network accessline 983
" [17]: https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel "HTML attribute: rel - HTML | MDN" - Network accessline 984
[17]: https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel "HTML attribute: rel - HTML | MDN" - Network accessline 985
[18]: https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Secure_Contexts "Secure contexts - Security | MDN" - Network accessline 986
[19]: https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html "File Upload - OWASP Cheat Sheet Series" - Network accessline 987
[20]: https://docs.npmjs.com/cli/v10/commands/npm-audit "npm-audit | npm Docs" - Network accessline 988
[21]: https://docs.npmjs.com/cli/v10/commands/npm-ci "npm-ci | npm Docs" - Network accessline 989
[22]: https://cheatsheetseries.owasp.org/cheatsheets/NPM_Security_Cheat_Sheet.html "NPM Security - OWASP Cheat Sheet Series" - Network accessline 990
[23]: https://react.dev/blog/2024/12/05/react-19 "React v19 – React"
bundled/skills/security-best-practices/references/javascript-typescript-vue-web-frontend-security.md
- Access to secretsline 186
[Credential-related source omitted] - Access to secretsline 192
[Credential-related source omitted] - Network accessline 503
* `fetch(url, { credentials: 'include', method: 'POST', body: ... })` with no CSRF token/header usage anywhere. - Access to secretsline 533
[Credential-related source omitted] - Network accessline 635
* `<script src="https://cdn.example/...">` with no `integrity`. - Network accessline 640
* Search `index.html` and server templates for `https://` script/style tags. - Access to secretsline 713
[Credential-related source omitted] - Network accessline 753
* Vue Docs: Security — `https://vuejs.org/guide/best-practices/security` ([Vue.js][1]) - Network accessline 754
* Vue Docs: Template Syntax (security warning about in-DOM templates) — `https://vuejs.org/guide/essentials/template-syntax` ([Vue.js][13]) - Network accessline 755
* Vue Docs: Production Deployment — `https://vuejs.org/guide/best-practices/production-deployment` ([Vue.js][3]) - Network accessline 756
* Vue Docs: Feature Flags — `https://link.vuejs.org/feature-flags` ([Vue.js][7]) - Network accessline 760
* Vite Docs: Env Variables and Modes (VITE_* exposure + security notes) — `https://vite.dev/guide/env-and-mode` ([vitejs][2]) - Network accessline 761
* Vite Docs: CLI (`vite preview` not designed for production) — `https://vite.dev/guide/cli` ([vitejs][5]) - Network accessline 762
* Vite Docs: Server Options (`server.host` can listen on public addresses) — `https://vite.dev/config/server-options` ([vitejs][14]) - Network accessline 766
* OWASP Cheat Sheet Series: XSS Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html` ([Vue.js][1]) - Network accessline 767
* OWASP Cheat Sheet Series: CSRF Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][9]) - Network accessline 768
* OWASP Cheat Sheet Series: Authorization — `https://cheatsheetseries.owasp.org/cheatsheets/Authorization_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][8]) - Network accessline 769
* OWASP Cheat Sheet Series: HTTP Headers — `https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][4]) - Network accessline 770
* HTML5 Security Cheat Sheet (referenced by Vue) — `https://html5sec.org/` ([Vue.js][1]) - Network accessline 774
* MDN: `rel="noopener"` — `https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel/noopener` ([MDN Web Docs][12]) - Network accessline 775
* MDN: Subresource Integrity — `https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity` ([MDN Web Docs][11]) - Network accessline 776
* web.dev: Trusted Types — `https://web.dev/trusted-types/` ([web.dev][10]) - Network accessline 778
[1]: https://vuejs.org/guide/best-practices/security "https://vuejs.org/guide/best-practices/security" - Network accessline 779
[2]: https://vite.dev/guide/env-and-mode "https://vite.dev/guide/env-and-mode" - Network accessline 780
[3]: https://vuejs.org/guide/best-practices/production-deployment "https://vuejs.org/guide/best-practices/production-deployment" - Network accessline 781
[4]: https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html" - Network accessline 782
[5]: https://vite.dev/guide/cli "https://vite.dev/guide/cli" - Network accessline 783
[6]: https://vite.dev/guide/build "https://vite.dev/guide/build" - Network accessline 784
[7]: https://vuejs.org/guide/best-practices/production-deployment?utm_source=chatgpt.com "Production Deployment" - Network accessline 785
[8]: https://cheatsheetseries.owasp.org/cheatsheets/Authorization_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Authorization_Cheat_Sheet.html" - Network accessline 786
[9]: https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html" - Network accessline 787
[10]: https://web.dev/articles/trusted-types "https://web.dev/articles/trusted-types" - Network accessline 788
[11]: https://developer.mozilla.org/en-US/docs/Web/Security/Defenses/Subresource_Integrity?utm_source=chatgpt.com "Subresource Integrity - Security - MDN Web Docs" - Network accessline 789
[12]: https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel/noopener "https://developer.mozilla.org/en-US/docs/Web/HTML/Reference/Attributes/rel/noopener" - Network accessline 790
[13]: https://vuejs.org/guide/essentials/template-syntax "Template Syntax | Vue.js" - Network accessline 791
[14]: https://vite.dev/config/server-options "https://vite.dev/config/server-options"
bundled/skills/security-best-practices/references/python-django-web-server-security.md
- Access to secretsline 170
[Credential-related source omitted] - Access to secretsline 199
[Credential-related source omitted] - Network accessline 855
- Django Downloads (current stable & supported branches): https://www.djangoproject.com/download/ - Network accessline 856
- Django 6.0 Release Notes: https://docs.djangoproject.com/en/6.0/releases/6.0/ - Network accessline 857
- Django: Deployment checklist (incl. check --deploy, runserver warning, HTTPS/cookies guidance): https://docs.djangoproject.com/en/6.0/howto/deployment/checklist/ - Network accessline 858
- Django: Settings reference (SecurityMiddleware settings, cookies, SECRET_KEY_FALLBACKS, CSP settings): https://docs.djangoproject.com/en/6.0/ref/settings/ - Network accessline 859
- Django: Security in Django (XSS/CSRF/SQLi/clickjacking/HTTPS/host header validation/uploads/CSP): https://docs.djangoproject.com/en/6.0/topics/security/ - Network accessline 860
- Django: CSRF how-to (middleware, csrf_token usage, AJAX header patterns, csrf_exempt cautions): https://docs.djangoproject.com/en/6.0/howto/csrf/ - Network accessline 861
- Django: Performing raw SQL queries (parameterization guidance): https://docs.djangoproject.com/en/6.0/topics/db/sql/ - Network accessline 862
- Django: QuerySet API reference (extra() cautions; “do not quote placeholders” guidance): https://docs.djangoproject.com/en/6.0/ref/models/querysets/ - Network accessline 863
- Django: Template built-ins (autoescape tag): https://docs.djangoproject.com/en/6.0/ref/templates/builtins/ - Network accessline 864
- Django: Template language reference (turning off autoescape & risks): https://docs.djangoproject.com/en/6.0/ref/templates/language/ - Network accessline 865
- Django: Utilities reference (e.g., format_html): https://docs.djangoproject.com/en/6.0/ref/utils/ - Network accessline 871
- OWASP Cheat Sheet Series: Django Security Cheat Sheet: https://cheatsheetseries.owasp.org/cheatsheets/Django_Security_Cheat_Sheet.html - Network accessline 874
[1]: https://docs.djangoproject.com/en/6.0/howto/deployment/checklist/ "https://docs.djangoproject.com/en/6.0/howto/deployment/checklist/" - Network accessline 875
[2]: https://docs.djangoproject.com/en/6.0/topics/security/ "Security in Django | Django documentation | Django" - Network accessline 876
[3]: https://docs.djangoproject.com/en/6.0/ref/settings/ "Settings | Django documentation | Django" - Network accessline 877
[4]: https://docs.djangoproject.com/en/6.0/howto/csrf/ "How to use Django’s CSRF protection | Django documentation | Django" - Network accessline 878
[5]: https://docs.djangoproject.com/en/6.0/ref/templates/builtins/ "https://docs.djangoproject.com/en/6.0/ref/templates/builtins/" - Network accessline 879
[6]: https://docs.djangoproject.com/en/6.0/ref/utils/ "https://docs.djangoproject.com/en/6.0/ref/utils/" - Network accessline 880
[7]: https://docs.djangoproject.com/en/6.0/topics/db/sql/ "https://docs.djangoproject.com/en/6.0/topics/db/sql/" [8]: https://docs.djangoproject.com/en/6.0/ref/models/querysets/ "https://docs.djangoproject.com/en/6.0/ref/models/querysets/" - Network accessline 881
[8]: https://docs.djangoproject.com/en/6.0/ref/models/querysets/ "https://docs.djangoproject.com/en/6.0/ref/models/querysets/" - Network accessline 882
[9]: https://www.djangoproject.com/download/ "Download Django | Django"
bundled/skills/security-best-practices/references/python-fastapi-web-server-security.md
- Access to secretsline 240
[Credential-related source omitted] - Access to secretsline 245
[Credential-related source omitted] - Network accessline 817
* `httpx.get(request.query_params["url"])` - Access to secretsline 921
[Credential-related source omitted] - Network accessline 968
* FastAPI (PyPI metadata, versioning) — `https://pypi.org/project/fastapi/` ([PyPI][1]) - Network accessline 969
* FastAPI docs: Security “First Steps” (Authorization Bearer header conventions) — `https://fastapi.tiangolo.com/tutorial/security/first-steps/` ([FastAPI][11]) - Network accessline 970
* FastAPI reference: Dependencies (`Depends`, `Security`) — `https://fastapi.tiangolo.com/reference/dependencies/` ([FastAPI][7]) - Network accessline 971
* FastAPI reference: APIRouter (router-level dependencies) — `https://fastapi.tiangolo.com/reference/apirouter/` ([FastAPI][28]) - Network accessline 972
* FastAPI docs: WebSockets — `https://fastapi.tiangolo.com/advanced/websockets/` ([FastAPI][27]) - Network accessline 976
* Starlette (PyPI, general capabilities) — `https://pypi.org/project/starlette/` ([PyPI][5]) - Network accessline 977
* Starlette docs: WebSockets — `https://starlette.dev/websockets/` ([Starlette][3]) - Network accessline 978
* Uvicorn (PyPI metadata) — `https://pypi.org/project/uvicorn/` ([PyPI][4]) - Network accessline 979
* Pydantic docs (v2.12.x) — `https://docs.pydantic.dev/latest/` ([Pydantic][29]) - Network accessline 983
* OWASP Cheat Sheet Series: Session Management — `https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][8]) - Network accessline 984
* OWASP Cheat Sheet Series: CSRF Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][2]) - Network accessline 985
* OWASP Cheat Sheet Series: XSS Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][16]) - Network accessline 986
* OWASP Cheat Sheet Series: Mass Assignment — `https://cheatsheetseries.owasp.org/cheatsheets/Mass_Assignment_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][14]) - Network accessline 987
* OWASP API Security Top 10 (2023) — `https://owasp.org/API-Security/editions/2023/en/0x11-t10/` ([OWASP Foundation][13]) - Network accessline 988
* OWASP Cheat Sheet Series: SQL Injection Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][21]) - Network accessline 989
* OWASP Cheat Sheet Series: OS Command Injection Defense — `https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][22]) - Network accessline 990
* OWASP Cheat Sheet Series: SSRF Prevention — `https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][23]) - Network accessline 991
* OWASP Cheat Sheet Series: File Upload — `https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][20]) - Network accessline 992
* OWASP Cheat Sheet Series: Unvalidated Redirects and Forwards — `https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][24]) - Network accessline 993
* OWASP Cheat Sheet Series: HTTP Security Response Headers — `https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][6]) - Network accessline 994
* OWASP Cheat Sheet Series: WebSocket Security — `https://cheatsheetseries.owasp.org/cheatsheets/WebSocket_Security_Cheat_Sheet.html` ([OWASP Cheat Sheet Series][25]) - Network accessline 995
* OWASP WSTG: Testing for Server-Side Template Injection — `https://owasp.org/www-project-web-security-testing-guide/v41/4-Web_Application_Security_Testing/07-Input_Validation_Testing/18-Testing_for_Server_Side_Template_Injection` ([OWASP F - Network accessline 996
* OWASP WSTG: Testing WebSockets — `https://owasp.org/www-project-web-security-testing-guide/latest/4-Web_Application_Security_Testing/11-Client-side_Testing/10-Testing_WebSockets` ([OWASP Foundation][26]) - Network accessline 1000
* Jinja: Sandbox — `https://jinja.palletsprojects.com/en/stable/sandbox/` ([jinja.palletsprojects.com][18]) - Network accessline 1004
* CVE-2023-29159 (StaticFiles path traversal; fixed 0.27.0) — `https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2023-29159/` ([advisories.gitlab.com][10]) - Network accessline 1005
* CVE-2024-47874 (multipart/form-data DoS; fixed 0.40.0) — `https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2024-47874/` ([advisories.gitlab.com][9]) - Network accessline 1006
* CVE-2025-62727 (FileResponse Range header DoS; fixed 0.49.1) — `https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2025-62727/` ([advisories.gitlab.com][19]) - Network accessline 1008
[1]: https://pypi.org/project/fastapi/ "https://pypi.org/project/fastapi/" - Network accessline 1009
[2]: https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html" - Network accessline 1010
[3]: https://starlette.dev/websockets/?utm_source=chatgpt.com "Websockets" - Network accessline 1011
[4]: https://pypi.org/project/uvicorn/ "https://pypi.org/project/uvicorn/" - Network accessline 1012
[5]: https://pypi.org/project/starlette/ "https://pypi.org/project/starlette/" - Network accessline 1013
[6]: https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html?utm_source=chatgpt.com "HTTP Security Response Headers Cheat Sheet" - Network accessline 1014
[7]: https://fastapi.tiangolo.com/reference/dependencies/?utm_source=chatgpt.com "Dependencies - Depends() and Security() - FastAPI" - Network accessline 1015
[8]: https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html" - Network accessline 1016
[9]: https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2024-47874/ "Starlette Denial of service (DoS) via multipart/form-data | GitLab Advisory Database" - Network accessline 1017
[10]: https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2023-29159/ "Starlette has Path Traversal vulnerability in StaticFiles | GitLab Advisory Database" - Network accessline 1018
[11]: https://fastapi.tiangolo.com/tutorial/security/first-steps/?utm_source=chatgpt.com "Security - First Steps - FastAPI" - Network accessline 1019
[12]: https://fastapi.tiangolo.com/tutorial/response-model/ "https://fastapi.tiangolo.com/tutorial/response-model/" - Network accessline 1020
[13]: https://owasp.org/API-Security/editions/2023/en/0x11-t10/ "https://owasp.org/API-Security/editions/2023/en/0x11-t10/" - Network accessline 1021
[14]: https://cheatsheetseries.owasp.org/cheatsheets/Mass_Assignment_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Mass_Assignment_Cheat_Sheet.html" - Network accessline 1022
[15]: https://fastapi.tiangolo.com/tutorial/extra-models/ "https://fastapi.tiangolo.com/tutorial/extra-models/" - Network accessline 1023
[16]: https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html" - Network accessline 1024
[17]: https://owasp.org/www-project-web-security-testing-guide/v41/4-Web_Application_Security_Testing/07-Input_Validation_Testing/18-Testing_for_Server_Side_Template_Injection?utm_source=chatgpt.com "Testing for Server Side Template Injecti - Network accessline 1025
[18]: https://jinja.palletsprojects.com/en/stable/sandbox/?utm_source=chatgpt.com "Sandbox — Jinja Documentation (3.1.x)" - Network accessline 1026
[19]: https://advisories.gitlab.com/pkg/pypi/starlette/CVE-2025-62727/ "Starlette vulnerable to O(n^2) DoS via Range header merging in ``starlette.responses.FileResponse`` | GitLab Advisory Database" - Network accessline 1027
[20]: https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html" - Network accessline 1028
[21]: https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html" - Network accessline 1029
[22]: https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html" - Network accessline 1030
[23]: https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html "https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html" - Network accessline 1031
[24]: https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html?utm_source=chatgpt.com "Unvalidated Redirects and Forwards Cheat Sheet" - Network accessline 1032
[25]: https://cheatsheetseries.owasp.org/cheatsheets/WebSocket_Security_Cheat_Sheet.html?utm_source=chatgpt.com "WebSocket Security - OWASP Cheat Sheet Series" - Network accessline 1033
[26]: https://owasp.org/www-project-web-security-testing-guide/latest/4-Web_Application_Security_Testing/11-Client-side_Testing/10-Testing_WebSockets?utm_source=chatgpt.com "WSTG - Latest | OWASP Foundation" - Network accessline 1034
[27]: https://fastapi.tiangolo.com/advanced/websockets/?utm_source=chatgpt.com "WebSockets - FastAPI" - Network accessline 1035
[28]: https://fastapi.tiangolo.com/reference/apirouter/?utm_source=chatgpt.com "APIRouter class - FastAPI" - Network accessline 1036
[29]: https://docs.pydantic.dev/latest/ "https://docs.pydantic.dev/latest/"
bundled/skills/security-best-practices/references/python-flask-web-server-security.md
- Network accessline 536
Insecure patterns: - `requests.get(request.args["url"])` - Network accessline 537
- `requests.get(request.args["url"])` - Network accessline 674
Primary framework documentation: - Flask Docs: Deploying to Production — https://flask.palletsprojects.com/en/stable/deploying/ - Network accessline 675
- Flask Docs: Deploying to Production — https://flask.palletsprojects.com/en/stable/deploying/ - Network accessline 676
- Flask Docs: Debugging Application Errors — https://flask.palletsprojects.com/en/stable/debugging/ - Network accessline 677
- Flask Docs: Configuration Handling — https://flask.palletsprojects.com/en/stable/config/ - Network accessline 678
- Flask Docs: Security Considerations — https://flask.palletsprojects.com/en/stable/web-security/ - Network accessline 679
- Flask Docs: Tell Flask it is Behind a Proxy — https://flask.palletsprojects.com/en/stable/deploying/proxy_fix/ - Network accessline 680
- Flask API Docs: Sessions — https://flask.palletsprojects.com/en/stable/api/#sessions - Network accessline 682
Werkzeug documentation & advisories: - Werkzeug Docs: Utilities (send_file / send_from_directory / safe_join / secure_filename / password hashing) — https://werkzeug.palletsprojects.com/en/stable/utils/ - Network accessline 683
- Werkzeug Docs: Utilities (send_file / send_from_directory / safe_join / secure_filename / password hashing) — https://werkzeug.palletsprojects.com/en/stable/utils/ - Network accessline 684
- GitHub Advisory: CVE-2025-66221 (Werkzeug safe_join Windows device names) — https://github.com/advisories/GHSA-hgf8-39gv-g3f2 - Network accessline 686
OWASP Cheat Sheet Series: - Session Management — https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html - Network accessline 687
- Session Management — https://cheatsheetseries.owasp.org/cheatsheets/Session_Management_Cheat_Sheet.html - Network accessline 688
- CSRF Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html - Network accessline 689
- XSS Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Cross_Site_Scripting_Prevention_Cheat_Sheet.html - Network accessline 690
- Input Validation — https://cheatsheetseries.owasp.org/cheatsheets/Input_Validation_Cheat_Sheet.html - Network accessline 691
- SQL Injection Prevention — https://cheatsheetseries.owasp.org/cheatsheets/SQL_Injection_Prevention_Cheat_Sheet.html - Network accessline 692
- Injection Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Injection_Prevention_Cheat_Sheet.html - Network accessline 693
- OS Command Injection Defense — https://cheatsheetseries.owasp.org/cheatsheets/OS_Command_Injection_Defense_Cheat_Sheet.html - Network accessline 694
- SSRF Prevention — https://cheatsheetseries.owasp.org/cheatsheets/Server_Side_Request_Forgery_Prevention_Cheat_Sheet.html - Network accessline 695
- File Upload — https://cheatsheetseries.owasp.org/cheatsheets/File_Upload_Cheat_Sheet.html - Network accessline 696
- Unvalidated Redirects — https://cheatsheetseries.owasp.org/cheatsheets/Unvalidated_Redirects_and_Forwards_Cheat_Sheet.html - Network accessline 697
- HTTP Headers — https://cheatsheetseries.owasp.org/cheatsheets/HTTP_Headers_Cheat_Sheet.html - Network accessline 699
Template safety references: - Jinja: Sandbox (rendering untrusted templates) — https://jinja.palletsprojects.com/en/stable/sandbox/ - Network accessline 700
- Jinja: Sandbox (rendering untrusted templates) — https://jinja.palletsprojects.com/en/stable/sandbox/ - Network accessline 701
- OWASP WSTG: Testing for Server-Side Template Injection — https://owasp.org/www-project-web-security-testing-guide/v41/4-Web_Application_Security_Testing/07-Input_Validation_Testing/18-Testing_for_Server_Side_Template_Injection - Network accessline 702
- PortSwigger Web Security Academy: Server-side template injection — https://portswigger.net/web-security/server-side-template-injection - Network accessline 704
HTTP semantics: - RFC 9110: HTTP Semantics (safe methods) — https://www.rfc-editor.org/rfc/rfc9110 - Network accessline 705
- RFC 9110: HTTP Semantics (safe methods) — https://www.rfc-editor.org/rfc/rfc9110
bundled/skills/security-ownership-map/LICENSE.txt
bundled/skills/security-ownership-map/scripts/build_ownership_map.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/security-ownership-map/scripts/community_maintainers.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/security-ownership-map/scripts/query_ownership.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/security-ownership-map/scripts/run_ownership_map.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/security-threat-model/LICENSE.txt
bundled/skills/senior-computer-vision/scripts/dataset_pipeline_builder.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-computer-vision/scripts/inference_optimizer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-computer-vision/scripts/vision_model_trainer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-data-scientist/scripts/experiment_designer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-data-scientist/scripts/feature_engineering_pipeline.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-data-scientist/scripts/model_evaluation_suite.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-ml-engineer/scripts/ml_monitoring_suite.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-ml-engineer/scripts/model_deployment_pipeline.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-ml-engineer/scripts/rag_system_builder.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-prompt-engineer/scripts/agent_orchestrator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-prompt-engineer/scripts/prompt_optimizer.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/senior-prompt-engineer/scripts/rag_evaluator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/sentry/LICENSE.txt
bundled/skills/sentry/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 11
[Credential-related source omitted] - Access to secretsline 12
[Credential-related source omitted] - Network accessline 17
[Credential-related source omitted] - Network accessline 18
[Credential-related source omitted] - Access to secretsline 20
[Credential-related source omitted]
bundled/skills/sentry/assets/sentry-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 50 44" fill="currentColor" aria-hidden="true">
bundled/skills/sentry/scripts/sentry_api.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 12
DEFAULT_BASE_URL = "https://sentry.io" - Network accessline 160
"--base-url", default=os.environ.get("SENTRY_BASE_URL", DEFAULT_BASE_URL), help="Sentry base URL (default: https://sentry.io)", - Network accessline 161
[Credential-related source omitted] - Access to secretsline 161
[Credential-related source omitted] - Network accessline 162
help="Sentry base URL (default: https://sentry.io)", - Access to secretsline 166
[Credential-related source omitted] - Access to secretsline 171
[Credential-related source omitted] - Access to secretsline 210
[Credential-related source omitted] - Access to secretsline 212
[Credential-related source omitted]
bundled/skills/shap/SKILL.md
bundled/skills/similarity-search-patterns/SKILL.md
- Access to secretsline 57
[Credential-related source omitted] - Access to secretsline 62
[Credential-related source omitted] - Network accessline 376
async with self.pool.acquire() as conn: rows = await conn.fetch(query, *params) - Network accessline 377
rows = await conn.fetch(query, *params) - Network accessline 396
"""Hybrid search combining vector and full-text.""" async with self.pool.acquire() as conn: rows = await conn.fetch( - Network accessline 397
async with self.pool.acquire() as conn: rows = await conn.fetch( """ - Network accessline 398
rows = await conn.fetch( - Network accessline 440
def __init__( self, url: str = "http://localhost:8080", - Network accessline 441
self, url: str = "http://localhost:8080", class_name: str = "Document" - Network accessline 442
url: str = "http://localhost:8080", - Network accessline 555
- [Pinecone Docs](https://docs.pinecone.io/) - Network accessline 556
- [Qdrant Docs](https://qdrant.tech/documentation/) - Network accessline 557
- [pgvector](https://github.com/pgvector/pgvector) - Network accessline 558
- [Weaviate Docs](https://weaviate.io/developers/weaviate)
bundled/skills/simpy/scripts/basic_simulation_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/simpy/scripts/resource_monitor.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/skill-creator/scripts/init_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/skill-creator/scripts/package_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/skill-creator/scripts/quick_validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/skypilot-multi-cloud-orchestration/SKILL.md
- Access to secretsline 409
[Credential-related source omitted] - Access to secretsline 410
[Credential-related source omitted] - Access to secretsline 415
[Credential-related source omitted] - Network accessline 506
- **Documentation**: https://docs.skypilot.co - Network accessline 507
- **GitHub**: https://github.com/skypilot-org/skypilot - Network accessline 508
- **Slack**: https://slack.skypilot.co - Network accessline 509
- **Examples**: https://github.com/skypilot-org/skypilot/tree/master/examples
bundled/skills/skypilot-multi-cloud-orchestration/references/advanced-usage.md
- Network accessline 108
workdir: url: https://github.com/user/repo.git - Network accessline 109
url: https://github.com/user/repo.git - Access to secretsline 145
[Credential-related source omitted] - Network accessline 237
# Test new version curl https://my-service-v2.skypilot.cloud/health - Network accessline 238
curl https://my-service-v2.skypilot.cloud/health - Network accessline 349
# Connect clients sky api login --endpoint https://your-server:8000 - Network accessline 350
sky api login --endpoint https://your-server:8000 - Access to secretsline 360
[Credential-related source omitted] - Access to secretsline 408
[Credential-related source omitted] - Access to secretsline 413
[Credential-related source omitted] - Access to secretsline 447
[Credential-related source omitted] - Access to secretsline 451
[Credential-related source omitted]
bundled/skills/skypilot-multi-cloud-orchestration/references/troubleshooting.md
- Network accessline 179
setup: | # Install specific CUDA version pip install torch==2.1.0+cu121 -f https://download.pytorch.org/whl/torch_stable.html - Network accessline 181
pip install torch==2.1.0+cu121 -f https://download.pytorch.org/whl/torch_stable.html - Access to secretsline 439
[Credential-related source omitted] - Network accessline 557
1. **Documentation**: https://docs.skypilot.co - Network accessline 558
2. **GitHub Issues**: https://github.com/skypilot-org/skypilot/issues - Network accessline 559
3. **Slack**: https://slack.skypilot.co - Network accessline 560
4. **Examples**: https://github.com/skypilot-org/skypilot/tree/master/examples
bundled/skills/slides-as-code/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/smart-file-writer/references/diagnostic-procedures.md
bundled/skills/smart-file-writer/references/index.md
- Network accessline 44
- [Python os module](https://docs.python.org/3/library/os.html) - Network accessline 45
- [Python shutil module](https://docs.python.org/3/library/shutil.html) - Network accessline 46
- [Windows File System Limits](https://docs.microsoft.com/en-us/windows/win32/fileio/maximum-file-path-limitation) - Network accessline 47
- [POSIX File Permissions](https://pubs.opengroup.org/onlinepubs/9699919799/basedefs/sys_stat.h.html)
bundled/skills/smart-file-writer/references/platform-specific.md
bundled/skills/smart-file-writer/scripts/validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/sparse-autoencoder-training/SKILL.md
- Network accessline 15
**GitHub**: [jbloomAus/SAELens](https://github.com/jbloomAus/SAELens) (1,100+ stars) - Network accessline 327
Browse pre-trained SAE features at [neuronpedia.org](https://neuronpedia.org): - Network accessline 357
### Tutorials - [Basic Loading & Analysis](https://github.com/jbloomAus/SAELens/blob/main/tutorials/basic_loading_and_analysing.ipynb) - Network accessline 358
- [Basic Loading & Analysis](https://github.com/jbloomAus/SAELens/blob/main/tutorials/basic_loading_and_analysing.ipynb) - Network accessline 359
- [Training a Sparse Autoencoder](https://github.com/jbloomAus/SAELens/blob/main/tutorials/training_a_sparse_autoencoder.ipynb) - Network accessline 360
- [ARENA SAE Curriculum](https://www.lesswrong.com/posts/LnHowHgmrMbWtpkxx/intro-to-superposition-and-sparse-autoencoders-colab) - Network accessline 362
### Papers - [Towards Monosemanticity](https://transformer-circuits.pub/2023/monosemantic-features) - Anthropic (2023) - Network accessline 363
- [Towards Monosemanticity](https://transformer-circuits.pub/2023/monosemantic-features) - Anthropic (2023) - Network accessline 364
- [Scaling Monosemanticity](https://transformer-circuits.pub/2024/scaling-monosemanticity/) - Anthropic (2024) - Network accessline 365
- [Sparse Autoencoders Find Highly Interpretable Features](https://arxiv.org/abs/2309.08600) - Cunningham et al. (ICLR 2024) - Network accessline 367
### Official Documentation - [SAELens Docs](https://jbloomaus.github.io/SAELens/) - Network accessline 368
- [SAELens Docs](https://jbloomaus.github.io/SAELens/) - Network accessline 369
- [Neuronpedia](https://neuronpedia.org) - Feature browser
bundled/skills/sparse-autoencoder-training/references/README.md
bundled/skills/sparse-autoencoder-training/references/tutorials.md
- Network accessline 307
### Official Tutorials - [Basic Loading & Analysis](https://github.com/jbloomAus/SAELens/blob/main/tutorials/basic_loading_and_analysing.ipynb) - Network accessline 308
- [Basic Loading & Analysis](https://github.com/jbloomAus/SAELens/blob/main/tutorials/basic_loading_and_analysing.ipynb) - Network accessline 309
- [Training SAEs](https://github.com/jbloomAus/SAELens/blob/main/tutorials/training_a_sparse_autoencoder.ipynb) - Network accessline 310
- [Logits Lens with Features](https://github.com/jbloomAus/SAELens/blob/main/tutorials/logits_lens_with_features.ipynb) - Network accessline 312
### ARENA Curriculum Comprehensive SAE course: https://www.lesswrong.com/posts/LnHowHgmrMbWtpkxx/intro-to-superposition-and-sparse-autoencoders-colab - Network accessline 313
Comprehensive SAE course: https://www.lesswrong.com/posts/LnHowHgmrMbWtpkxx/intro-to-superposition-and-sparse-autoencoders-colab - Network accessline 315
### Key Papers - [Towards Monosemanticity](https://transformer-circuits.pub/2023/monosemantic-features) - Anthropic (2023) - Network accessline 316
- [Towards Monosemanticity](https://transformer-circuits.pub/2023/monosemantic-features) - Anthropic (2023) - Network accessline 317
- [Scaling Monosemanticity](https://transformer-circuits.pub/2024/scaling-monosemanticity/) - Anthropic (2024) - Network accessline 318
- [Sparse Autoencoders Find Interpretable Features](https://arxiv.org/abs/2309.08600) - ICLR 2024
bundled/skills/spec-kit-vibe-compat/scripts/speckit-router.ps1
- Executable scriptline 1
Executable file
bundled/skills/speech/LICENSE.txt
bundled/skills/speech/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 47
[Credential-related source omitted] - Network accessline 49
If the key is missing, give the user these steps: 1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Network accessline 50
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted]
bundled/skills/speech/assets/speech-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
bundled/skills/speech/references/cli.md
bundled/skills/speech/scripts/text_to_speech.py
bundled/skills/splitting-datasets/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
bundled/skills/splitting-datasets/assets/dataset_schema.json
- Network accessline 1
{ "_comment": "This JSON schema defines the expected structure for a dataset to be split.", "$schema": "http://json-schema.org/draft-07/schema#", - Network accessline 2
"_comment": "This JSON schema defines the expected structure for a dataset to be split.", "$schema": "http://json-schema.org/draft-07/schema#", "title": "Dataset Schema", - Network accessline 3
"$schema": "http://json-schema.org/draft-07/schema#",
bundled/skills/splitting-datasets/scripts/split_data.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/spreadsheet/LICENSE.txt
bundled/skills/spreadsheet/SKILL.md
- Dangerous shell operationline 65
sudo apt-get install -y libreoffice poppler-utils
bundled/skills/spreadsheet/assets/spreadsheet-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
bundled/skills/spreadsheet/references/examples/openpyxl/create_basic_spreadsheet.py
- Executable scriptline 1
Executable file
bundled/skills/spreadsheet/references/examples/openpyxl/create_spreadsheet_with_styling.py
- Executable scriptline 1
Executable file
bundled/skills/spreadsheet/references/examples/openpyxl/read_existing_spreadsheet.py
- Executable scriptline 1
Executable file
bundled/skills/spreadsheet/references/examples/openpyxl/styling_spreadsheet.py
- Executable scriptline 1
Executable file
bundled/skills/stable-baselines3/references/algorithms.md
- Network accessline 330
- **RL Baselines3 Zoo**: Collection of pre-trained agents and hyperparameters: https://github.com/DLR-RM/rl-baselines3-zoo
bundled/skills/stable-baselines3/references/callbacks.md
- Network accessline 554
- Official SB3 Callbacks Guide: https://stable-baselines3.readthedocs.io/en/master/guide/callbacks.html - Network accessline 555
- Callback API Reference: https://stable-baselines3.readthedocs.io/en/master/common/callbacks.html - Network accessline 556
- TensorBoard Documentation: https://www.tensorflow.org/tensorboard
bundled/skills/stable-baselines3/references/custom_environments.md
- Network accessline 524
- Template: See `scripts/custom_env_template.py` - Gymnasium Documentation: https://gymnasium.farama.org/ - Network accessline 525
- Gymnasium Documentation: https://gymnasium.farama.org/ - Network accessline 526
- SB3 Custom Env Guide: https://stable-baselines3.readthedocs.io/en/master/guide/custom_env.html
bundled/skills/stable-baselines3/references/vectorized_envs.md
- Network accessline 566
- Official SB3 VecEnv Guide: https://stable-baselines3.readthedocs.io/en/master/guide/vec_envs.html - Network accessline 567
- VecEnv API Reference: https://stable-baselines3.readthedocs.io/en/master/common/vec_env.html - Network accessline 568
- Multiprocessing Best Practices: https://docs.python.org/3/library/multiprocessing.html
bundled/skills/stable-baselines3/scripts/custom_env_template.py
- Executable scriptline 1
Executable file
bundled/skills/stable-baselines3/scripts/evaluate_agent.py
- Executable scriptline 1
Executable file
bundled/skills/stable-baselines3/scripts/train_rl_agent.py
- Executable scriptline 1
Executable file
bundled/skills/statistical-analysis/SKILL.md
bundled/skills/statistical-analysis/references/reporting_standards.md
bundled/skills/statistical-analysis/scripts/assumption_checks.py
- Executable scriptline 1
Executable file
bundled/skills/statistics-math/SKILL.md
bundled/skills/statistics-math/assets/schema.json
bundled/skills/statistics-math/scripts/validate.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/statsmodels/SKILL.md
- Network accessline 604
For detailed documentation and examples: - Official docs: https://www.statsmodels.org/stable/ - Network accessline 605
- Official docs: https://www.statsmodels.org/stable/ - Network accessline 606
- User guide: https://www.statsmodels.org/stable/user-guide.html - Network accessline 607
- Examples: https://www.statsmodels.org/stable/examples/index.html - Network accessline 608
- API reference: https://www.statsmodels.org/stable/api.html
bundled/skills/structured-content-storage/assets/templates/CHANGELOG-template.md
bundled/skills/submission-checklist/SKILL.md
- Broad permissionsline 1
Bash
bundled/skills/sympy/SKILL.md
- Network accessline 491
- Official Documentation: https://docs.sympy.org/ - Network accessline 492
- Tutorial: https://docs.sympy.org/latest/tutorials/intro-tutorial/index.html - Network accessline 493
- API Reference: https://docs.sympy.org/latest/reference/index.html - Network accessline 494
- Examples: https://github.com/sympy/sympy/tree/master/examples
bundled/skills/sympy/references/code-generation-printing.md
- Dangerous shell operationline 205
# This can be eval()'ed to recreate the expression
bundled/skills/systematic-debugging/SKILL.md
bundled/skills/systematic-debugging/condition-based-waiting-example.ts
- Executable scriptline 1
Executable file
bundled/skills/systematic-debugging/find-polluter.sh
- Executable scriptline 1
#!/usr/bin/env bash
bundled/skills/tensorboard/SKILL.md
- Network accessline 39
# Launch TensorBoard tensorboard --logdir=runs # Access at http://localhost:6006 - Network accessline 41
# Access at http://localhost:6006 - Network accessline 618
- **Documentation**: https://www.tensorflow.org/tensorboard - Network accessline 619
- **PyTorch Integration**: https://pytorch.org/docs/stable/tensorboard.html - Network accessline 620
- **GitHub**: https://github.com/tensorflow/tensorboard (27k+ stars) - Network accessline 621
- **TensorBoard.dev**: https://tensorboard.dev (share experiments publicly)
bundled/skills/tensorboard/references/integrations.md
- Network accessline 634
- **PyTorch**: https://pytorch.org/docs/stable/tensorboard.html - Network accessline 635
- **TensorFlow**: https://www.tensorflow.org/tensorboard - Network accessline 636
- **Lightning**: https://pytorch-lightning.readthedocs.io/en/stable/extensions/logging.html - Network accessline 637
- **Transformers**: https://huggingface.co/docs/transformers/main_classes/trainer - Network accessline 638
- **Fast.ai**: https://docs.fast.ai/callback.tensorboard.html
bundled/skills/tensorboard/references/profiling.md
- Network accessline 542
- **PyTorch Profiler**: https://pytorch.org/tutorials/recipes/recipes/profiler_recipe.html - Network accessline 543
- **TensorFlow Profiler**: https://www.tensorflow.org/guide/profiler - Network accessline 544
- **NVIDIA Nsight**: https://developer.nvidia.com/nsight-systems - Network accessline 545
- **PyTorch Bottleneck**: https://pytorch.org/docs/stable/bottleneck.html
bundled/skills/tensorboard/references/visualization.md
- Network accessline 618
- **TensorBoard Documentation**: https://www.tensorflow.org/tensorboard - Network accessline 619
- **PyTorch TensorBoard**: https://pytorch.org/docs/stable/tensorboard.html - Network accessline 620
- **Projector Guide**: https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin
bundled/skills/theme-factory/LICENSE.txt
bundled/skills/tiledbvcf/SKILL.md
- Network accessline 310
**Open Source Documentation:** - TileDB Academy: https://cloud.tiledb.com/academy/ - Network accessline 311
- TileDB Academy: https://cloud.tiledb.com/academy/ - Network accessline 312
- Population Genomics Guide: https://cloud.tiledb.com/academy/structure/life-sciences/population-genomics/ - Network accessline 313
- TileDB-VCF GitHub: https://github.com/TileDB-Inc/TileDB-VCF - Network accessline 317
**For Large-Scale/Production Genomics:** - TileDB-Cloud Platform: https://cloud.tiledb.com - Network accessline 318
- TileDB-Cloud Platform: https://cloud.tiledb.com - Network accessline 319
- TileDB Academy (All Documentation): https://cloud.tiledb.com/academy/ - Network accessline 321
**Getting Started:** - Free account signup: https://cloud.tiledb.com - Network accessline 322
- Free account signup: https://cloud.tiledb.com - Network accessline 335
# Sign up at https://cloud.tiledb.com - Access to secretsline 351
[Credential-related source omitted] - Network accessline 452
**Next Steps:** - Visit https://cloud.tiledb.com to create account - Network accessline 453
- Visit https://cloud.tiledb.com to create account - Network accessline 454
- Review documentation at https://cloud.tiledb.com/academy/
bundled/skills/timesfm-forecasting/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Network accessline 147
# CUDA 12.1 (NVIDIA GPU) pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cu121 - Network accessline 148
pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cu121 - Network accessline 150
# CPU only pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cpu - Network accessline 151
pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cpu - Network accessline 693
- **Paper**: [A Decoder-Only Foundation Model for Time-Series Forecasting](https://arxiv.org/abs/2310.10688) (ICML 2024) - Network accessline 694
- **Repository**: https://github.com/google-research/timesfm - Network accessline 695
- **Hugging Face**: https://huggingface.co/collections/google/timesfm-release-66e4be5fdb56e960c1e482a6 - Network accessline 696
- **Google Blog**: https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ - Network accessline 697
- **BigQuery Integration**: https://cloud.google.com/bigquery/docs/timesfm-model
bundled/skills/timesfm-forecasting/examples/anomaly-detection/detect_anomalies.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/timesfm-forecasting/examples/covariates-forecasting/demo_covariates.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 20
import tempfile, urllib.request tmp = tempfile.mkdtemp(prefix="timesfm_retail_") # urllib.request.urlretrieve("https://...store_sales.csv", f"{tmp}/store_sales.csv") - Network accessline 21
tmp = tempfile.mkdtemp(prefix="timesfm_retail_") # urllib.request.urlretrieve("https://...store_sales.csv", f"{tmp}/store_sales.csv") # df = pd.read_csv(f"{tmp}/store_sales.csv") - Network accessline 22
# urllib.request.urlretrieve("https://...store_sales.csv", f"{tmp}/store_sales.csv")
bundled/skills/timesfm-forecasting/examples/global-temperature/generate_animation_data.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/timesfm-forecasting/examples/global-temperature/generate_gif.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/timesfm-forecasting/examples/global-temperature/generate_html.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 23
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>TimesFM Interactive Forecast Animation</title> <script src="https://cdn.jsdelivr.net/npm/chart.js"></script> - Network accessline 24
<title>TimesFM Interactive Forecast Animation</title> <script src="https://cdn.jsdelivr.net/npm/chart.js"></script> <style> - Network accessline 25
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script> - Network accessline 218
<footer> <p>TimesFM 1.0 (200M) PyTorch • <a href="https://github.com/google-research/timesfm">Google Research</a></p> - Network accessline 219
<p>TimesFM 1.0 (200M) PyTorch • <a href="https://github.com/google-research/timesfm">Google Research</a></p>
bundled/skills/timesfm-forecasting/examples/global-temperature/run_example.sh
- Executable scriptline 1
#!/bin/bash
bundled/skills/timesfm-forecasting/examples/global-temperature/run_forecast.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/timesfm-forecasting/examples/global-temperature/visualize_forecast.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/timesfm-forecasting/scripts/check_system.py
bundled/skills/timesfm-forecasting/scripts/forecast_csv.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/torch-geometric/SKILL.md
- Network accessline 43
uv pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html - Network accessline 677
- **Documentation**: https://pytorch-geometric.readthedocs.io/ - Network accessline 678
- **GitHub**: https://github.com/pyg-team/pytorch_geometric - Network accessline 679
- **Tutorials**: https://pytorch-geometric.readthedocs.io/en/latest/get_started/introduction.html - Network accessline 680
- **Examples**: https://github.com/pyg-team/pytorch_geometric/tree/master/examples
bundled/skills/torch-geometric/scripts/benchmark_model.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/torch-geometric/scripts/create_gnn_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/torch-geometric/scripts/visualize_graph.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/torchdrug/SKILL.md
bundled/skills/transcribe/LICENSE.txt
bundled/skills/transcribe/SKILL.md
bundled/skills/transcribe/assets/transcribe-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" viewBox="0 0 20 20">
bundled/skills/transcribe/scripts/transcribe_diarize.py
bundled/skills/transformer-lens-interpretability/SKILL.md
- Network accessline 15
**GitHub**: [TransformerLensOrg/TransformerLens](https://github.com/TransformerLensOrg/TransformerLens) (2,900+ stars) - Network accessline 41
pip install git+https://github.com/TransformerLensOrg/TransformerLens - Access to secretsline 58
[Credential-related source omitted] - Network accessline 328
### Tutorials - [Main Demo Notebook](https://transformerlensorg.github.io/TransformerLens/generated/demos/Main_Demo.html) - Network accessline 329
- [Main Demo Notebook](https://transformerlensorg.github.io/TransformerLens/generated/demos/Main_Demo.html) - Network accessline 330
- [Activation Patching Demo](https://colab.research.google.com/github/TransformerLensOrg/TransformerLens/blob/main/demos/Activation_Patching_in_TL_Demo.ipynb) - Network accessline 331
- [ARENA Mech Interp Course](https://arena-foundation.github.io/ARENA/) - 200+ hours of tutorials - Network accessline 333
### Papers - [A Mathematical Framework for Transformer Circuits](https://transformer-circuits.pub/2021/framework/index.html) - Network accessline 334
- [A Mathematical Framework for Transformer Circuits](https://transformer-circuits.pub/2021/framework/index.html) - Network accessline 335
- [In-context Learning and Induction Heads](https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html) - Network accessline 336
- [Interpretability in the Wild (IOI)](https://arxiv.org/abs/2211.00593) - Network accessline 338
### Official Documentation - [Official Docs](https://transformerlensorg.github.io/TransformerLens/) - Network accessline 339
- [Official Docs](https://transformerlensorg.github.io/TransformerLens/) - Network accessline 340
- [Model Properties Table](https://transformerlensorg.github.io/TransformerLens/generated/model_properties_table.html) - Network accessline 341
- [Neel Nanda's Glossary](https://www.neelnanda.io/mechanistic-interpretability/glossary)
bundled/skills/transformer-lens-interpretability/references/README.md
- Network accessline 13
- **Official Documentation**: https://transformerlensorg.github.io/TransformerLens/ - Network accessline 14
- **GitHub Repository**: https://github.com/TransformerLensOrg/TransformerLens - Network accessline 15
- **Model Properties Table**: https://transformerlensorg.github.io/TransformerLens/generated/model_properties_table.html
bundled/skills/transformer-lens-interpretability/references/api.md
- Access to secretsline 24
[Credential-related source omitted]
bundled/skills/transformer-lens-interpretability/references/tutorials.md
- Network accessline 328
### Official Tutorials - [Main Demo](https://transformerlensorg.github.io/TransformerLens/generated/demos/Main_Demo.html) - Network accessline 329
- [Main Demo](https://transformerlensorg.github.io/TransformerLens/generated/demos/Main_Demo.html) - Network accessline 330
- [Exploratory Analysis](https://transformerlensorg.github.io/TransformerLens/generated/demos/Exploratory_Analysis_Demo.html) - Network accessline 331
- [Activation Patching Demo](https://colab.research.google.com/github/TransformerLensOrg/TransformerLens/blob/main/demos/Activation_Patching_in_TL_Demo.ipynb) - Network accessline 333
### ARENA Course Comprehensive 200+ hour curriculum: https://arena-foundation.github.io/ARENA/ - Network accessline 334
Comprehensive 200+ hour curriculum: https://arena-foundation.github.io/ARENA/ - Network accessline 336
### Neel Nanda's Resources - [Getting Started in Mech Interp](https://www.neelnanda.io/mechanistic-interpretability/getting-started) - Network accessline 337
- [Getting Started in Mech Interp](https://www.neelnanda.io/mechanistic-interpretability/getting-started) - Network accessline 338
- [Mech Interp Glossary](https://www.neelnanda.io/mechanistic-interpretability/glossary) - Network accessline 339
- [YouTube Channel](https://www.youtube.com/@neelnanda)
bundled/skills/transformers/SKILL.md
bundled/skills/transformers/references/pipelines.md
- Network accessline 298
pipe("https://example.com/image.jpg")
bundled/skills/treatment-plans/SKILL.md
- Broad permissionsline 1
Read Write Edit Bash - Dangerous shell operationline 1390
sudo cp assets/medical_treatment_plan.sty /usr/local/texlive/texmf-local/tex/latex/ - Dangerous shell operationline 1391
sudo texhash - Network accessline 1413
**Download from CTAN:** - Visit: https://ctan.org/ - Network accessline 1414
- Visit: https://ctan.org/ - Search for medical document classes - Download and install per package instructions - Dangerous shell operationline 1423
sudo tlmgr update --self - Dangerous shell operationline 1424
sudo tlmgr install tcolorbox tikz pgf - Dangerous shell operationline 1439
sudo tlmgr install tcolorbox tikz pgf
bundled/skills/treatment-plans/assets/STYLING_QUICK_REFERENCE.md
- Dangerous shell operationline 171
sudo tlmgr install tcolorbox tikz pgf
bundled/skills/treatment-plans/scripts/check_completeness.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/treatment-plans/scripts/generate_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/treatment-plans/scripts/timeline_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/treatment-plans/scripts/validate_treatment_plan.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/uniprot-database/SKILL.md
- Network accessline 51
Use the API search endpoint: `https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}` - Network accessline 63
**Retrieve endpoint:** `https://rest.uniprot.org/uniprotkb/{accession}.{format}` - Network accessline 65
Example: `https://rest.uniprot.org/uniprotkb/P12345.fasta` - Network accessline 71
**ID Mapping workflow:** 1. Submit mapping job to: `https://rest.uniprot.org/idmapping/run` - Network accessline 72
1. Submit mapping job to: `https://rest.uniprot.org/idmapping/run` - Network accessline 73
2. Check job status: `https://rest.uniprot.org/idmapping/status/{jobId}` - Network accessline 74
3. Retrieve results: `https://rest.uniprot.org/idmapping/results/{jobId}` - Network accessline 92
`https://rest.uniprot.org/uniprotkb/stream?query={query}&format={format}` - Network accessline 112
**Example:** `https://rest.uniprot.org/uniprotkb/search?query=insulin&fields=accession,gene_names,organism_name,length,sequence&format=tsv` - Network accessline 185
- **API Documentation**: https://www.uniprot.org/help/api - Network accessline 186
- **Interactive API Explorer**: https://www.uniprot.org/api-documentation - Network accessline 187
- **REST Tutorial**: https://www.uniprot.org/help/uniprot_rest_tutorial - Network accessline 188
- **Query Syntax Help**: https://www.uniprot.org/help/query-fields - Network accessline 189
- **SPARQL Endpoint**: https://sparql.uniprot.org/ (for advanced graph queries)
bundled/skills/uniprot-database/references/api_examples.md
- Network accessline 11
# Search for human insulin proteins url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 12
url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 19
response = requests.get(url, params=params) - Network accessline 30
# Get human insulin sequence in FASTA format accession = "P01308" url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta" - Network accessline 32
url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta" - Network accessline 34
response = requests.get(url) - Network accessline 42
# Get specific fields only url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 43
url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 50
response = requests.get(url, params=params) - Network accessline 59
def map_uniprot_ids(ids, from_db, to_db): # Submit job submit_url = "https://rest.uniprot.org/idmapping/run" - Network accessline 60
# Submit job submit_url = "https://rest.uniprot.org/idmapping/run" data = { - Network accessline 61
submit_url = "https://rest.uniprot.org/idmapping/run" - Network accessline 68
response = requests.post(submit_url, data=data) - Network accessline 71
# Poll for completion status_url = f"https://rest.uniprot.org/idmapping/status/{job_id}" - Network accessline 72
status_url = f"https://rest.uniprot.org/idmapping/status/{job_id}" while True: response = requests.get(status_url) - Network accessline 73
while True: response = requests.get(status_url) status = response.json() - Network accessline 74
response = requests.get(status_url) - Network accessline 80
# Get results results_url = f"https://rest.uniprot.org/idmapping/results/{job_id}" response = requests.get(results_url) - Network accessline 81
results_url = f"https://rest.uniprot.org/idmapping/results/{job_id}" response = requests.get(results_url) return response.json() - Network accessline 82
response = requests.get(results_url) - Network accessline 95
# Stream all reviewed human proteins url = "https://rest.uniprot.org/uniprotkb/stream" - Network accessline 96
url = "https://rest.uniprot.org/uniprotkb/stream" - Network accessline 102
response = requests.get(url, params=params, stream=True) - Network accessline 115
def get_all_results(query, fields=None): """Get all results with pagination""" url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 116
"""Get all results with pagination""" url = "https://rest.uniprot.org/uniprotkb/search" all_results = [] - Network accessline 117
url = "https://rest.uniprot.org/uniprotkb/search" - Network accessline 129
while True: response = requests.get(url, params=params) - Network accessline 130
response = requests.get(url, params=params) - Network accessline 150
## cURL Examples - Network accessline 154
# Search for insulin proteins curl "https://rest.uniprot.org/uniprotkb/search?query=insulin&format=json&size=5" - Network accessline 155
curl "https://rest.uniprot.org/uniprotkb/search?query=insulin&format=json&size=5" - Network accessline 160
# Get human insulin in FASTA format curl "https://rest.uniprot.org/uniprotkb/P01308.fasta" - Network accessline 161
curl "https://rest.uniprot.org/uniprotkb/P01308.fasta" - Network accessline 166
# Get specific fields in TSV format curl "https://rest.uniprot.org/uniprotkb/search?query=gene:BRCA1&format=tsv&fields=accession,gene_names,length" - Network accessline 167
curl "https://rest.uniprot.org/uniprotkb/search?query=gene:BRCA1&format=tsv&fields=accession,gene_names,length" - Network accessline 172
# Submit mapping job curl -X POST "https://rest.uniprot.org/idmapping/run" \ - Network accessline 173
curl -X POST "https://rest.uniprot.org/idmapping/run" \ - Network accessline 180
# Get mapping results (replace JOB_ID) curl "https://rest.uniprot.org/idmapping/results/JOB_ID" - Network accessline 181
curl "https://rest.uniprot.org/idmapping/results/JOB_ID" - Network accessline 186
# Download all human reviewed proteins curl "https://rest.uniprot.org/uniprotkb/stream?query=organism_id:9606+AND+reviewed:true&format=fasta" \ - Network accessline 187
curl "https://rest.uniprot.org/uniprotkb/stream?query=organism_id:9606+AND+reviewed:true&format=fasta" \ - Network accessline 198
# Search for insulin proteins url <- "https://rest.uniprot.org/uniprotkb/search" - Network accessline 199
url <- "https://rest.uniprot.org/uniprotkb/search" - Network accessline 218
# Get protein sequence accession <- "P01308" url <- paste0("https://rest.uniprot.org/uniprotkb/", accession, ".fasta") - Network accessline 220
url <- paste0("https://rest.uniprot.org/uniprotkb/", accession, ".fasta") - Network accessline 232
# Get data as TSV url <- "https://rest.uniprot.org/uniprotkb/search" - Network accessline 233
url <- "https://rest.uniprot.org/uniprotkb/search" - Network accessline 249
// Search for proteins async function searchUniProt(query) { const url = `https://rest.uniprot.org/uniprotkb/search?query=${encodeURIComponent(query)}&format=json&size=10`; - Network accessline 251
const url = `https://rest.uniprot.org/uniprotkb/search?query=${encodeURIComponent(query)}&format=json&size=10`; - Network accessline 253
const response = await fetch(url); - Network accessline 266
async function getProtein(accession, format = "json") { const url = `https://rest.uniprot.org/uniprotkb/${accession}.${format}`; - Network accessline 267
const url = `https://rest.uniprot.org/uniprotkb/${accession}.${format}`; - Network accessline 269
const response = await fetch(url); - Network accessline 285
async function mapIds(ids, fromDb, toDb) { // Submit job const submitUrl = "https://rest.uniprot.org/idmapping/run"; - Network accessline 286
// Submit job const submitUrl = "https://rest.uniprot.org/idmapping/run"; const formData = new URLSearchParams({ - Network accessline 287
const submitUrl = "https://rest.uniprot.org/idmapping/run"; - Network accessline 294
const submitResponse = await fetch(submitUrl, { - Network accessline 300
// Poll for completion const statusUrl = `https://rest.uniprot.org/idmapping/status/${jobId}`; - Network accessline 301
const statusUrl = `https://rest.uniprot.org/idmapping/status/${jobId}`; while (true) { const statusResponse = await fetch(statusUrl); - Network accessline 302
while (true) { const statusResponse = await fetch(statusUrl); const status = await statusResponse.json(); - Network accessline 303
const statusResponse = await fetch(statusUrl); - Network accessline 313
// Get results const resultsUrl = `https://rest.uniprot.org/idmapping/results/${jobId}`; const resultsResponse = await fetch(resultsUrl); - Network accessline 314
const resultsUrl = `https://rest.uniprot.org/idmapping/results/${jobId}`; const resultsResponse = await fetch(resultsUrl); return await resultsResponse.json(); - Network accessline 315
const resultsResponse = await fetch(resultsUrl); - Network accessline 332
class UniProtClient: def __init__(self, rate_limit=1.0): self.base_url = "https://rest.uniprot.org" - Network accessline 333
def __init__(self, rate_limit=1.0): self.base_url = "https://rest.uniprot.org" self.rate_limit = rate_limit - Network accessline 334
self.base_url = "https://rest.uniprot.org" - Network accessline 356
response = requests.get( - Network accessline 384
def download_with_progress(query, output_file, format="fasta"): """Download results with progress bar""" url = "https://rest.uniprot.org/uniprotkb/stream" - Network accessline 385
"""Download results with progress bar""" url = "https://rest.uniprot.org/uniprotkb/stream" params = { - Network accessline 386
url = "https://rest.uniprot.org/uniprotkb/stream" - Network accessline 392
response = requests.get(url, params=params, stream=True) - Network accessline 410
- API Documentation: https://www.uniprot.org/help/api - Network accessline 411
- Interactive API Explorer: https://www.uniprot.org/api-documentation - Network accessline 412
- Python client (Unipressed): https://github.com/multimeric/Unipressed - Network accessline 413
- UniProt REST API documentation: https://www.uniprot.org/help/api
bundled/skills/uniprot-database/references/api_fields.md
- Network accessline 9
https://rest.uniprot.org/uniprotkb/search?query=insulin&fields=accession,gene_names,organism_name,length - Network accessline 217
curl https://rest.uniprot.org/configure/uniprotkb/result-fields - Network accessline 222
import requests response = requests.get("https://rest.uniprot.org/configure/uniprotkb/result-fields") - Network accessline 223
response = requests.get("https://rest.uniprot.org/configure/uniprotkb/result-fields") - Network accessline 273
- Interactive field explorer: https://www.uniprot.org/api-documentation - Network accessline 274
- API fields endpoint: https://rest.uniprot.org/configure/uniprotkb/result-fields - Network accessline 275
- Return fields documentation: https://www.uniprot.org/help/return_fields
bundled/skills/uniprot-database/references/id_mapping_databases.md
- Network accessline 8
import requests response = requests.get("https://rest.uniprot.org/configure/idmapping/fields") - Network accessline 9
response = requests.get("https://rest.uniprot.org/configure/idmapping/fields") - Network accessline 260
GET https://rest.uniprot.org/configure/idmapping/fields - Network accessline 265
POST https://rest.uniprot.org/idmapping/run - Network accessline 273
GET https://rest.uniprot.org/idmapping/status/{jobId} - Network accessline 278
GET https://rest.uniprot.org/idmapping/results/{jobId} - Network accessline 283
- ID Mapping tool: https://www.uniprot.org/id-mapping - Network accessline 284
- API documentation: https://www.uniprot.org/help/id_mapping - Network accessline 285
- Programmatic access: https://www.uniprot.org/help/api_idmapping
bundled/skills/uniprot-database/references/query_syntax.md
- Network accessline 220
Test queries using: - **Web interface**: https://www.uniprot.org/uniprotkb - Network accessline 221
- **Web interface**: https://www.uniprot.org/uniprotkb - Network accessline 222
- **API**: https://rest.uniprot.org/uniprotkb/search?query=YOUR_QUERY - Network accessline 223
- **API documentation**: https://www.uniprot.org/help/query-fields - Network accessline 254
- Full query field reference: https://www.uniprot.org/help/query-fields - Network accessline 255
- API query documentation: https://www.uniprot.org/help/api_queries - Network accessline 256
- Text search documentation: https://www.uniprot.org/help/text-search
bundled/skills/uniprot-database/scripts/uniprot_client.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 31
BASE_URL = "https://rest.uniprot.org" - Network accessline 61
response = requests.get(endpoint, params=params) - Network accessline 83
response = requests.get(endpoint) - Network accessline 134
response = requests.get(endpoint, params=params, stream=True) - Network accessline 173
response = requests.post(submit_endpoint, data=data) - Network accessline 180
while True: response = requests.get(status_endpoint) - Network accessline 181
response = requests.get(status_endpoint) - Network accessline 193
params = {"format": format} response = requests.get(results_endpoint, params=params) - Network accessline 194
response = requests.get(results_endpoint, params=params) - Network accessline 212
response = requests.get(endpoint) - Network accessline 227
response = requests.get(endpoint)
bundled/skills/unsloth/references/llms-txt.md
- Access to secretsline 12
[Credential-related source omitted] - Network accessline 35
{% hint style="success" %} Read more on running Llama 4 here: <https://docs.unsloth.ai/basics/tutorial-how-to-run-and-fine-tune-llama-4> - Network accessline 36
Read more on running Llama 4 here: <https://docs.unsloth.ai/basics/tutorial-how-to-run-and-fine-tune-llama-4> - Network accessline 75
Qwen3-Coder is Qwen’s new series of coding agent models, available in 30B (**Qwen3-Coder-Flash**) and 480B parameters. **Qwen3-480B-A35B-Instruct** achieves SOTA coding performance rivalling Claude Sonnet-4, GPT-4.1, and [Kimi K2](https://d - Network accessline 77
We also uploaded Qwen3-Coder with native <mark style="background-color:purple;">**1M context length**</mark> extended by YaRN and full-precision 8bit and 16bit versions. [Unsloth](https://github.com/unslothai/unsloth) also now supports fine - Network accessline 85
{% hint style="success" %} **Does** [**Unsloth Dynamic Quants**](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) **work?** Yes, and very well. In third-party testing on the Aider Polyglot benchmark, the **UD-Q4\_K\_XL (276GB)** dy - Network accessline 86
**Does** [**Unsloth Dynamic Quants**](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) **work?** Yes, and very well. In third-party testing on the Aider Polyglot benchmark, the **UD-Q4\_K\_XL (276GB)** dynamic quant nearly matched - Network accessline 91
| Dynamic 2.0 GGUF (to run) | 1M Context Dyn - Network accessline 93
| <ul><li><a href="https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF">30B-A3B-Instruct</a></li><li><a href="https://huggingface.co/unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF">480B-A35B-Instruct</a></li></ul> | <ul><li><a hre - Network accessline 147
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 186
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 188
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 188
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 236
Orpheus supports tags like `<laugh>`, `<chuckle>`, `<sigh>`, `<cough>`, `<sniffle>`, `<groan>`, `<yawn>`, `<gasp>`, etc. For example: `"I missed you <laugh> so much!"`. These tags are enclosed in angle brackets and will be treated as speci - Network accessline 299
Unsloth model catalog for all our [Dynamic](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) GGUF, 4-bit, 16-bit models on Hugging Face. - Network accessline 309
| Model | Variant | GGUF | Instruct (4-bit) - Network accessline 310
| ------------------------------------------------------------------------------------------ | ---------------------- | ------------------------------------------------------------------------------- | -------------------------------------- - Network accessline 311
| [**gpt-oss** ](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune) | 120b | [link](https://huggingface.co/unsloth/gpt-oss-120b-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 312
| | 20b | [link](https://huggingface.co/unsloth/gpt-oss-20b-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 313
| [**DeepSeek-V3.1**](https://docs.unsloth.ai/models/deepseek-v3.1-how-to-run-locally) | Terminus | [link](https://huggingface.co/unsloth/DeepSeek-V3.1-Terminus-GGUF) | — - Network accessline 314
| | V3.1 | [link](https://huggingface.co/unsloth/DeepSeek-V3.1-GGUF) | — - Network accessline 315
| [**Qwen3-VL**](https://docs.unsloth.ai/models/qwen3-vl-how-to-run-and-fine-tune) | 2B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-2B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 316
| | 2B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-2B-Thinking-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 317
| | 4B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-4B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 318
| | 4B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-4B-Thinking-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 319
| | 8B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 320
| | 8B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-8B-Thinking-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 321
| | 30B-A3B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF) | — - Network accessline 322
| | 30B-A3B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-30B-A3B-Thinking-GGUF) | — - Network accessline 323
| | 32B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-32B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 324
| | 32B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-32B-Thinking-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 325
| | 235B-A22B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-VL-235B-A22B-Instruct-GGUF) | — - Network accessline 326
| | 235B-A22B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-VL-235B-A22B-Thinking-GGUF) | — - Network accessline 327
| [**Qwen3-2507**](https://docs.unsloth.ai/models/qwen3-how-to-run-and-fine-tune/qwen3-2507) | 30B-A3B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF) | — - Network accessline 328
| | 30B-A3B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Thinking-2507-GGUF) | — - Network accessline 329
| | 235B-A22B-Thinking | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B-Thinking-2507-GGUF/) | — - Network accessline 330
| | 235B-A22B-Instruct | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B-Instruct-2507-GGUF/) | — - Network accessline 331
| **Qwen3-Coder** | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF) | — - Network accessline 332
| | 480B-A35B | [link](https://huggingface.co/unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF) | — - Network accessline 333
| **Granite-4.0 (new)** | H-Small | [link](https://huggingface.co/unsloth/granite-4.0-h-small-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 334
| **GLM (new)** | 4.6 | [link](https://huggingface.co/unsloth/GLM-4.6-GGUF) | — - Network accessline 335
| | 4.5-Air | [link](https://huggingface.co/unsloth/GLM-4.5-Air-GGUF) | — - Network accessline 336
| **Kimi-K2-0905** | 1T | [link](https://huggingface.co/unsloth/Kimi-K2-Instruct-0905-GGUF) | — - Network accessline 337
| **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3n-E2B-it-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 338
| | E4B | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 339
| **DeepSeek-R1-0528** | R1-0528-Qwen3-8B | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 340
| | R1-0528 | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF) | — - Network accessline 341
| **Mistral** | Magistral Small (2509) | [link](https://huggingface.co/unsloth/Magistral-Small-2509-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 342
| | Magistral Small (2507) | [link](https://huggingface.co/unsloth/Magistral-Small-2507-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 343
| | Small 3.2 24B (2506) | [link](https://huggingface.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 344
| FLUX.1 | Kontext-dev | [link](https://huggingface.co/unsloth/FLUX.1-Kontext-dev-GGUF) | — - Network accessline 345
| **Qwen3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 346
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 347
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 348
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 349
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 350
| | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 351
| | 32 B | [link](https://huggingface.co/unsloth/Qwen3-32B-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 352
| | 235B-A22B | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B-GGUF) | — - Network accessline 353
| **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 354
| | Maverick 17B 128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF) | — - Network accessline 355
| **Grok 2** | 270B | [link](https://huggingface.co/unsloth/grok-2-GGUF) | — - Network accessline 356
| **Qwen-2.5 Omni** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-3B-GGUF) | — - Network accessline 357
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-7B-GGUF) | — - Network accessline 358
| **Phi-4** | Reasoning-plus | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 359
| | Reasoning | [link](https://huggingface.co/unsloth/Phi-4-reasoning-GGUF) | [link](https://huggingface.co/unsloth/ - Network accessline 361
| Model | Variant | GGUF | Instruct (4-bit) | | ----------------- | ------- - Network accessline 362
| ----------------- | ---------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | **DeepSeek-V3.1** | Terminu - Network accessline 363
| **DeepSeek-V3.1** | Terminus | [link](https://huggingface.co/unsloth/DeepSeek-V3.1-Terminus-GGUF) | | - Network accessline 364
| | V3.1 | [link](https://huggingface.co/unsloth/DeepSeek-V3.1-GGUF) | | - Network accessline 365
| **DeepSeek-V3** | V3-0324 | [link](https://huggingface.co/unsloth/DeepSeek-V3-0324-GGUF) | — | - Network accessline 366
| | V3 | [link](https://huggingface.co/unsloth/DeepSeek-V3-GGUF) | — | - Network accessline 367
| **DeepSeek-R1** | R1-0528 | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF) | — | - Network accessline 368
| | R1-0528-Qwen3-8B | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B-unsloth-bnb-4bit) | - Network accessline 369
| | R1 | [link](https://huggingface.co/unsloth/DeepSeek-R1-GGUF) | — | - Network accessline 370
| | R1 Zero | [link](https://huggingface.co/unsloth/DeepSeek-R1-Zero-GGUF) | — | - Network accessline 371
| | Distill Llama 3 8 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-8B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-8B-unsloth-bnb-4bit) | - Network accessline 372
| | Distill Llama 3.3 70 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-70B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-70B-bnb-4bit) | - Network accessline 373
| | Distill Qwen 2.5 1.5 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-1.5B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-1.5B-unsloth-bnb-4bit) | - Network accessline 374
| | Distill Qwen 2.5 7 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-unsloth-bnb-4bit) | - Network accessline 375
| | Distill Qwen 2.5 14 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-unsloth-bnb-4bit) | - Network accessline 376
| | Distill Qwen 2.5 32 B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-32B-GGUF) | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit) | - Network accessline 378
| Model | Variant | GGUF | Instruct (4-bit) | | ------------- | ------------ - Network accessline 379
| ------------- | ------------------- | ------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------- | | **Llama 4** | Scout 17 B-1 - Network accessline 380
| **Llama 4** | Scout 17 B-16 E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-4bit) | - Network accessline 381
| | Maverick 17 B-128 E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF) | — | - Network accessline 382
| **Llama 3.3** | 70 B | [link](https://huggingface.co/unsloth/Llama-3.3-70B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Llama-3.3-70B-Instruct-bnb-4bit) | - Network accessline 383
| **Llama 3.2** | 1 B | [link](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-bnb-4bit) | - Network accessline 384
| | 3 B | [link](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct-bnb-4bit) | - Network accessline 385
| | 11 B Vision | — | [link](https://huggingface.co/unsloth/Llama-3.2-11B-Vision-Instruct-unsloth-bnb-4bit) | - Network accessline 386
| | 90 B Vision | — | [link](https://huggingface.co/unsloth/Llama-3.2-90B-Vision-Instruct-bnb-4bit) | - Network accessline 387
| **Llama 3.1** | 8 B | [link](https://huggingface.co/unsloth/Llama-3.1-8B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit) | - Network accessline 388
| | 70 B | — | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-70B-Instruct-bnb-4bit) | - Network accessline 389
| | 405 B | — | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-405B-Instruct-bnb-4bit) | - Network accessline 390
| **Llama 3** | 8 B | — | [link](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) | - Network accessline 391
| | 70 B | — | [link](https://huggingface.co/unsloth/llama-3-70b-bnb-4bit) | - Network accessline 392
| **Llama 2** | 7 B | — | [link](https://huggingface.co/unsloth/llama-2-7b-chat-bnb-4bit) | - Network accessline 393
| | 13 B | — | [link](https://huggingface.co/unsloth/llama-2-13b-bnb-4bit) | - Network accessline 394
| **CodeLlama** | 7 B | — | [link](https://huggingface.co/unsloth/codellama-7b-bnb-4bit) | - Network accessline 395
| | 13 B | — | [link](https://huggingface.co/unsloth/codellama-13b-bnb-4bit) | - Network accessline 396
| | 34 B | — | [link](https://huggingface.co/unsloth/codellama-34b-bnb-4bit) | - Network accessline 398
| Model | Variant | GGUF | Instruct (4-bit) | | ------------ | ------------- | -------------------------------- - Network accessline 399
| ------------ | ------------- | ------------------------------------------------------------ | ---------------------------------------------------------------------------- | | **Gemma 3n** | E2B | <U+200B>[link](https://huggingface.co/u - Network accessline 400
| **Gemma 3n** | E2B | <U+200B>[link](https://huggingface.co/unsloth/gemma-3n-E2B-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3n-E2B-it-unsloth-bnb-4bit) | - Possible obfuscationline 400
| **Gemma 3n** | E2B | <U+200B>[link](https://huggingface.co/unsloth/gemma-3n-E2B-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3n-E2B-it-unsloth-bnb-4bit) | - Network accessline 401
| | E4B | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it-unsloth-bnb-4bit) | - Network accessline 402
| **Gemma 3** | 270M | [link](https://huggingface.co/unsloth/gemma-3-270m-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3-270m-it) | - Network accessline 403
| | 1 B | [link](https://huggingface.co/unsloth/gemma-3-1b-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3-1b-it-unsloth-bnb-4bit) | - Network accessline 404
| | 4 B | [link](https://huggingface.co/unsloth/gemma-3-4b-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3-4b-it-unsloth-bnb-4bit) | - Network accessline 405
| | 12 B | [link](https://huggingface.co/unsloth/gemma-3-12b-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3-12b-it-unsloth-bnb-4bit) | - Network accessline 406
| | 27 B | [link](https://huggingface.co/unsloth/gemma-3-27b-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-3-27b-it-unsloth-bnb-4bit) | - Network accessline 407
| **MedGemma** | 4 B (vision) | [link](https://huggingface.co/unsloth/medgemma-4b-it-GGUF) | [link](https://huggingface.co/unsloth/medgemma-4b-it-unsloth-bnb-4bit) | - Network accessline 408
| | 27 B (vision) | [link](https://huggingface.co/unsloth/medgemma-27b-it-GGUF) | [link](https://huggingface.co/unsloth/medgemma-27b-text-it-unsloth-bnb-4bit) | - Network accessline 409
| **Gemma 2** | 2 B | [link](https://huggingface.co/unsloth/gemma-2-it-GGUF) | [link](https://huggingface.co/unsloth/gemma-2-2b-it-bnb-4bit) | - Network accessline 410
| | 9 B | — | [link](https://huggingface.co/unsloth/gemma-2-9b-it-bnb-4bit) | - Network accessline 411
| | 27 B | — | [link](https://huggingface.co/unsloth/gemma-2-27b-it-bnb-4bit) | - Network accessline 413
| Model | Variant | GGUF | Instruct (4-bit) | | -------------------------- | ---- - Network accessline 414
| -------------------------- | ---------- | ---------------------------------------------------------------------------- | ------------------------------------------------------------------------------- | | **Qwen 3** | 0.6 - Network accessline 415
| **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-0.6B-unsloth-bnb-4bit) | - Network accessline 416
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-1.7B-unsloth-bnb-4bit) | - Network accessline 417
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-4B-unsloth-bnb-4bit) | - Network accessline 418
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-8B-unsloth-bnb-4bit) | - Network accessline 419
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-14B-unsloth-bnb-4bit) | - Network accessline 420
| | 30 B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-bnb-4bit) | - Network accessline 421
| | 32 B | [link](https://huggingface.co/unsloth/Qwen3-32B-GGUF) | [link](https://huggingface.co/unsloth/Qwen3-32B-unsloth-bnb-4bit) | - Network accessline 422
| | 235 B-A22B | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B-GGUF) | — | - Network accessline 423
| **Qwen 2.5 Omni** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-3B-GGUF) | — | - Network accessline 424
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-7B-GGUF) | — | - Network accessline 425
| **Qwen 2.5 VL** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-3B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-VL-3B-Instruct-unsloth-bnb-4bit) | - Network accessline 426
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-7B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bit) | - Network accessline 427
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-32B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit) | - Network accessline 428
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-72B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-VL-72B-Instruct-unsloth-bnb-4bit) | - Network accessline 429
| **Qwen 2.5** | 0.5 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-0.5B-Instruct-bnb-4bit) | - Network accessline 430
| | 1.5 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit) | - Network accessline 431
| | 3 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-bnb-4bit) | - Network accessline 432
| | 7 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-7B-Instruct-bnb-4bit) | - Network accessline 433
| | 14 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-14B-Instruct-bnb-4bit) | - Network accessline 434
| | 32 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-32B-Instruct-bnb-4bit) | - Network accessline 435
| | 72 B | — | [link](https://huggingface.co/unsloth/Qwen2.5-72B-Instruct-bnb-4bit) | - Network accessline 436
| **Qwen 2.5 Coder (128 K)** | 0.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-0.5B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-0.5B-Instruct-bnb-4bit) | - Network accessline 437
| | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-1.5B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-1.5B-Instruct-bnb-4bit) | - Network accessline 438
| | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-3B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit) | - Network accessline 439
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-7B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit) | - Network accessline 440
| | 14 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-14B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-14B-Instruct-bnb-4bit) | - Network accessline 441
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-32B-Instruct-128K-GGUF) | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-32B-Instruct-bnb-4bit) | - Network accessline 442
| **QwQ** | 32 B | [link](https://huggingface.co/unsloth/QwQ-32B-GGUF) | [link](https://huggingface.co/unsloth/QwQ-32B-unsloth-bnb-4bit) | - Network accessline 443
| **QVQ (preview)** | 72 B | — | [link](https://huggingface.co/unsloth/QVQ-72B-Preview-bnb-4bit) | - Network accessline 444
| **Qwen 2 (chat)** | 1.5 B | — | [link](https://huggingface.co/unsloth/Qwen2-1.5B-Instruct-bnb-4bit) | - Network accessline 445
| | 7 B | — | [link](https://huggingface.co/unsloth/Qwen2-7B-Instruct-bnb-4bit) | - Network accessline 446
| | 72 B | — | [link](https://huggingface.co/unsloth/Qwen2-72B-Instruct-bnb-4bit) | - Network accessline 447
| **Qwen 2 VL** | 2 B | — | [link](https://huggingface.co/unsloth/Qwen2-VL-2B-Instruct-unsloth-bnb-4bit) | - Network accessline 448
| | 7 B | — | [link](https://huggingface.co/unsloth/Qwen2-VL-7B-Instruct-unsloth-bnb-4bit) | - Network accessline 449
| | 72 B | — | [link](https://huggingface.co/unsloth/Qwen2-VL-72B-Instruct-bnb-4bit) | - Network accessline 451
<table><thead><tr><th width="174">Model</th><th>Variant</th><th>GGUF</th><th>Instruct (4-bit)</th></tr></thead><tbody><tr><td><strong>Mistral Small</strong></td><td>3.2-24 B (2506)</td><td><a href="https://huggingface.co/unsloth/Mistral-Sma - Network accessline 453
| Model | Variant | GGUF | Instruct (4-bit) | | ----------- | ---------------- | ------------------------ - Network accessline 454
| ----------- | ---------------- | ---------------------------------------------------------------- | ---------------------------------------------------------------------------- | | **Phi-4** | Reasoning-plus | [link](https://huggingfa - Network accessline 455
| **Phi-4** | Reasoning-plus | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus-GGUF) | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus-unsloth-bnb-4bit) | - Network accessline 456
| | Reasoning | [link](https://huggingface.co/unsloth/Phi-4-reasoning-GGUF) | [link](https://huggingface.co/unsloth/phi-4-reasoning-unsloth-bnb-4bit) | - Network accessline 457
| | Mini-Reasoning | [link](https://huggingface.co/unsloth/Phi-4-mini-reasoning-GGUF) | [link](https://huggingface.co/unsloth/Phi-4-mini-reasoning-unsloth-bnb-4bit) | - Network accessline 458
| | Phi-4 (instruct) | [link](https://huggingface.co/unsloth/phi-4-GGUF) | [link](https://huggingface.co/unsloth/phi-4-unsloth-bnb-4bit) | - Network accessline 459
| | mini (instruct) | [link](https://huggingface.co/unsloth/Phi-4-mini-instruct-GGUF) | [link](https://huggingface.co/unsloth/Phi-4-mini-instruct-unsloth-bnb-4bit) | - Network accessline 460
| **Phi-3.5** | mini | — | [link](https://huggingface.co/unsloth/Phi-3.5-mini-instruct-bnb-4bit) | - Network accessline 461
| **Phi-3** | mini | — | [link](https://huggingface.co/unsloth/Phi-3-mini-4k-instruct-bnb-4bit) | - Network accessline 462
| | medium | — | [link](https://huggingface.co/unsloth/Phi-3-medium-4k-instruct-bnb-4bit) | - Network accessline 466
| Model | Variant | GGUF | Instruct (4-bit) | | -------------- | ----------------- | ----- - Network accessline 467
| -------------- | ----------------- | ------------------------------------------------------------------------------ | ------------------------------------------------------------------------- | | GLM | 4.5-Air | [link - Network accessline 468
| GLM | 4.5-Air | [link](https://huggingface.co/unsloth/GLM-4.5-Air-GGUF) | | - Network accessline 469
| | 4.5 | [4.5](https://huggingface.co/unsloth/GLM-4.5-GGUF) | | - Network accessline 470
| | 4-32B-0414 | [4-32B-0414](https://huggingface.co/unsloth/GLM-4-32B-0414-GGUF) | | - Network accessline 471
| Hunyuan | A13B | [link](https://huggingface.co/unsloth/Hunyuan-A13B-Instruct-GGUF) | — | - Network accessline 472
| Orpheus | 0.1-ft (3B) | [link](https://app.gitbook.com/o/HpyELzcNe0topgVLGCZY/s/xhOjnexMCB3dmuQFQ2Zq/) | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-ft-unsloth-bnb-4bit) | - Network accessline 473
| **LLava** | 1.5 (7 B) | — | [link](https://huggingface.co/unsloth/llava-1.5-7b-hf-bnb-4bit) | - Network accessline 474
| | 1.6 Mistral (7 B) | — | [link](https://huggingface.co/unsloth/llava-v1.6-mistral-7b-hf-bnb-4bit) | - Network accessline 475
| **TinyLlama** | Chat | — | [link](https://huggingface.co/unsloth/tinyllama-chat-bnb-4bit) | - Network accessline 476
| **SmolLM 2** | 135 M | [link](https://huggingface.co/unsloth/SmolLM2-135M-Instruct-GGUF) | [link](https://huggingface.co/unsloth/SmolLM2-135M-Instruct-bnb-4bit) | - Network accessline 477
| | 360 M | [link](https://huggingface.co/unsloth/SmolLM2-360M-Instruct-GGUF) | [link](https://huggingface.co/unsloth/SmolLM2-360M-Instruct-bnb-4bit) | - Network accessline 478
| | 1.7 B | [link](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct-GGUF) | [link](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct-bnb-4bit) | - Network accessline 479
| **Zephyr-SFT** | 7 B | — | [link](https://huggingface.co/unsloth/zephyr-sft-bnb-4bit) | - Network accessline 480
| **Yi** | 6 B (v1.5) | — | [link](https://huggingface.co/unsloth/Yi-1.5-6B-bnb-4bit) | - Network accessline 481
| | 6 B (v1.0) | — | [link](https://huggingface.co/unsloth/yi-6b-bnb-4bit) | - Network accessline 482
| | 34 B (chat) | — | [link](https://huggingface.co/unsloth/yi-34b-chat-bnb-4bit) | - Network accessline 483
| | 34 B (base) | — | [link](https://huggingface.co/unsloth/yi-34b-bnb-4bit) | - Network accessline 489
| Model | Variant | Instruct (16-bit) | | -------------------- | ---------------------- | --------------------------------------------------------------- - Network accessline 490
| -------------------- | ---------------------- | -------------------------------------------------------------------------- | | **gpt-oss** (new) | 20b | [link](https://huggingface.co/unsloth/gpt-oss-20b) - Network accessline 491
| **gpt-oss** (new) | 20b | [link](https://huggingface.co/unsloth/gpt-oss-20b) | - Network accessline 492
| | 120b | [link](https://huggingface.co/unsloth/gpt-oss-120b) | - Network accessline 493
| **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it) | - Network accessline 494
| | E4B | [link](https://huggingface.co/unsloth/gemma-3n-E2B-it) | - Network accessline 495
| **DeepSeek-R1-0528** | R1-0528-Qwen3-8B | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B) | - Network accessline 496
| | R1-0528 | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528) | - Network accessline 497
| **Mistral** | Small 3.2 24B (2506) | [link](https://huggingface.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506) | - Network accessline 498
| | Small 3.1 24B (2503) | [link](https://huggingface.co/unsloth/Mistral-Small-3.1-24B-Instruct-2503) | - Network accessline 499
| | Small 3.0 24B (2501) | [link](https://huggingface.co/unsloth/Mistral-Small-24B-Instruct-2501) | - Network accessline 500
| | Magistral Small (2506) | [link](https://huggingface.co/unsloth/Magistral-Small-2506) | - Network accessline 501
| **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B) | - Network accessline 502
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B) | - Network accessline 503
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B) | - Network accessline 504
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B) | - Network accessline 505
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B) | - Network accessline 506
| | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B) | - Network accessline 507
| | 32 B | [link](https://huggingface.co/unsloth/Qwen3-32B) | - Network accessline 508
| | 235B-A22B | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B) | - Network accessline 509
| **Llama 4** | Scout 17B-16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct) | - Network accessline 510
| | Maverick 17B-128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct) | - Network accessline 511
| **Qwen 2.5 Omni** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-3B) | - Network accessline 512
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-7B) | - Network accessline 513
| **Phi-4** | Reasoning-plus | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus) | - Network accessline 514
| | Reasoning | [link](https://huggingface.co/unsloth/Phi-4-reasoning) | - Network accessline 516
| Model | Variant | Instruct (16-bit) | | --------------- | --------------------- | -------------------------------------------------------------------- | | **DeepSe - Network accessline 517
| --------------- | --------------------- | -------------------------------------------------------------------- | | **DeepSeek-V3** | V3-0324 | [link](https://huggingface.co/unsloth/DeepSeek-V3-0324) | | - Network accessline 518
| **DeepSeek-V3** | V3-0324 | [link](https://huggingface.co/unsloth/DeepSeek-V3-0324) | - Network accessline 519
| | V3 | [link](https://huggingface.co/unsloth/DeepSeek-V3) | - Network accessline 520
| **DeepSeek-R1** | R1-0528 | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528) | - Network accessline 521
| | R1-0528-Qwen3-8B | [link](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B) | - Network accessline 522
| | R1 | [link](https://huggingface.co/unsloth/DeepSeek-R1) | - Network accessline 523
| | R1 Zero | [link](https://huggingface.co/unsloth/DeepSeek-R1-Zero) | - Network accessline 524
| | Distill Llama 3 8B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-8B) | - Network accessline 525
| | Distill Llama 3.3 70B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-70B) | - Network accessline 526
| | Distill Qwen 2.5 1.5B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-1.5B) | - Network accessline 527
| | Distill Qwen 2.5 7B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-7B) | - Network accessline 528
| | Distill Qwen 2.5 14B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-14B) | - Network accessline 529
| | Distill Qwen 2.5 32B | [link](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-32B) | - Network accessline 531
| Family | Variant | Instruct (16-bit) | | ------------- | ----------------- | ------------------------------------------------------------------------- | | **Llama 4* - Network accessline 532
| ------------- | ----------------- | ------------------------------------------------------------------------- | | **Llama 4** | Scout 17B-16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct) | | - Network accessline 533
| **Llama 4** | Scout 17B-16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct) | - Network accessline 534
| | Maverick 17B-128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct) | - Network accessline 535
| **Llama 3.3** | 70 B | [link](https://huggingface.co/unsloth/Llama-3.3-70B-Instruct) | - Network accessline 536
| **Llama 3.2** | 1 B | [link](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) | - Network accessline 537
| | 3 B | [link](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct) | - Network accessline 538
| | 11 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-11B-Vision-Instruct) | - Network accessline 539
| | 90 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-90B-Vision-Instruct) | - Network accessline 540
| **Llama 3.1** | 8 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) | - Network accessline 541
| | 70 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-70B-Instruct) | - Network accessline 542
| | 405 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-405B-Instruct) | - Network accessline 543
| **Llama 3** | 8 B | [link](https://huggingface.co/unsloth/llama-3-8b-Instruct) | - Network accessline 544
| | 70 B | [link](https://huggingface.co/unsloth/llama-3-70b-Instruct) | - Network accessline 545
| **Llama 2** | 7 B | [link](https://huggingface.co/unsloth/llama-2-7b-chat) | - Network accessline 547
| Model | Variant | Instruct (16-bit) | | ------------ | ------- | ------------------------------------------------------ | | **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3 - Network accessline 548
| ------------ | ------- | ------------------------------------------------------ | | **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it) | | | E4B | [link](https://huggingface.co/unsloth/gemma-3 - Network accessline 549
| **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3n-E4B-it) | - Network accessline 550
| | E4B | [link](https://huggingface.co/unsloth/gemma-3n-E2B-it) | - Network accessline 551
| **Gemma 3** | 1 B | [link](https://huggingface.co/unsloth/gemma-3-1b-it) | - Network accessline 552
| | 4 B | [link](https://huggingface.co/unsloth/gemma-3-4b-it) | - Network accessline 553
| | 12 B | [link](https://huggingface.co/unsloth/gemma-3-12b-it) | - Network accessline 554
| | 27 B | [link](https://huggingface.co/unsloth/gemma-3-27b-it) | - Network accessline 555
| **Gemma 2** | 2 B | [link](https://huggingface.co/unsloth/gemma-2b-it) | - Network accessline 556
| | 9 B | [link](https://huggingface.co/unsloth/gemma-9b-it) | - Network accessline 557
| | 27 B | [link](https://huggingface.co/unsloth/gemma-27b-it) | - Network accessline 559
| Family | Variant | Instruct (16-bit) | | ------------------------ | --------- | ----------------------------------------------------------------------- | | **Qwen 3 - Network accessline 560
| ------------------------ | --------- | ----------------------------------------------------------------------- | | **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B) | | - Network accessline 561
| **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B) | - Network accessline 562
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B) | - Network accessline 563
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B) | - Network accessline 564
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B) | - Network accessline 565
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B) | - Network accessline 566
| | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B) | - Network accessline 567
| | 32 B | [link](https://huggingface.co/unsloth/Qwen3-32B) | - Network accessline 568
| | 235B-A22B | [link](https://huggingface.co/unsloth/Qwen3-235B-A22B) | - Network accessline 569
| **Qwen 2.5 Omni** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-3B) | - Network accessline 570
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Omni-7B) | - Network accessline 571
| **Qwen 2.5 VL** | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-3B-Instruct) | - Network accessline 572
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-7B-Instruct) | - Network accessline 573
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-32B-Instruct) | - Network accessline 574
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2.5-VL-72B-Instruct) | - Network accessline 575
| **Qwen 2.5** | 0.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-0.5B-Instruct) | - Network accessline 576
| | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-1.5B-Instruct) | - Network accessline 577
| | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct) | - Network accessline 578
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-7B-Instruct) | - Network accessline 579
| | 14 B | [link](https://huggingface.co/unsloth/Qwen2.5-14B-Instruct) | - Network accessline 580
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-32B-Instruct) | - Network accessline 581
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2.5-72B-Instruct) | - Network accessline 582
| **Qwen 2.5 Coder 128 K** | 0.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-0.5B-Instruct-128K) | - Network accessline 583
| | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-1.5B-Instruct-128K) | - Network accessline 584
| | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-3B-Instruct-128K) | - Network accessline 585
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-7B-Instruct-128K) | - Network accessline 586
| | 14 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-14B-Instruct-128K) | - Network accessline 587
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-Coder-32B-Instruct-128K) | - Network accessline 588
| **QwQ** | 32 B | [link](https://huggingface.co/unsloth/QwQ-32B) | - Network accessline 589
| **QVQ (preview)** | 72 B | — | | **Qwen 2 (Chat)** | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2-1.5B-Instruct) | | - Network accessline 590
| **Qwen 2 (Chat)** | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2-1.5B-Instruct) | - Network accessline 591
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2-7B-Instruct) | - Network accessline 592
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2-72B-Instruct) | - Network accessline 593
| **Qwen 2 VL** | 2 B | [link](https://huggingface.co/unsloth/Qwen2-VL-2B-Instruct) | - Network accessline 594
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2-VL-7B-Instruct) | - Network accessline 595
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2-VL-72B-Instruct) | - Network accessline 597
| Model | Variant | Instruct (16-bit) | | ---------------- | -------------- | ------------------------------------------------------------------ | | **Mistral** | Small - Network accessline 598
| ---------------- | -------------- | ------------------------------------------------------------------ | | **Mistral** | Small 2409-22B | [link](https://huggingface.co/unsloth/Mistral-Small-Instruct-2409) | | **Mistral** | Large - Network accessline 599
| **Mistral** | Small 2409-22B | [link](https://huggingface.co/unsloth/Mistral-Small-Instruct-2409) | - Network accessline 600
| **Mistral** | Large 2407 | [link](https://huggingface.co/unsloth/Mistral-Large-Instruct-2407) | - Network accessline 601
| **Mistral** | 7B v0.3 | [link](https://huggingface.co/unsloth/mistral-7b-instruct-v0.3) | - Network accessline 602
| **Mistral** | 7B v0.2 | [link](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2) | - Network accessline 603
| **Pixtral** | 12B 2409 | [link](https://huggingface.co/unsloth/Pixtral-12B-2409) | - Network accessline 604
| **Mixtral** | 8×7B | [link](https://huggingface.co/unsloth/Mixtral-8x7B-Instruct-v0.1) | - Network accessline 605
| **Mistral NeMo** | 12B 2407 | [link](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407) | - Network accessline 606
| **Devstral** | Small 2505 | [link](https://huggingface.co/unsloth/Devstral-Small-2505) | - Network accessline 608
| Model | Variant | Instruct (16-bit) | | ----------- | -------------- | --------------------------------------------------------------- | | **Phi-4** | Reasoning-plus | [link](ht - Network accessline 609
| ----------- | -------------- | --------------------------------------------------------------- | | **Phi-4** | Reasoning-plus | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus) | | | Reasoning | [link](ht - Network accessline 610
| **Phi-4** | Reasoning-plus | [link](https://huggingface.co/unsloth/Phi-4-reasoning-plus) | - Network accessline 611
| | Reasoning | [link](https://huggingface.co/unsloth/Phi-4-reasoning) | - Network accessline 612
| | Phi-4 (core) | [link](https://huggingface.co/unsloth/Phi-4) | - Network accessline 613
| | Mini-Reasoning | [link](https://huggingface.co/unsloth/Phi-4-mini-reasoning) | - Network accessline 614
| | Mini | [link](https://huggingface.co/unsloth/Phi-4-mini) | - Network accessline 615
| **Phi-3.5** | Mini | [link](https://huggingface.co/unsloth/Phi-3.5-mini-instruct) | - Network accessline 616
| **Phi-3** | Mini | [link](https://huggingface.co/unsloth/Phi-3-mini-4k-instruct) | - Network accessline 617
| | Medium | [link](https://huggingface.co/unsloth/Phi-3-medium-4k-instruct) | - Network accessline 621
| Model | Instruct (16-bit) | | ---------------------- | ---------------------------------------------------------------- | | Orpheus-3B (v0.1 ft) | [link](https://huggingfac - Network accessline 622
| ---------------------- | ---------------------------------------------------------------- | | Orpheus-3B (v0.1 ft) | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-ft) | | Orpheus-3B (v0.1 pt) | [link](https://huggingfac - Network accessline 623
| Orpheus-3B (v0.1 ft) | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-ft) | - Network accessline 624
| Orpheus-3B (v0.1 pt) | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-pretrained) | - Network accessline 625
| Sesame-CSM 1B | [link](https://huggingface.co/unsloth/csm-1b) | - Network accessline 626
| Whisper Large V3 (STT) | [link](https://huggingface.co/unsloth/whisper-large-v3) | - Network accessline 627
| Llasa-TTS 1B | [link](https://huggingface.co/unsloth/Llasa-1B) | - Network accessline 628
| Spark-TTS 0.5B | [link](https://huggingface.co/unsloth/Spark-TTS-0.5B) | - Network accessline 629
| Oute-TTS 1B | [link](https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B) | - Network accessline 635
| Model | Variant | Base (16-bit) | Base (4-bit) | | ------------ | ----------------- | ---------- - Network accessline 636
| ------------ | ----------------- | ---------------------------------------------------------------- | -------------------------------------------------------------------------------------- | | **Gemma 3n** | E2B | [link](htt - Network accessline 637
| **Gemma 3n** | E2B | [link](https://huggingface.co/unsloth/gemma-3n-E2B) | [link](https://huggingface.co/unsloth/gemma-3n-E2B-unsloth-bnb-4bit) | - Network accessline 638
| | E4B | [link](https://huggingface.co/unsloth/gemma-3n-E4B) | [link](https://huggingface.co/unsloth/gemma-3n-E4B-unsloth-bnb-4bit) | - Network accessline 639
| **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B-Base) | [link](https://huggingface.co/unsloth/Qwen3-0.6B-Base-unsloth-bnb-4bit) | - Network accessline 640
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B-Base) | [link](https://huggingface.co/unsloth/Qwen3-1.7B-Base-unsloth-bnb-4bit) | - Network accessline 641
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B-Base) | [link](https://huggingface.co/unsloth/Qwen3-4B-Base-unsloth-bnb-4bit) | - Network accessline 642
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B-Base) | [link](https://huggingface.co/unsloth/Qwen3-8B-Base-unsloth-bnb-4bit) | - Network accessline 643
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B-Base) | [link](https://huggingface.co/unsloth/Qwen3-14B-Base-unsloth-bnb-4bit) | - Network accessline 644
| | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Base) | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Base-bnb-4bit) | - Network accessline 645
| **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E) | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-4bit) | - Network accessline 646
| | Maverick 17B 128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E) | — | - Network accessline 650
| Model | Variant | Base (16-bit) | Base (4-bit) | | ------------- | ----------------- | ----------------------------------- - Network accessline 651
| ------------- | ----------------- | ---------------------------------------------------------------- | ----------------------------------------------------------- | | **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unslo - Network accessline 652
| **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E) | — | - Network accessline 653
| | Maverick 17B 128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E) | — | - Network accessline 654
| **Llama 3.3** | 70 B | [link](https://huggingface.co/unsloth/Llama-3.3-70B) | — | - Network accessline 655
| **Llama 3.2** | 1 B | [link](https://huggingface.co/unsloth/Llama-3.2-1B) | — | - Network accessline 656
| | 3 B | [link](https://huggingface.co/unsloth/Llama-3.2-3B) | — | - Network accessline 657
| | 11 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-11B-Vision) | — | - Network accessline 658
| | 90 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-90B-Vision) | — | - Network accessline 659
| **Llama 3.1** | 8 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) | — | - Network accessline 660
| | 70 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-70B) | — | - Network accessline 661
| **Llama 3** | 8 B | [link](https://huggingface.co/unsloth/llama-3-8b) | [link](https://huggingface.co/unsloth/llama-3-8b-bnb-4bit) | - Network accessline 662
| **Llama 2** | 7 B | [link](https://huggingface.co/unsloth/llama-2-7b) | [link](https://huggingface.co/unsloth/llama-2-7b-bnb-4bit) | - Network accessline 663
| | 13 B | [link](https://huggingface.co/unsloth/llama-2-13b) | [link](https://huggingface.co/unsloth/llama-2-13b-bnb-4bit) | - Network accessline 665
| Model | Variant | Base (16-bit) | Base (4-bit) | | ------------ | ------- | ------------------------------------------------- - Network accessline 666
| ------------ | ------- | --------------------------------------------------------- | -------------------------------------------------------------------------- | | **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B- - Network accessline 667
| **Qwen 3** | 0.6 B | [link](https://huggingface.co/unsloth/Qwen3-0.6B-Base) | [link](https://huggingface.co/unsloth/Qwen3-0.6B-Base-unsloth-bnb-4bit) | - Network accessline 668
| | 1.7 B | [link](https://huggingface.co/unsloth/Qwen3-1.7B-Base) | [link](https://huggingface.co/unsloth/Qwen3-1.7B-Base-unsloth-bnb-4bit) | - Network accessline 669
| | 4 B | [link](https://huggingface.co/unsloth/Qwen3-4B-Base) | [link](https://huggingface.co/unsloth/Qwen3-4B-Base-unsloth-bnb-4bit) | - Network accessline 670
| | 8 B | [link](https://huggingface.co/unsloth/Qwen3-8B-Base) | [link](https://huggingface.co/unsloth/Qwen3-8B-Base-unsloth-bnb-4bit) | - Network accessline 671
| | 14 B | [link](https://huggingface.co/unsloth/Qwen3-14B-Base) | [link](https://huggingface.co/unsloth/Qwen3-14B-Base-unsloth-bnb-4bit) | - Network accessline 672
| | 30B-A3B | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Base) | [link](https://huggingface.co/unsloth/Qwen3-30B-A3B-Base-unsloth-bnb-4bit) | - Network accessline 673
| **Qwen 2.5** | 0.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-0.5B) | [link](https://huggingface.co/unsloth/Qwen2.5-0.5B-bnb-4bit) | - Network accessline 674
| | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2.5-1.5B) | [link](https://huggingface.co/unsloth/Qwen2.5-1.5B-bnb-4bit) | - Network accessline 675
| | 3 B | [link](https://huggingface.co/unsloth/Qwen2.5-3B) | [link](https://huggingface.co/unsloth/Qwen2.5-3B-bnb-4bit) | - Network accessline 676
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2.5-7B) | [link](https://huggingface.co/unsloth/Qwen2.5-7B-bnb-4bit) | - Network accessline 677
| | 14 B | [link](https://huggingface.co/unsloth/Qwen2.5-14B) | [link](https://huggingface.co/unsloth/Qwen2.5-14B-bnb-4bit) | - Network accessline 678
| | 32 B | [link](https://huggingface.co/unsloth/Qwen2.5-32B) | [link](https://huggingface.co/unsloth/Qwen2.5-32B-bnb-4bit) | - Network accessline 679
| | 72 B | [link](https://huggingface.co/unsloth/Qwen2.5-72B) | [link](https://huggingface.co/unsloth/Qwen2.5-72B-bnb-4bit) | - Network accessline 680
| **Qwen 2** | 1.5 B | [link](https://huggingface.co/unsloth/Qwen2-1.5B) | [link](https://huggingface.co/unsloth/Qwen2-1.5B-bnb-4bit) | - Network accessline 681
| | 7 B | [link](https://huggingface.co/unsloth/Qwen2-7B) | [link](https://huggingface.co/unsloth/Qwen2-7B-bnb-4bit) | - Network accessline 685
| Model | Variant | Base (16-bit) | Base (4-bit) | | ------------- | ----------------- | ----------------------------------- - Network accessline 686
| ------------- | ----------------- | ---------------------------------------------------------------- | ----------------------------------------------------------- | | **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unslo - Network accessline 687
| **Llama 4** | Scout 17B 16E | [link](https://huggingface.co/unsloth/Llama-4-Scout-17B-16E) | — | - Network accessline 688
| | Maverick 17B 128E | [link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E) | — | - Network accessline 689
| **Llama 3.3** | 70 B | [link](https://huggingface.co/unsloth/Llama-3.3-70B) | — | - Network accessline 690
| **Llama 3.2** | 1 B | [link](https://huggingface.co/unsloth/Llama-3.2-1B) | — | - Network accessline 691
| | 3 B | [link](https://huggingface.co/unsloth/Llama-3.2-3B) | — | - Network accessline 692
| | 11 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-11B-Vision) | — | - Network accessline 693
| | 90 B Vision | [link](https://huggingface.co/unsloth/Llama-3.2-90B-Vision) | — | - Network accessline 694
| **Llama 3.1** | 8 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) | — | - Network accessline 695
| | 70 B | [link](https://huggingface.co/unsloth/Meta-Llama-3.1-70B) | — | - Network accessline 696
| **Llama 3** | 8 B | [link](https://huggingface.co/unsloth/llama-3-8b) | [link](https://huggingface.co/unsloth/llama-3-8b-bnb-4bit) | - Network accessline 697
| **Llama 2** | 7 B | [link](https://huggingface.co/unsloth/llama-2-7b) | [link](https://huggingface.co/unsloth/llama-2-7b-bnb-4bit) | - Network accessline 698
| | 13 B | [link](https://huggingface.co/unsloth/llama-2-13b) | [link](https://huggingface.co/unsloth/llama-2-13b-bnb-4bit) | - Network accessline 700
| Model | Variant | Base (16-bit) | Base (4-bit) | | ----------- | ------- | ----------------------------------------------------- | --- - Network accessline 701
| ----------- | ------- | ----------------------------------------------------- | ---------------------------------------------------------------------- | | **Gemma 3** | 1 B | [link](https://huggingface.co/unsloth/gemma-3-1b-pt) | [li - Network accessline 702
| **Gemma 3** | 1 B | [link](https://huggingface.co/unsloth/gemma-3-1b-pt) | [link](https://huggingface.co/unsloth/gemma-3-1b-pt-unsloth-bnb-4bit) | - Network accessline 703
| | 4 B | [link](https://huggingface.co/unsloth/gemma-3-4b-pt) | [link](https://huggingface.co/unsloth/gemma-3-4b-pt-unsloth-bnb-4bit) | - Network accessline 704
| | 12 B | [link](https://huggingface.co/unsloth/gemma-3-12b-pt) | [link](https://huggingface.co/unsloth/gemma-3-12b-pt-unsloth-bnb-4bit) | - Network accessline 705
| | 27 B | [link](https://huggingface.co/unsloth/gemma-3-27b-pt) | [link](https://huggingface.co/unsloth/gemma-3-27b-pt-unsloth-bnb-4bit) | - Network accessline 706
| **Gemma 2** | 2 B | [link](https://huggingface.co/unsloth/gemma-2-2b) | — | - Network accessline 707
| | 9 B | [link](https://huggingface.co/unsloth/gemma-2-9b) | — | - Network accessline 708
| | 27 B | [link](https://huggingface.co/unsloth/gemma-2-27b) | — | - Network accessline 712
| Model | Variant | Base (16-bit) | Base (4-bit) | | ----------- | ---------------- | ----------------------------------- - Network accessline 713
| ----------- | ---------------- | ------------------------------------------------------------------ | --------------------------------------------------------------- | | **Mistral** | Small 24B 2501 | [link](https://huggingface.co/unslo - Network accessline 714
| **Mistral** | Small 24B 2501 | [link](https://huggingface.co/unsloth/Mistral-Small-24B-Base-2501) | — | - Network accessline 715
| | NeMo 12B 2407 | [link](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) | — | - Network accessline 716
| | 7B v0.3 | [link](https://huggingface.co/unsloth/mistral-7b-v0.3) | [link](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) | - Network accessline 717
| | 7B v0.2 | [link](https://huggingface.co/unsloth/mistral-7b-v0.2) | [link](https://huggingface.co/unsloth/mistral-7b-v0.2-bnb-4bit) | - Network accessline 718
| | Pixtral 12B 2409 | [link](https://huggingface.co/unsloth/Pixtral-12B-Base-2409) | — | - Network accessline 722
| Model | Variant | Base (16-bit) | Base (4-bit) | | -------------- | -------------- | ----------------- - Network accessline 723
| -------------- | -------------- | ---------------------------------------------------------------- | --------------------------------------------------------------------------------- | | **TinyLlama** | 1.1 B (Base) | [link](https://hu - Network accessline 724
| **TinyLlama** | 1.1 B (Base) | [link](https://huggingface.co/unsloth/tinyllama) | [link](https://huggingface.co/unsloth/tinyllama-bnb-4bit) | - Network accessline 725
| **Orpheus-3b** | 0.1-pretrained | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-pretrained) | [link](https://huggingface.co/unsloth/orpheus-3b-0.1-pretrained-unsloth-bnb-4bit) | - Network accessline 749
Docker might be the easiest way for Windows users to get started with Unsloth as there is no setup needed or dependency issues. [**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) is Unsloth's only Docker image. For [Blackwell - Network accessline 751
For installation instructions, please follow our [Docker guide](https://docs.unsloth.ai/new/how-to-fine-tune-llms-with-unsloth-and-docker), otherwise here is a quickstart guide: - Network accessline 758
Install Docker via [Linux](https://docs.docker.com/engine/install/) or [Desktop](https://docs.docker.com/desktop/) (other). Then install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/ins - Dangerous shell operationline 761
</strong>sudo apt-get update && sudo apt-get install -y \ - Network accessline 770
[**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) is Unsloth's only Docker image. - Network accessline 774
Go to [http://localhost:8888](http://localhost:8888/) and open Unsloth. Access the `unsloth-notebooks` tabs to see Unsloth notebooks. - Network accessline 779
If you're new, follow our step-by-step [Fine-tuning Guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide), [RL Guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) or just save/copy any of our premade [no - Network accessline 793
You should install the latest version of your GPUs driver. Download drivers here: [NVIDIA GPU Drive](https://www.nvidia.com/Download/index.aspx) - Network accessline 801
* Launch the Installer here: [Visual Studio Community Edition](https://visualstudio.microsoft.com/vs/community/) - Network accessline 825
Follow the instructions to install [CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit-archive). - Network accessline 827
Then install Miniconda (which has Python) here: [https://www.anaconda.com/docs/getting-started/miniconda/install](https://www.anaconda.com/docs/getting-started/miniconda/install#quickstart-install-instructions) - Network accessline 833
You will need the correct version of PyTorch that is compatible with your CUDA drivers, so make sure to select them carefully. [Install PyTorch](https://pytorch.org/get-started/locally/) - Network accessline 850
* Install Triton from this Windows fork and follow the instructions [here](https://github.com/woct0rdho/triton-windows) (be aware that the Windows fork requires PyTorch >= 2.4 and CUDA 12) - Network accessline 857
1. Install `torch` and `triton`. Go to <https://pytorch.org> to install it. For example `pip install torch torchvision torchaudio triton` - Network accessline 858
2. Confirm if CUDA is installated correctly. Try `nvcc`. If that fails, you need to install `cudatoolkit` or CUDA drivers. 3. Install `xformers` manually. You can try installing `vllm` and seeing if `vllm` succeeds. Check if `xformers` succ - Network accessline 859
3. Install `xformers` manually. You can try installing `vllm` and seeing if `vllm` succeeds. Check if `xformers` succeeded with `python -m xformers.info` Go to <https://github.com/facebookresearch/xformers>. Another option is to install `fl - Network accessline 860
4. Double check that your versions of Python, CUDA, CUDNN, `torch`, `triton`, and `xformers` are compatible with one another. The [PyTorch Compatibility Matrix](https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-m - Network accessline 867
1. **Install NVIDIA CUDA Toolkit**: * Download and install the appropriate version of the **NVIDIA CUDA Toolkit** from [CUDA Downloads](https://developer.nvidia.com/cuda-downloads). - Network accessline 868
* Download and install the appropriate version of the **NVIDIA CUDA Toolkit** from [CUDA Downloads](https://developer.nvidia.com/cuda-downloads). - Network accessline 870
* **Note**: No additional setup is required after installation for Unsloth. 2. **Install Microsoft C++ Build Tools**: * Download and install **Microsoft Build Tools for Visual Studio** from the [official website](https://visualstudio.mic - Network accessline 871
2. **Install Microsoft C++ Build Tools**: * Download and install **Microsoft Build Tools for Visual Studio** from the [official website](https://visualstudio.microsoft.com/visual-cpp-build-tools/). * During installation, select the ** - Network accessline 872
* Download and install **Microsoft Build Tools for Visual Studio** from the [official website](https://visualstudio.microsoft.com/visual-cpp-build-tools/). - Network accessline 886
* Verify: Open a new terminal and type `cl`. It should show version info. 4. **Install Conda** 1. Download and install **Miniconda** from the [official website](https://docs.anaconda.com/miniconda/install/#quick-command-line-install) - Network accessline 887
4. **Install Conda** 1. Download and install **Miniconda** from the [official website](https://docs.anaconda.com/miniconda/install/#quick-command-line-install) 2. Follow installation instruction from the website - Network accessline 888
1. Download and install **Miniconda** from the [official website](https://docs.anaconda.com/miniconda/install/#quick-command-line-install) - Network accessline 894
1. **Download the** [**unsloth\_windows.ps1**](https://github.com/unslothai/notebooks/blob/main/unsloth_windows.ps1) **PowerShell script by going through this link**. - Network accessline 911
1. Install python though [Python's official site](https://www.python.org/downloads/windows/). - Network accessline 958
pip install "unsloth[windows] @ git+https://github.com/unslothai/unsloth.git" - Network accessline 1014
{% hint style="info" %} Please see <https://docs.unsloth.ai/basics/deepseek-r1-0528-how-to-run-locally> (May 28th 2025 update) to learn on how to run DeepSeek faster and more efficiently! - Network accessline 1015
Please see <https://docs.unsloth.ai/basics/deepseek-r1-0528-how-to-run-locally> (May 28th 2025 update) to learn on how to run DeepSeek faster and more efficiently! - Network accessline 1022
<table data-full-width="true"><thead><tr><th>MoE Bits</th><th>Type</th><th>Disk Size</th><th>Accuracy</th><th>Link</th><th>Details</th></tr></thead><tbody><tr><td>1.78bit</td><td>IQ1_S</td><td><strong>173GB</strong></td><td>Ok</td><td><a hr - Network accessline 1030
According to [DeepSeek](https://huggingface.co/deepseek-ai/DeepSeek-V3-0324), these are the recommended settings for inference: - Network accessline 1032
* <mark style="background-color:blue;">**Temperature of 0.3**</mark> (Maybe 0.0 for coding as [seen here](https://api-docs.deepseek.com/quick_start/parameter_settings)) - Network accessline 1041
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 1047
2. Download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose `UD-IQ1_S`(dynamic 1.78bit quant) or other quantized versions like `Q4_K_M` . <mark style="background-color:green;">**I recommend using - Network accessline 1055
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1056
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1057
git clone https://github.com/ggml-org/llama.cpp - Network accessline 1081
> **Try QAT with our free** [**Qwen3 (4B) notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) - Network accessline 1096
[Credential-related source omitted] - Network accessline 1100
Dequantizing back to 16bits simply does the reverse operation by `float16(qW) / a` . Post-training quantization (PTQ) can greatly reduce storage and inference costs, but quite often degrades accuracy when representing high-precision values - Network accessline 1104
[Credential-related source omitted] - Network accessline 1106
To enable smarter quantization, we collaborated with the [TorchAO](https://github.com/pytorch/ao) team to add **Quantization-Aware Training (QAT)** directly inside of Unsloth - so now you can fine-tune models in Unsloth and then export them - Network accessline 1116
[Credential-related source omitted] - Network accessline 1176
Qwen released 2507 (July 2025) updates for their [Qwen3](https://docs.unsloth.ai/models/qwen3-how-to-run-and-fine-tune) 4B, 30B and 235B models, introducing both "thinking" and "non-thinking" variants. The non-thinking '**Qwen3-30B-A3B-Inst - Network accessline 1180
[Unsloth](https://github.com/unslothai/unsloth) also now supports fine-tuning and [Reinforcement Learning (RL)](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) of Qwen3-2507 models — 2x faster, with 70% less VRAM, and 8 - Network accessline 1184
**Unsloth** [**Dynamic 2.0**](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) **GGUFs:** - Network accessline 1186
| Model | GGUFs to run: | | ------------------------ | ---------------------- - Network accessline 1187
| ------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Qwen3-**4B-2507** | [Instruct](https://hug - Network accessline 1188
| Qwen3-**4B-2507** | [Instruct](https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-GGUF) • [Thinking ](https://huggingface.co/unsloth/Qwen3-4B-Thinking-2507-GGUF) | - Network accessline 1189
| Qwen3-**30B-A3B**-2507 | [Instruct](#llama.cpp-run-qwen3-30b-a3b-instruct-2507-tutorial) • [Thinking](https://huggingface.co/unsloth/Qwen3-30B-A3B-Thinking-2507-GGUF) | - Network accessline 1190
| Qwen3-**235B-A22B**-2507 | [Instruct](https://huggingface.co/unsloth/Qwen3-235B-A22B-Instruct-2507-GGUF) • [Thinking](https://huggingface.co/unsloth/Qwen3-235B-A22B-Thinking-2507-GGUF) | - Network accessline 1240
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 1261
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 1263
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 1263
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 1273
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1274
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1275
git clone https://github.com/ggml-org/llama.cpp - Access to secretsline 1331
[Credential-related source omitted] - Access to secretsline 1352
[Credential-related source omitted] - Network accessline 1395
curl -X POST http://localhost:8000/v1/load_lora_adapter \ - Network accessline 1405
curl -X POST http://localhost:8000/v1/unload_lora_adapter \ - Network accessline 1436
* E.g. For image-based training, select a vision model such as *Llama 3.2 Vision*. For code datasets, opt for a specialized model like *Qwen Coder 2.5*. * **Licensing and Requirements**: Different models may have specific licensing terms an - Network accessline 1437
* **Licensing and Requirements**: Different models may have specific licensing terms and [system requirements](https://docs.unsloth.ai/beginner-start-here/unsloth-requirements#system-requirements). Be sure to review these carefully to avoid - Network accessline 1442
* Use our [VRAM guideline](https://docs.unsloth.ai/beginner-start-here/unsloth-requirements#approximate-vram-requirements-based-on-model-parameters) to determine the VRAM requirements for the model you’re considering. - Network accessline 1448
* We recommend using the latest model for the best performance and capabilities. For instance, as of January 2025, the leading 70B model is *Llama 3.3*. * You can stay up to date by exploring our [model catalog](https://docs.unsloth.ai/get- - Network accessline 1449
* You can stay up to date by exploring our [model catalog](https://docs.unsloth.ai/get-started/all-our-models) to find the newest and relevant options. - Network accessline 1464
Base models, on the other hand, are the original pre-trained versions without instruction fine-tuning. These are specifically designed for customization through fine-tuning, allowing you to adapt them to your unique needs. Base models are c - Network accessline 1471
* **300–1,000 Rows of High-Quality Data**: With a medium-sized, high-quality dataset, fine-tuning the base or instruct model are both viable options. * **Less than 300 Rows**: For smaller datasets, the instruct model is typically the better - Network accessline 1473
* For information how how big your dataset should be, [see here](https://docs.unsloth.ai/get-started/datasets-guide#how-big-should-my-dataset-be) - Network accessline 1481
* Model names ending in **`unsloth-bnb-4bit`** indicate they are [**Unsloth dynamic 4-bit**](https://unsloth.ai/blog/dynamic-4bit) **quants**. These models consume slightly more VRAM than standard BitsAndBytes 4-bit models but offer signifi - Network accessline 1507
[Credential-related source omitted] - Network accessline 1538
* You can use our [Magistral-2509 Kaggle notebook](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/magistral-how-to-run-and-fine-tune#fine-tuning-magistral-with-unsloth) as an example which utilizes multi-GPU Unsloth - Network accessline 1551
* [unsloth-5090-multiple](https://github.com/thad0ctor/unsloth-5090-multiple): A fork enabling Unsloth to run efficiently on multi-GPU systems, particularly for the NVIDIA [RTX 5090](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blac - Network accessline 1552
* [opensloth](https://github.com/anhvth/opensloth): Unsloth with support for multi-GPU training including experimental features. - Network accessline 1554
**Stay tuned for our official announcement!**\ For more details, check out our ongoing [Pull Request](https://github.com/unslothai/unsloth/issues/2435) discussing multi-GPU support. - Network accessline 1555
For more details, check out our ongoing [Pull Request](https://github.com/unslothai/unsloth/issues/2435) discussing multi-GPU support. - Network accessline 1581
If you're a beginner, here might be the first questions you'll ask before your first fine-tune. You can also always ask our community by joining our [Reddit page](https://www.reddit.com/r/unsloth/). - Network accessline 1585
[Credential-related source omitted] - Network accessline 1593
uv pip install -U vllm --pre --extra-index-url https://wheels.vllm.ai/nightly - Network accessline 1661
Unsloth supports natively 2x faster inference. For our inference only notebook, click [here](https://colab.research.google.com/drive/1aqlNQi7MMJbynFDyOQteD2t0yVfjb9Zh?usp=sharing). - Network accessline 1679
Sometimes when you execute a cell [this error](https://github.com/googlecolab/colabtools/issues/3409) can appear. To solve this, in a new cell, run the below: - Network accessline 1700
{% hint style="success" %} Please see <https://docs.unsloth.ai/basics/deepseek-r1-0528-how-to-run-locally> for an updated DeepSeek R1-0528 (May 28th 2025 version) - Network accessline 1701
Please see <https://docs.unsloth.ai/basics/deepseek-r1-0528-how-to-run-locally> for an updated DeepSeek R1-0528 (May 28th 2025 version) - Network accessline 1706
1. Do not forget about `<｜User｜>` and `<｜Assistant｜>` tokens! - Or use a chat template formatter 2. Obtain the latest `llama.cpp` at: [github.com/ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp). You can follow the build instruc - Network accessline 1707
2. Obtain the latest `llama.cpp` at: [github.com/ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp). You can follow the build instructions below as well: - Network accessline 1716
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1717
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 1718
git clone https://github.com/ggerganov/llama.cpp - Network accessline 1770
[Credential-related source omitted] - Network accessline 1776
[Credential-related source omitted] - Network accessline 1799
[Credential-related source omitted] - Network accessline 1801
This means the memory space for inference and training can in theory be re-used, since inference and training are separate modes - this is where [vLLM's sleep mode feature](https://docs.vllm.ai/en/latest/features/sleep_mode.html#rlhf-weight - Network accessline 1828
[Credential-related source omitted] - Network accessline 1834
[Credential-related source omitted] - Network accessline 1838
<table data-full-width="true"><thead><tr><th>Experiments</th><th>Config</th><th>Status</th><th>GPU Memory usage</th><th>Comments</th></tr></thead><tbody><tr><td><ol><li><a href="https://colab.research.google.com/drive/18CssBY5C0mStnLvu2Hlt4 - Network accessline 1850
[Credential-related source omitted] - Network accessline 1856
[Credential-related source omitted] - Network accessline 1860
We now select better compilation flags and reduce compile times by 50% or more. We also managed to dynamically patch any vLLM version to handle `gc.collect` better for backwards compatibility reasons, as inspired from this [vLLM pull reques - Network accessline 1866
All our GRPO notebooks have Unsloth Standby on by default and all optimizations! See <https://docs.unsloth.ai/get-started/unsloth-notebooks> for all our GRPO notebooks, or try the below: - Network accessline 1868
* [**Qwen3 (4B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) **-** Advanced GRPO LoRA - Network accessline 1869
* [**DeepSeek-R1-0528-Qwen3 (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DeepSeek_R1_0528_Qwen3_\(8B\)_GRPO.ipynb) (for multilingual usecases) - Network accessline 1870
* [Gemma 3 (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(1B\)-GRPO.ipynb) - Network accessline 1871
* [Llama 3.2 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Advanced_Llama3_2_\(3B\)_GRPO_LoRA.ipynb) - Advanced GRPO LoRA - Network accessline 1872
* [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-GRPO.ipynb) - Network accessline 1873
* [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4_\(14B\)-GRPO.ipynb) - Network accessline 1874
* [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-GRPO.ipynb) - Network accessline 1875
* [Qwen2.5 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_\(3B\)-GRPO.ipynb) - Access to secretsline 1882
[Credential-related source omitted] - Access to secretsline 1899
[Credential-related source omitted] - Network accessline 2027
{% hint style="warning" %} If you're having issues with your GRPO model not learning, we'd highly recommend to use our [Advanced GRPO notebooks](https://docs.unsloth.ai/unsloth-notebooks#grpo-reasoning-notebooks) as it has a much better rew - Network accessline 2028
If you're having issues with your GRPO model not learning, we'd highly recommend to use our [Advanced GRPO notebooks](https://docs.unsloth.ai/unsloth-notebooks#grpo-reasoning-notebooks) as it has a much better reward function and you should - Network accessline 2033
[Credential-related source omitted] - Network accessline 2045
[Credential-related source omitted] - Network accessline 2049
You can then save your model to GGUF, Ollama etc. by following our [guide here](https://docs.unsloth.ai/fine-tuning-llms-guide#id-7.-running--saving-the-model). - Network accessline 2051
[Credential-related source omitted] - Network accessline 2060
We have multiple options for saving your fine-tuned model, but we’ll focus on the easiest and most popular approaches which you can read more about [here](https://docs.unsloth.ai/basics/running-and-saving-models) - Network accessline 2095
Install the latest PyTorch, TorchAO, Xformers from <https://pytorch.org/> - Network accessline 2113
And that's it! Try some examples in our [**Unsloth Notebooks**](https://docs.unsloth.ai/get-started/unsloth-notebooks) page! - Network accessline 2117
You can use our :ledger:[gpt-oss RL auto win 2048](https://github.com/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game_BF16.ipynb) example on a MI300X (192GB) GPU. The goal is to play the 2048 game automatic - Network accessline 2122
[Credential-related source omitted] - Network accessline 2130
[Credential-related source omitted] - Network accessline 2137
[Credential-related source omitted] - Network accessline 2139
You can also use our :ledger:[automatic kernel gen RL notebook](https://github.com/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_GRPO_BF16.ipynb) also with gpt-oss to auto create matrix multiplication kernels in Python. The notebook also - Network accessline 2159
[Credential-related source omitted] - Network accessline 2169
AMD GPUs also need the bitsandbytes `blocksize` to be 128 and not 64 - this also means our pre-quantized models (for example [unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-bnb-4bit)) fr - Network accessline 2183
pip install --upgrade torch==2.8.0 pytorch-triton-rocm torchvision torchaudio torchao==0.13.0 xformers --index-url https://download.pytorch.org/whl/rocm6.4 - Network accessline 2188
pip install --no-deps unsloth unsloth-zoo pip install --no-deps git+https://github.com/unslothai/unsloth-zoo.git - Network accessline 2189
pip install --no-deps git+https://github.com/unslothai/unsloth-zoo.git - Network accessline 2190
pip install "unsloth[amd] @ git+https://github.com/unslothai/unsloth" - Network accessline 2394
[Credential-related source omitted] - Network accessline 2428
bash NOTEBOOK_URL="https://raw.githubusercontent.com/unslothai/notebooks/refs/heads/main/nb/gpt_oss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.ipynb" wget -O "gpt_oss_20B_RL_2048_Game.ipynb" "$NOTEBOOK_URL" - Network accessline 2429
NOTEBOOK_URL="https://raw.githubusercontent.com/unslothai/notebooks/refs/heads/main/nb/gpt_oss_(20B)_Reinforcement_Learning_2048_Game_DGX_Spark.ipynb" - Network accessline 2430
wget -O "gpt_oss_20B_RL_2048_Game.ipynb" "$NOTEBOOK_URL" - Network accessline 2435
[Credential-related source omitted] - Network accessline 2437
Don't forget Unsloth also allows you to [save and run](https://docs.unsloth.ai/basics/running-and-saving-models) your models after fine-tuning so you can locally deploy them directly on your DGX Spark after. - Network accessline 2441
Many thanks to [Lakshmi Ramesh](https://www.linkedin.com/in/rlakshmi24/) and [Barath Anandan](https://www.linkedin.com/in/barathsa/) from NVIDIA for helping Unsloth’s DGX Spark launch and building the Docker image. - Network accessline 2447
[Credential-related source omitted] - Network accessline 2451
Thanks to Tim from [AnythingLLM](https://github.com/Mintplex-Labs/anything-llm) for providing a great fine-tuning tutorial with Unsloth on DGX Spark: - Network accessline 2453
{% embed url="<https://www.youtube.com/watch?t=962s&v=zs-J9sKxvoM>" %} - Network accessline 2471
[Credential-related source omitted] - Network accessline 2478
Inside the container, start Jupyter and run the required notebook. You can use the Reinforcement Learning gpt-oss 20b to win 2048 [notebook here](https://github.com/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_204 - Network accessline 2480
[Credential-related source omitted] - Network accessline 2504
</strong> "unsloth/gpt-oss-20b", # 20B model using MXFP4 format "unsloth/gpt-oss-120b", ] # More models at https://huggingface.co/unsloth - Network accessline 2506
] # More models at https://huggingface.co/unsloth - Network accessline 2523
Now it's time to adjust your training hyperparameters. For a deeper dive into how, when, and what to tune, check out our [detailed hyperparameters guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Network accessline 2525
{% hint style="info" %} To avoid [overfitting](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting), monitor your training loss and avoid setting these values too high. - Network accessline 2526
To avoid [overfitting](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting), monitor your training loss and avoid setting these values too high.  - Network accessline 2531
For this example, we will use the [`HuggingFaceH4/Multilingual-Thinking`](https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking). This dataset contains chain-of-thought reasoning examples derived from user questions translated - Network accessline 2541
[Credential-related source omitted] - Network accessline 2543
One unique feature of gpt-oss is its use of the [**OpenAI Harmony format**](https://github.com/openai/harmony)**,** which supports structured conversations, reasoning output, and tool calling. This format includes tags such as `<|start|>` , - Network accessline 2545
{% hint style="info" %} 🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 2546
🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 2549
Feel free to adapt the prompt and structure to suit your own dataset or use-case. For more guidance, refer to our [dataset guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide). - Network accessline 2552
We've pre-selected training hyperparameters for optimal results. However, you can modify them based on your specific use case. Refer to our [hyperparameters guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparamet - Network accessline 2558
[Credential-related source omitted] - Network accessline 2569
[Credential-related source omitted] - Network accessline 2586
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 2599
As always, feel free to drop by our [Discord](https://discord.com/invite/unsloth) or [Reddit](https://www.reddit.com/r/unsloth/) if you need any help. - Network accessline 2605
Yes you can now [save/export your gpt-oss fine-tuned](https://docs.unsloth.ai/models/long-context-gpt-oss-training#new-saving-to-gguf-vllm-after-gpt-oss-training) model using Unsloth's new update! - Network accessline 2617
Yes! Unsloth now supports RL for gpt-oss with GRPO/GSPO. We made it work on a free Kaggle notebook and achieved the fastest inference for RL. [Read more here](https://docs.unsloth.ai/new/gpt-oss-reinforcement-learning) - Network accessline 2619
***Acknowledgements:** A huge thank you to* [*Eyera*](https://huggingface.co/Orenguteng) *for contributing to this guide!* - Network accessline 2686
* The [text completion notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_\(7B\)-Text_Completion.ipynb) is for continued pretraining/raw text. - Network accessline 2687
* The [continued pretraining notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb) is for learning another language. - Network accessline 2689
You can read more about continued pretraining and our release in our [blog post](https://unsloth.ai/blog/contpretraining). - Network accessline 2996
1. We find using lower KV cache quantization (4bit) seems to degrade generation quality via empirical tests - more tests need to be done, but we suggest using `q8_0` cache quantization. The goal of quantization is to support longer context - Network accessline 2997
2. We found the `down_proj` in this model to be extremely sensitive to quantitation. We had to redo some of our dyanmic quants which used 2bits for `down_proj` and now we use 3bits as the minimum for all these matrices. 3. Using `llama.cpp` - Network accessline 2998
3. Using `llama.cpp` 's Flash Attention backend does result in somewhat faster decoding speeds. Use `-DGGML_CUDA_FA_ALL_QUANTS=ON` when compiling. Note it's also best to set your CUDA architecture as found in <https://developer.nvidia.com/c - Network accessline 3023
Kimi-K2-Instruct-0905 the new version of K2 achieves SOTA performance in knowledge, reasoning, coding, and agentic tasks. The full 1T parameter model from Moonshot AI requires 1.09TB of disk space, while the quantized **Unsloth Dynamic 1.8- - Network accessline 3025
You can now run **Kimi-K2-Instruct-0905** with our new GGUFs. Use our same settings below but ensure you change the model name from 'Kimi-K2-Instruct' to 'Kimi-K2-Instruct-0905': [K2-0905 GGUFs](https://huggingface.co/unsloth/Kimi-K2-Instru - Network accessline 3027
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run quantized LLMs with minimal accuracy loss. - Network accessline 3029
<a href="https://docs.unsloth.ai/basics/kimi-k2-how-to-run-locally#run-kimi-k2-tutorials" class="button primary">Run in llama.cpp</a> - Network accessline 3053
According to [Moonshot AI](https://huggingface.co/moonshotai/Kimi-K2-Instruct), these are the recommended settings for Kimi K2 inference: - Network accessline 3078
<table data-full-width="false"><thead><tr><th>MoE Bits</th><th>Type + Link</th><th>Disk Size</th><th>Details</th></tr></thead><tbody><tr><td>1.66bit</td><td><a href="https://huggingface.co/unsloth/Kimi-K2-Instruct-GGUF/tree/main/UD-TQ1_0">U - Network accessline 3080
We've also uploaded versions in [BF16 format](https://huggingface.co/unsloth/Kimi-K2-Instruct-BF16). - Network accessline 3084
{% hint style="success" %} You can now use the latest update of [llama.cpp](https://github.com/ggml-org/llama.cpp) to run the model: - Network accessline 3085
You can now use the latest update of [llama.cpp](https://github.com/ggml-org/llama.cpp) to run the model: - Network accessline 3090
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 3106
3. Download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose `UD-TQ1_0`(dynamic 1.8bit quant) or other quantized versions like `Q2_K_XL` . We <mark style="background-color:green;">**recommend using - Network accessline 3146
Also see our GitHub repo for our notebooks: [github.com/unslothai/notebooks](https://github.com/unslothai/notebooks/) - Network accessline 3152
* [**gpt-oss (20b)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-Fine-tuning.ipynb) • [Inference](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\) - Network accessline 3153
* [**DeepSeek-OCR**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\).ipynb) **- new** - Network accessline 3154
* [Qwen3 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) • [**Qwen3-VL (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL - Network accessline 3155
* [**Qwen3-2507-4B**](https://docs.unsloth.ai/models/qwen3-how-to-run-and-fine-tune/qwen3-2507) • [Thinking](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-Thinking.ipynb) • [Instruct](https://colab.r - Network accessline 3156
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) • [Text](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversation - Network accessline 3157
* [IBM Granite-4.0-H](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb) - new - Network accessline 3158
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) • [Text](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) • [Vision](https://colab - Network accessline 3159
* [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb)  - Network accessline 3160
* [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-Alpaca.ipynb) • [Llama 3.2 (1B + 3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3 - Network accessline 3164
* [**gpt-oss-20b**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) (automatic kernels creation) - new - Network accessline 3165
* [**gpt-oss-20b**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) (auto win 2048 game) - new - Network accessline 3166
* [**Qwen3-VL (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - Vision **GSPO** - new - Network accessline 3167
* [Qwen3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) **-** Advanced GRPO LoRA - Network accessline 3168
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - Vision GSPO - new - Network accessline 3169
* [**DeepSeek-R1-0528-Qwen3 (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DeepSeek_R1_0528_Qwen3_\(8B\)_GRPO.ipynb) (for multilingual usecase) - Network accessline 3170
* [Gemma 3 (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(1B\)-GRPO.ipynb) - Network accessline 3171
* [Llama 3.2 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Advanced_Llama3_2_\(3B\)_GRPO_LoRA.ipynb) - Advanced GRPO LoRA - Network accessline 3172
* [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-GRPO.ipynb) - Network accessline 3173
* [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4_\(14B\)-GRPO.ipynb)  - Network accessline 3174
* [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-GRPO.ipynb) - Network accessline 3178
* [Sesame-CSM (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Sesame_CSM_\(1B\)-TTS.ipynb) - new - Network accessline 3179
* [Orpheus-TTS (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Orpheus_\(3B\)-TTS.ipynb) - Network accessline 3180
* [Whisper Large V3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Whisper.ipynb) - Speech-to-Text (STT) - Network accessline 3181
* [Llasa-TTS (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llasa_TTS_\(1B\).ipynb) - Network accessline 3182
* [Spark-TTS (0.5B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Spark_TTS_\(0_5B\).ipynb) - Network accessline 3183
* [Oute-TTS (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Oute_TTS_\(1B\).ipynb) - Network accessline 3187
* [Whisper-Large-V3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Whisper.ipynb) - Network accessline 3188
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Audio.ipynb) - Audio - Network accessline 3192
* [**Qwen3-VL (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision.ipynb) **- new** - Network accessline 3193
* [**DeepSeek-OCR**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\).ipynb) **- new** - Network accessline 3194
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision.ipynb) - vision - Network accessline 3195
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) - vision - Network accessline 3196
* [Llama 3.2 Vision (11B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb) - Network accessline 3197
* [Qwen2.5-VL (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_VL_\(7B\)-Vision.ipynb) - Network accessline 3198
* [Pixtral (12B) 2409](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Pixtral_\(12B\)-Vision.ipynb) - Network accessline 3199
* [Qwen3-VL](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - Vision GSPO - new - Network accessline 3200
* [Qwen2.5-VL](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_GRPO.ipynb) - Vision GSPO - Network accessline 3201
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - Vision GSPO - new - Network accessline 3211
* [gpt-oss-120b ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(120B\)_A100-Fine-tuning.ipynb)- new - Network accessline 3212
* [Qwen3 (32B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(32B\)_A100-Reasoning-Conversational.ipynb) - new - Network accessline 3213
* [Llama 3.3 (70B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.3_\(70B\)_A100-Conversational.ipynb) - new - Network accessline 3214
* [Gemma 3 (27B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(27B\)_A100-Conversational.ipynb) - new - Network accessline 3218
* [**Customer support agent**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb) **- new** - Network accessline 3219
* [**Automatic Kernel Creation**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) with RL **- new** - Network accessline 3220
* [**ModernBERT-large**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) **- new** as of Aug 19 - Network accessline 3221
* [**Synthetic Data Generation Llama 3.2 (3B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Meta_Synthetic_Data_Llama3_2_\(3B\).ipynb) - new - Network accessline 3222
* [**Tool Calling**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb) **- new** - Network accessline 3223
* [**Customer support agent**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb) **- new** - Network accessline 3224
* [Mistral v0.3 Instruct (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb) - Network accessline 3225
* [Ollama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb) - Network accessline 3226
* [ORPO](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-ORPO.ipynb) - Network accessline 3227
* [Continued Pretraining](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb) - Network accessline 3228
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb) - Network accessline 3229
* [***Inference only***](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-Inference.ipynb) - Network accessline 3230
* [Llama 3 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Alpaca.ipynb) - Network accessline 3234
* [**Customer support agent**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb) **- new** - Network accessline 3235
* [**Automatic Kernel Creation**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) with RL **- new** - Network accessline 3236
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb) - Network accessline 3237
* [**BERT - Text Classification**](https://colab.research.google.com/github/timothelaborie/text_classification_scripts/blob/main/unsloth_classification.ipynb) **- new as of Aug 19** - Network accessline 3238
* [Ollama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb) - Network accessline 3239
* [**Tool Calling**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb) **- new** - Network accessline 3240
* [Continued Pretraining (CPT)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb) - Network accessline 3241
* [Multiple Datasets](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) by Flail - Network accessline 3242
* [KTO](https://colab.research.google.com/drive/1MRgGtLWuZX4ypSfGguFgC-IblTvO2ivM?usp=sharing) by Jeffrey - Network accessline 3243
* [Inference chat UI](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Unsloth_Studio.ipynb) - Network accessline 3244
* [Conversational](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 3245
* [ChatML](https://colab.research.google.com/drive/15F1xyn8497_dUbxZP4zWmPZ3PJx1Oymv?usp=sharing) - Network accessline 3246
* [Text Completion](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_\(7B\)-Text_Completion.ipynb) - Network accessline 3250
* [Qwen2.5 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_\(3B\)-GRPO.ipynb) - Network accessline 3251
* [Gemma 2 (9B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma2_\(9B\)-Alpaca.ipynb) - Network accessline 3252
* [Mistral NeMo (12B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_Nemo_\(12B\)-Alpaca.ipynb) - Network accessline 3253
* [Phi-3.5 (mini)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_3.5_Mini-Conversational.ipynb) - Network accessline 3254
* [Phi-3 (medium)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_3_Medium-Conversational.ipynb) - Network accessline 3255
* [Gemma 2 (2B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma2_\(2B\)-Alpaca.ipynb) - Network accessline 3256
* [Qwen 2.5 Coder (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(14B\)-Conversational.ipynb) - Network accessline 3257
* [Mistral Small (22B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_Small_\(22B\)-Alpaca.ipynb) - Network accessline 3258
* [TinyLlama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/TinyLlama_\(1.1B\)-Alpaca.ipynb) - Network accessline 3259
* [CodeGemma (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/CodeGemma_\(7B\)-Conversational.ipynb) - Network accessline 3260
* [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Alpaca.ipynb) - Network accessline 3261
* [Qwen2 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_\(7B\)-Alpaca.ipynb) - Network accessline 3265
* [**gpt-oss (20B)**](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-gpt-oss-\(20B\)-Fine-tuning.ipynb\&accelerator=nvidiaTeslaT4) **- new** - Network accessline 3266
* [Gemma 3n (E4B)](https://www.kaggle.com/code/danielhanchen/gemma-3n-4b-multimodal-finetuning-inference) - Network accessline 3267
* [Qwen3 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen3_\(14B\).ipynb) - Network accessline 3268
* [Magistral-2509 (24B)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Magistral_\(24B\)-Reasoning-Conversational.ipynb\&accelerator=nvidiaTeslaT4) - new - Network accessline 3269
* [Gemma 3 (4B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma3_\(4B\).ipynb) - Network accessline 3270
* [Phi-4 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Phi_4-Conversational.ipynb) - Network accessline 3271
* [Llama 3.1 (8B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-Alpaca.ipynb) - Network accessline 3272
* [Llama 3.2 (1B + 3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 3273
* [Qwen 2.5 (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_\(7B\)-Alpaca.ipynb) - Network accessline 3277
* [**Qwen2.5-VL**](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen2_5_7B_VL_GRPO.ipynb\&accelerator=nvidiaTeslaT4) - Vision GRPO - new - Network accessline 3278
* [Qwen3 (4B)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen3_\(4B\)-GRPO.ipynb\&accelerator=nvidiaTeslaT4) - Network accessline 3279
* [Gemma 3 (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma3_\(1B\)-GRPO.ipynb) - Network accessline 3280
* [Llama 3.1 (8B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-GRPO.ipynb) - Network accessline 3281
* [Phi-4 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Phi_4_\(14B\)-GRPO.ipynb) - Network accessline 3282
* [Qwen 2.5 (3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_\(3B\)-GRPO.ipynb) - Network accessline 3286
* [Sesame-CSM (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Sesame_CSM_\(1B\)-TTS.ipynb) - Network accessline 3287
* [Orpheus-TTS (3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Orpheus_\(3B\)-TTS.ipynb) - Network accessline 3288
* [Whisper Large V3](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Whisper.ipynb) – Speech-to-Text - Network accessline 3289
* [Llasa-TTS (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llasa_TTS_\(1B\).ipynb) - Network accessline 3290
* [Spark-TTS (0.5B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Spark_TTS_\(0_5B\).ipynb) - Network accessline 3291
* [Oute-TTS (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Oute_TTS_\(1B\).ipynb) - Network accessline 3295
* [Llama 3.2 Vision (11B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.2_\(11B\)-Vision.ipynb) - Network accessline 3296
* [Qwen 2.5-VL (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_VL_\(7B\)-Vision.ipynb) - Network accessline 3297
* [Pixtral (12B) 2409](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Pixtral_\(12B\)-Vision.ipynb) - Network accessline 3301
* [Tool Calling](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb\&accelerator=nvidiaTeslaT4) - Network accessline 3302
* [ORPO](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3_\(8B\)-ORPO.ipynb) - Network accessline 3303
* [Continued Pretraining](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_v0.3_\(7B\)-CPT.ipynb) - Network accessline 3304
* [DPO Zephyr](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Zephyr_\(7B\)-DPO.ipynb) - Network accessline 3305
* [Inference only](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-Inference.ipynb) - Network accessline 3306
* [Ollama](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3_\(8B\)-Ollama.ipynb) - Network accessline 3307
* [Text Completion](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_\(7B\)-Text_Completion.ipynb) - Network accessline 3308
* [CodeForces-cot (Reasoning)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-CodeForces-cot-Finetune_for_Reasoning_on_CodeForces.ipynb) - Network accessline 3309
* [Unsloth Studio (chat UI)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Unsloth_Studio.ipynb) - Network accessline 3313
* [Gemma 2 (9B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma2_\(9B\)-Alpaca.ipynb) - Network accessline 3314
* [Gemma 2 (2B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma2_\(2B\)-Alpaca.ipynb) - Network accessline 3315
* [CodeGemma (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-CodeGemma_\(7B\)-Conversational.ipynb) - Network accessline 3316
* [Mistral NeMo (12B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_Nemo_\(12B\)-Alpaca.ipynb) - Network accessline 3317
* [Mistral Small (22B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_Small_\(22B\)-Alpaca.ipynb) - Network accessline 3318
* [TinyLlama (1.1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-TinyLlama_\(1.1B\)-Alpaca.ipynb) - Network accessline 3320
To view a complete list of all our Kaggle notebooks, [click here](https://github.com/unslothai/notebooks#-kaggle-notebooks). - Network accessline 3322
{% hint style="info" %} Feel free to contribute to the notebooks by visiting our [repo](https://github.com/unslothai/notebooks)! - Network accessline 3323
Feel free to contribute to the notebooks by visiting our [repo](https://github.com/unslothai/notebooks)! - Network accessline 3334
{% hint style="warning" %} Only use Conda if you have it. If not, use [Pip](https://docs.unsloth.ai/get-started/install-and-update/pip-install). - Network accessline 3335
Only use Conda if you have it. If not, use [Pip](https://docs.unsloth.ai/get-started/install-and-update/pip-install). - Network accessline 3340
If you're looking to install Conda in a Linux environment, [read here](https://docs.anaconda.com/miniconda/), or run the below: - Network accessline 3358
mkdir -p ~/miniconda3 wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh - Network accessline 3359
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh - Dangerous shell operationline 3361
rm -rf ~/miniconda3/miniconda.sh - Network accessline 3392
You can also run your fine-tuned models by using [Unsloth's 2x faster inference](https://docs.unsloth.ai/basics/running-and-saving-models/unsloth-inference). - Network accessline 3404
Unsloth now supports vision/multimodal RL with [Qwen3-VL](https://docs.unsloth.ai/models/qwen3-vl-how-to-run-and-fine-tune), [Gemma 3](https://docs.unsloth.ai/models/gemma-3-how-to-run-and-fine-tune) and more. Due to Unsloth's unique [weigh - Network accessline 3406
Unsloth can train Qwen3-VL-8B with GSPO/GRPO on a free Colab T4 GPU. Other VLMs work too, but may need larger GPUs. Gemma requires newer GPUs than T4 because vLLM [restricts to Bfloat16](https://docs.unsloth.ai/models/gemma-3-how-to-run-and - Network accessline 3408
* **Qwen-3 VL-8B** (vLLM inference)**:** [Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - Network accessline 3409
* **Qwen-2.5 VL-7B** (vLLM inference)**:** [Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_GRPO.ipynb) •[ Kaggle](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/note - Network accessline 3410
* **Gemma-3-4B** (Unsloth inference): [Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - Network accessline 3412
We have also added vLLM VLM integration into Unsloth natively, so all you have to do to use vLLM inference is enable the `fast_inference=True` flag when initializing the model. Special thanks to [Sinoué GAD](https://github.com/unslothai/uns - Network accessline 3414
This VLM support also integrates our latest update for even more memory efficient + faster RL including our [Standby feature](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/memory-efficient-rl#unsloth-standby), which un - Access to secretsline 3427
[Credential-related source omitted] - Network accessline 3454
<pre class="language-bash"><code class="lang-bash">pip install --upgrade --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git - Network accessline 3455
<strong>pip install --upgrade --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth-zoo.git - Network accessline 3460
'2025.1.5' is one of the previous old versions of Unsloth. Change it to a specific release listed on our [Github here](https://github.com/unslothai/unsloth/releases). - Access to secretsline 3510
[Credential-related source omitted] - Network accessline 3536
pip install ninja export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3537
export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive cd xformers && python setup.py install && cd .. - Network accessline 3538
git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3541
uv pip install unsloth bash curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env - Network accessline 3542
bash curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env bash - Dangerous shell operationline 3543
curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env - Network accessline 3543
curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env - Network accessline 3552
bash uv pip install -qqq \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 3553
uv pip install -qqq \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ "unsloth[base] @ git+https://github.com/unslothai/unsloth" - Network accessline 3554
"unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 3555
"unsloth[base] @ git+https://github.com/unslothai/unsloth" - Network accessline 3561
pip install ninja export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3562
export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive cd xformers && python setup.py install && cd .. - Network accessline 3563
git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3566
uv pip install -U transformers bash curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" - Network accessline 3567
bash curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" bash - Network accessline 3568
curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" - Network accessline 3574
conda activate unsloth-blackwell bash pip install -U vllm --extra-index-url https://download.pytorch.org/whl/cu128 - Network accessline 3575
bash pip install -U vllm --extra-index-url https://download.pytorch.org/whl/cu128 bash - Network accessline 3576
pip install -U vllm --extra-index-url https://download.pytorch.org/whl/cu128 - Network accessline 3584
pip install ninja export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3585
export TORCH_CUDA_ARCH_LIST="12.0" git clone --depth=1 https://github.com/facebookresearch/xformers --recursive cd xformers && python setup.py install && cd .. - Network accessline 3586
git clone --depth=1 https://github.com/facebookresearch/xformers --recursive - Network accessline 3608
# Install xformers from source with optimized build flags pip install -v --no-build-isolation -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers - Network accessline 3609
pip install -v --no-build-isolation -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers - Network accessline 3622
[**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) is Unsloth's only Docker image. For Blackwell and 50-series GPUs, use this same image - no separate image needed. - Network accessline 3624
For installation instructions, please follow our [Unsloth Docker guide](https://docs.unsloth.ai/new/how-to-fine-tune-llms-with-unsloth-and-docker). - Network accessline 3664
Google’s Gemma 3n multimodal model handles image, audio, video, and text inputs. Available in 2B and 4B sizes, it supports 140 languages for text and multimodal tasks. You can now run and fine-tune **Gemma-3n-E4B** and **E2B** locally using - Network accessline 3666
> **Fine-tune Gemma 3n with our** [**free Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) - Network accessline 3674
<table><thead><tr><th width="249">Dynamic 2.0 GGUF (text only)</th><th width="285">Dynamic 4-bit Instruct (to fine-tune)</th><th>16-bit Instruct</th></tr></thead><tbody><tr><td><ul><li><a href="https://huggingface.co/unsloth/gemma-3n-E2B-it - Network accessline 3676
**See all our Gemma 3n uploads including base and more formats in** [**our collection here**](https://huggingface.co/collections/unsloth/gemma-3n-685d3874830e49e1c93f9339)**.** - Network accessline 3720
{% hint style="info" %} We would first like to thank [Xuan-Son Nguyen](https://x.com/ngxson) from Hugging Face, [Georgi Gerganov](https://x.com/ggerganov) from the llama.cpp team on making Gemma 3N work in llama.cpp! - Network accessline 3721
We would first like to thank [Xuan-Son Nguyen](https://x.com/ngxson) from Hugging Face, [Georgi Gerganov](https://x.com/ggerganov) from the llama.cpp team on making Gemma 3N work in llama.cpp! - Network accessline 3724
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Dangerous shell operationline 3745
ollama rm hf.co/unsloth/gemma-3n-E4B-it-GGUF:UD-Q4_K_XL - Network accessline 3752
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 3754
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 3754
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 3781
* It might also be because your inference engine adds an unnecessary "start of sequence" token (or the lack of thereof on the contrary) so ensure you check both hypotheses! * <mark style="background-color:green;">**Use our conversational no - Network accessline 3782
* <mark style="background-color:green;">**Use our conversational notebooks to force the chat template - this will fix most issues.**</mark> * Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/ - Network accessline 3783
* Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) - Network accessline 3784
* Gemma-3 4B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) - Network accessline 3785
* Llama-3.2 3B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 3786
* Phi-4 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb) - Network accessline 3787
* Mistral v0.3 7B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb) - Network accessline 3788
* **More notebooks in our** [**notebooks repo**](https://github.com/unslothai/notebooks)**.** - Network accessline 3806
RUN git clone --depth=1 https://github.com/facebookresearch/xformers --recursive && \ - Network accessline 3824
!uv pip install -qqq \ "torch>=2.8.0" "triton>=3.4.0" {install_numpy} \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 3825
"torch>=2.8.0" "triton>=3.4.0" {install_numpy} \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ "unsloth[base] @ git+https://github.com/unslothai/unsloth" \ - Network accessline 3826
"unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 3827
"unsloth[base] @ git+https://github.com/unslothai/unsloth" \ - Network accessline 3828
torchvision bitsandbytes \ git+https://github.com/huggingface/transformers \ git+https://github.com/triton-lang/triton.git@05b2c186c1b6c9a08375389d5efe9cb4c401c075#subdirectory=python/triton_kernels - Network accessline 3829
git+https://github.com/huggingface/transformers \ - Network accessline 3830
git+https://github.com/triton-lang/triton.git@05b2c186c1b6c9a08375389d5efe9cb4c401c075#subdirectory=python/triton_kernels - Network accessline 3835
We’ll load **`gpt-oss-20b`** using Unsloth's [linearized version](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune/..#making-efficient-gpt-oss-fine-tuning-work) (as no other version will work for QLoRA fine-tuning). Configur - Network accessline 3862
* [GRPO notebooks](https://docs.unsloth.ai/unsloth-notebooks#grpo-reasoning-rl-notebooks) - Network accessline 3863
* [ORPO notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-ORPO.ipynb) - Network accessline 3864
* [DPO Zephyr notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb) - Network accessline 3865
* [KTO notebook](https://colab.research.google.com/drive/1MRgGtLWuZX4ypSfGguFgC-IblTvO2ivM?usp=sharing) - Network accessline 3866
* [SimPO notebook](https://colab.research.google.com/drive/1Hs5oQDovOay4mFA6Y9lQhVJ8TnbFLFh2?usp=sharing) - Network accessline 3868
We're also in 🤗Hugging Face's official docs! We're on the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and the [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#acceler - Access to secretsline 3873
[Credential-related source omitted] - Network accessline 3905
Finetuned from [**Mistral-Small-3.1**](https://huggingface.co/unsloth/Mistral-Small-3.1-24B-Instruct-2503-GGUF), Devstral supports a 128k context window. Devstral Small 1.1 has improved performance, achieving a score of 53.6% performance on - Network accessline 3917
All Devstral uploads use our Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) methodology, delivering the best performance on 5-shot MMLU and KL Divergence benchmarks. This means, you can run and fine-tune qua - Network accessline 3921
| Devstral 2507 (new) | Devstral 2505 | | ----- - Network accessline 3922
| ---------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------- | | GGUF: - Network accessline 3923
| GGUF: [Devstral-Small-2507-GGUF](https://huggingface.co/unsloth/Devstral-Small-2507-GGUF) | [Devstral-Small-2505-GGUF](https://huggingface.co/unsloth/Devstral-Small-2505-GGUF) | - Network accessline 3924
| 4-bit BnB: [Devstral-Small-2507-unsloth-bnb-4bit](https://huggingface.co/unsloth/Devstral-Small-2507-unsloth-bnb-4bit) | [Devstral-Small-2505-unsloth-bnb-4bit](https://huggingface.co/unsloth/Devstral-Small-2505-unsloth-bnb-4bit) | - Network accessline 3936
**A system prompt is recommended**, and is a derivative of Open Hand's system prompt. The full system prompt is provided [here](https://huggingface.co/unsloth/Devstral-Small-2505/blob/main/SYSTEM_PROMPT.txt). - Network accessline 3946
2. Run the model with our dynamic quant. Note you can call `ollama serve &`in another terminal if it fails! We include all suggested parameters (temperature etc) in `params` in our Hugging Face upload! 3. Also Devstral supports 128K context - Network accessline 3947
3. Also Devstral supports 128K context lengths, so best to enable [**KV cache quantization**](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-set-the-quantization-type-for-the-kv-cache). We use 8bit quantization which saves - Network accessline 3951
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 3973
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 3975
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 3975
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 3986
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 3987
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 3988
git clone https://github.com/ggerganov/llama.cpp - Network accessline 4001
RUN git clone https://github.com/triton-lang/triton.git && \ - Network accessline 4084
**Not necessarily.** Many assume RAG will consistently outperform a fine-tuned model, but that’s not the case when fine-tuning is done properly. In fact, a well-tuned model often matches or even surpasses RAG-based systems on specialized ta - Network accessline 4090
**Not at all!** While full fine-tuning or pretraining can be costly, these are not necessary (pretraining is especially not necessary). In most cases, LoRA or QLoRA fine-tuning can be done for minimal cost. In fact, with Unsloth’s [free not - Network accessline 4107
We recommend starting with **QLoRA**, as it’s one of the most efficient and accessible methods available. Thanks to Unsloth’s [dynamic 4-bit](https://unsloth.ai/blog/dynamic-4bit) quants, the accuracy loss compared to standard 16-bit LoRA f - Network accessline 4113
{% content-ref url="../fine-tuning-llms-guide/lora-hyperparameters-guide" %} [lora-hyperparameters-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Network accessline 4114
[lora-hyperparameters-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Access to secretsline 4127
[Credential-related source omitted] - Access to secretsline 4135
[Credential-related source omitted] - Dangerous shell operationline 4146
* Use `USER_PASSWORD` for sudo operations inside container - Network accessline 4193
Read our full DeepSeek-R1 blogpost here: [unsloth.ai/blog/deepseekr1-dynamic](https://unsloth.ai/blog/deepseekr1-dynamic) - Network accessline 4209
{% tabs %} {% tab title="IQ1\_S code" %} {% file src="<https://3215535692-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FxhOjnexMCB3dmuQFQ2Zq%2Fuploads%2FqpBdpW55h5mNAzVoTxPI%2Finference_UD-IQ1_S_3407.txt?alt=media&toke - Network accessline 4211
[Credential-related source omitted] - Network accessline 4213
[Credential-related source omitted] - Network accessline 4215
[Credential-related source omitted] - Network accessline 4218
[Credential-related source omitted] - Network accessline 4219
[Credential-related source omitted] - Network accessline 4221
[Credential-related source omitted] - Network accessline 4223
[Credential-related source omitted] - Network accessline 4226
[Credential-related source omitted] - Network accessline 4227
[Credential-related source omitted] - Network accessline 4229
[Credential-related source omitted] - Network accessline 4231
[Credential-related source omitted] - Network accessline 4237
{% tabs %} {% tab title="IQ1\_S basic code" %} {% file src="<https://3215535692-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FxhOjnexMCB3dmuQFQ2Zq%2Fuploads%2FFtAMzAucSfKMkkmXItTj%2Finference_basic-IQ1_S_3407.txt?alt=m - Network accessline 4239
[Credential-related source omitted] - Network accessline 4241
[Credential-related source omitted] - Network accessline 4243
[Credential-related source omitted] - Network accessline 4245
[Credential-related source omitted] - Network accessline 4246
[Credential-related source omitted] - Network accessline 4248
[Credential-related source omitted] - Network accessline 4250
[Credential-related source omitted] - Network accessline 4252
{% tab title="IQ2\_XXS basic code" %} {% file src="<https://3215535692-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FxhOjnexMCB3dmuQFQ2Zq%2Fuploads%2FajsVHsVqlWpwHk7mY32t%2Finference_basic-IQ2_XXS_3407.txt?alt=media&to - Network accessline 4253
[Credential-related source omitted] - Network accessline 4255
[Credential-related source omitted] - Network accessline 4257
[Credential-related source omitted] - Network accessline 4275
If you're still encountering any issues with versions or depencies, please use our [Docker image](https://docs.unsloth.ai/get-started/install-and-update/docker) which will have everything pre-installed. - Network accessline 4288
* It might also be because your inference engine adds an unnecessary "start of sequence" token (or the lack of thereof on the contrary) so ensure you check both hypotheses! * <mark style="background-color:green;">**Use our conversational no - Network accessline 4289
* <mark style="background-color:green;">**Use our conversational notebooks to force the chat template - this will fix most issues.**</mark> * Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/ - Network accessline 4290
* Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) - Network accessline 4291
* Gemma-3 4B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) - Network accessline 4292
* Llama-3.2 3B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 4293
* Phi-4 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb) - Network accessline 4294
* Mistral v0.3 7B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb) - Network accessline 4295
* **More notebooks in our** [**notebooks docs**](https://docs.unsloth.ai/get-started/unsloth-notebooks) - Network accessline 4320
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 4321
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 4322
git clone https://github.com/ggerganov/llama.cpp - Network accessline 4355
DeepSeek-R1-0528 is DeepSeek's new update to their R1 reasoning model. The full 671B parameter model requires 715GB of disk space. The quantized dynamic **1.66-bit** version uses 162GB (-80% reduction in size). GGUF: [DeepSeek-R1-0528-GGUF] - Network accessline 4357
DeepSeek also released a R1-0528 distilled version by fine-tuning Qwen3 (8B). The distill achieves similar performance to Qwen3 (235B). ***You can also*** [***fine-tune Qwen3 Distill***](#fine-tuning-deepseek-r1-0528-with-unsloth) ***with U - Network accessline 4359
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run & fine-tune quantized DeepSeek LLMs with minimal accuracy loss. - Network accessline 4366
NEW: Huge improvements to tool calling and chat template fixes.\ \ New [TQ1\_0 dynamic 1.66-bit quant](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF?show_file_info=DeepSeek-R1-0528-UD-TQ1_0.gguf) - 162GB in size. Ideal for 192GB RAM - Network accessline 4367
\ New [TQ1\_0 dynamic 1.66-bit quant](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF?show_file_info=DeepSeek-R1-0528-UD-TQ1_0.gguf) - 162GB in size. Ideal for 192GB RAM (including Mac) and Ollama users. Try: `ollama run hf.co/unsloth/ - Network accessline 4368
New [TQ1\_0 dynamic 1.66-bit quant](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF?show_file_info=DeepSeek-R1-0528-UD-TQ1_0.gguf) - 162GB in size. Ideal for 192GB RAM (including Mac) and Ollama users. Try: `ollama run hf.co/unsloth/De - Network accessline 4387
According to [DeepSeek](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528), these are the recommended settings for R1 (R1-0528 and Qwen3 distill should use the same settings) inference: - Network accessline 4404
* Qwen3 (8B) distill: [DeepSeek-R1-0528-Qwen3-8B-GGUF](https://huggingface.co/unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF) - Network accessline 4407
We also uploaded [IQ4\_NL](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF/tree/main/IQ4_NL) and [Q4\_1](https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF/tree/main/Q4_1) quants which run specifically faster for ARM and Apple device - Network accessline 4409
<table data-full-width="false"><thead><tr><th>MoE Bits</th><th>Type + Link</th><th>Disk Size</th><th>Details</th></tr></thead><tbody><tr><td>1.66bit</td><td><a href="https://huggingface.co/unsloth/DeepSeek-R1-0528-GGUF?show_file_info=DeepSe - Network accessline 4411
We've also uploaded versions in [BF16 format](https://huggingface.co/unsloth/DeepSeek-R1-0528-BF16), and original [FP8 (float8) format](https://huggingface.co/unsloth/DeepSeek-R1-0528). - Network accessline 4425
Open WebUI has made an step-by-step tutorial on how to run R1 here and for R1-0528, you will just need to replace R1 with the new 0528 quant: [docs.openwebui.com/tutorials/integrations/deepseekr1-dynamic/](https://docs.openwebui.com/tutoria - Network accessline 4433
1. <mark style="background-color:yellow;">**To run the full 720GB R1-0528 model,**</mark> [<mark style="background-color:yellow;">**see here**</mark>](#run-full-r1-0528-on-llama.cpp)<mark style="background-color:yellow;">**.**</mark> Obtain - Network accessline 4439
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 4455
3. Download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose `UD-IQ1_S`(dynamic 1.78bit quant) or other quantized versions like `Q4_K_M` . We <mark style="background-color:green;">**recommend using - Network accessline 4473
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 4475
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 4475
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 4499
GLM-4.6 is the latest reasoning model from **Z.ai**, achieving SOTA performance on coding and agent benchmarks while offering improved conversational chats. The full 355B parameter model requires **400GB** of disk space, while the Unsloth D - Network accessline 4506
You asked for benchmarks on our quants, so we’re showcasing Aider Polyglot results! Our Dynamic 3-bit DeepSeek V3.1 GGUF scores **75.6%**, surpassing many full-precision SOTA LLMs. [Read more.](https://docs.unsloth.ai/new/unsloth-dynamic-gg - Network accessline 4509
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and Aider performance, meaning you can run & fine-tune quantized GLM LLMs with minimal accuracy loss. - Network accessline 4519
[Credential-related source omitted] - Network accessline 4551
{% stepper %} {% step %} Install `ollama` if you haven't already! To run more variants of the model, [see here](https://docs.unsloth.ai/deepseek-v3.1-how-to-run-locally#run-in-llama.cpp). - Network accessline 4553
Install `ollama` if you haven't already! To run more variants of the model, [see here](https://docs.unsloth.ai/deepseek-v3.1-how-to-run-locally#run-in-llama.cpp). - Network accessline 4566
{% stepper %} {% step %} Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or jus - Network accessline 4568
Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 4592
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 4594
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 4594
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 4632
Unsloth Docker image: [**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) - Network accessline 4643
Install Docker via [Linux](https://docs.docker.com/engine/install/) or [Desktop](https://docs.docker.com/desktop/) (other).\ - Network accessline 4644
Then install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installation): - Dangerous shell operationline 4647
</strong>sudo apt-get update && sudo apt-get install -y \ - Network accessline 4654
[Credential-related source omitted] - Network accessline 4659
[**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) is Unsloth's only Docker image. For Blackwell and 50-series GPUs, use this same image - no separate one needed. - Network accessline 4661
[Credential-related source omitted] - Network accessline 4666
Go to [http://localhost:8888](http://localhost:8888/) and open Unsloth. - Network accessline 4668
[Credential-related source omitted] - Network accessline 4672
[Credential-related source omitted] - Network accessline 4677
If you're new, follow our step-by-step [Fine-tuning Guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide), [RL Guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) or just save/copy any of our premade [no - Network accessline 4679
[Credential-related source omitted] - Access to secretsline 4706
[Credential-related source omitted] - Access to secretsline 4708
[Credential-related source omitted] - Network accessline 4740
One of the key parts of creating a dataset is your [chat template](https://docs.unsloth.ai/basics/chat-templates) and how you are going to design it. Tokenization is also important as it breaks text into tokens, which can be words, sub-word - Network accessline 4759
* Chat-based dialogues (Q\&A, learn a new language, customer support, conversations). * Structured tasks ([classification](https://colab.research.google.com/github/timothelaborie/text_classification_scripts/blob/main/unsloth_classification. - Network accessline 4760
* Structured tasks ([classification](https://colab.research.google.com/github/timothelaborie/text_classification_scripts/blob/main/unsloth_classification.ipynb), summarization, generation tasks). - Network accessline 4789
For [**continued pretraining**](https://docs.unsloth.ai/basics/continued-pretraining), we use raw text format without specific structure: - Network accessline 4793
If we are adapting a model to a new task, and intend for the model to output text in a single turn based on a specific set of instructions, we can use **Instruction** format in [Alpaca style](https://docs.unsloth.ai/basics/tutorial-how-to-f - Network accessline 4828
<mark style="color:green;">**A:**</mark> If your dataset is already formatted in the Alpaca format, then follow the formatting steps as shown in the Llama3.1 [notebook ](https://colab.research.google.com/github/unslothai/notebooks/blob/mai - Network accessline 4836
<mark style="color:green;">**A:**</mark> The `chat_template` attribute when a model is first uploaded by the original model owners sometimes contains errors and may take time to be updated. In contrast, at Unsloth, we thoroughly check and - Network accessline 4840
<mark style="color:green;">**A:**</mark> Submit a feature request on the unsloth github issues [forum](https://github.com/unslothai/unsloth). As a temporary workaround, you could also use the tokenizer's own apply\_chat\_template function - Network accessline 4846
* Produce entirely new data - either from scratch or from your existing dataset * Diversify your dataset so your model does not [overfit](https://docs.unsloth.ai/get-started/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting) - Network accessline 4847
* Diversify your dataset so your model does not [overfit](https://docs.unsloth.ai/get-started/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting) and become too specific - Network accessline 4852
We collaborated with Meta to launch a free notebook for creating Synthetic Datasets automatically using local models like Llama 3.2. [Access the notebook here.](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Meta_ - Network accessline 4889
If you want to fine-tune a model that already has reasoning capabilities like the distilled versions of DeepSeek-R1 (e.g. DeepSeek-R1-Distill-Llama-8B), you will need to still follow question/task and answer pairs however, for your answer y - Network accessline 4891
For a model that does not have reasoning and you want to train it so that it later encompasses reasoning capabilities, you will need to utilize a standard dataset but this time without reasoning in its answers. This is training process is k - Network accessline 4897
* Standardize the format of all datasets, combine them into a single dataset, and fine-tune on this unified dataset. * Use the [Multiple Datasets](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) notebo - Network accessline 4898
* Use the [Multiple Datasets](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) notebook to fine-tune on multiple datasets directly. - Network accessline 4908
[Credential-related source omitted] - Network accessline 4912
You can access the GPT4 version of the Alpaca dataset [here](https://huggingface.co/datasets/vicgalle/alpaca-gpt4.). Below shows some examples of the dataset: - Network accessline 4914
[Credential-related source omitted] - Network accessline 4918
[Credential-related source omitted] - Network accessline 4924
[Credential-related source omitted] - Network accessline 4930
[Credential-related source omitted] - Network accessline 4934
[Credential-related source omitted] - Network accessline 4938
[Credential-related source omitted] - Network accessline 4948
[Credential-related source omitted] - Network accessline 4974
[Credential-related source omitted] - Network accessline 4978
[Credential-related source omitted] - Network accessline 4984
[Credential-related source omitted] - Network accessline 4988
The dataset for fine-tuning a vision or multimodal model also includes image inputs. For example, the [Llama 3.2 Vision Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb#scroll - Network accessline 4990
We'll be using a sampled version of the ROCO radiography dataset. You can access the dataset [here](https://www.google.com/url?q=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Funsloth%2FRadiology_mini). The dataset includes X-rays, CT scans and - Network accessline 4994
| Image - Network accessline 4996
[Credential-related source omitted] - Network accessline 5010
For more details, view our dataset section in the [notebook here](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb#scrollTo=vITh0KVJ10qX). - Network accessline 5082
* **Operating System**: Works on Linux and Windows. * Supports NVIDIA GPUs since 2018+ including [Blackwell RTX 50](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) and [**DGX Spark**](https://docs.u - Network accessline 5083
* Supports NVIDIA GPUs since 2018+ including [Blackwell RTX 50](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) and [**DGX Spark**](https://docs.unsloth.ai/basics/fine-tuning-llms-with-nvidia-dgx-sp - Network accessline 5084
Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20 & 50, A100, H100, L40 etc) [Check your GPU!](https://developer.nvidia.com/cuda-gpus) GTX 1070, 1080 works, but is slow. - Network accessline 5085
* The official [Unsloth Docker image](https://hub.docker.com/r/unsloth/unsloth) `unsloth/unsloth` is available on Docker Hub. - Network accessline 5086
* Unsloth works on [AMD](https://docs.unsloth.ai/new/fine-tuning-llms-on-amd-gpus-with-unsloth) and [Intel](https://github.com/unslothai/unsloth/pull/2621) GPUs! Apple/Silicon/MLX is in the works. - Network accessline 5101
**For context length benchmarks, see** [**here**](https://docs.unsloth.ai/basics/unsloth-benchmarks#context-length-benchmarks)**.** - Network accessline 5134
<table><thead><tr><th width="212.9000244140625">Argument</th><th>Example and use-case</th></tr></thead><tbody><tr><td><strong><code>--gpu-memory-utilization</code></strong></td><td>Default 0.9. How much VRAM usage vLLM can use. Reduce if go - Network accessline 5181
curl -X POST http://localhost:8000/v1/load_lora_adapter \ - Network accessline 5204
Qwen released QwQ-32B - a reasoning model with performance comparable to DeepSeek-R1 on many [benchmarks](https://qwenlm.github.io/blog/qwq-32b/). However, people have been experiencing **infinite generations**, **many repetitions**, \<thin - Network accessline 5212
| [GGUF](https://huggingface.co/unsloth/QwQ-32B-GGUF) | [Dynamic 4-bit](https://huggingface.co/unsloth/QwQ-32B-unsloth-bnb-4bit) | [BnB 4-bit](https://huggingface.co/unsloth/QwQ-32B-bnb-4bit) | [16-bit](https://huggingface.co/unsloth/QwQ-32 - Network accessline 5217
According to [Qwen](https://huggingface.co/Qwen/QwQ-32B), these are the recommended settings for inference: - Network accessline 5244
Courtesy to [@krist486](https://x.com/krist486/status/1897885598196654180) for bringing llama.cpp sampling directions to my attention. - Network accessline 5248
We investigated usage of `dry penalty` as suggested in <https://github.com/ggml-org/llama.cpp/blob/master/examples/main/README.md> using a value of 0.8, but we actually found this to **rather cause syntax issues especially for coding**. If - Network accessline 5260
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 5262
2. Download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose Q4\_K\_M, or other quantized versions (like BF16 full precision). More versions at: <https://huggingface.co/unsloth/QwQ-32B-GGUF> - Network accessline 5289
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 5291
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 5291
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 5310
Qwen3-VL has vision, video and OCR capabilities as well as 256K context (can be extended to 1M).\ \ [Unsloth](https://github.com/unslothai/unsloth) supports **Qwen3-VL fine-tuning and** [**RL**](https://docs.unsloth.ai/new/vision-reinforcem - Network accessline 5312
[Unsloth](https://github.com/unslothai/unsloth) supports **Qwen3-VL fine-tuning and** [**RL**](https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl). Train Qwen3-VL (8B) for free with our [notebooks](#fine-tuning-qwen3-vl). - Network accessline 5322
| <ul><li><a href="https://huggingface.co/unsloth/Qwen3-VL-2B-Instruct-GGUF">2B-Instruct</a></li><li><a href="https://huggingface.co/unsloth/Qwen3-VL-2B-Thinking-GGUF">2B-Thinking</a></li><li><a href="https://huggingface.co/unsloth/Qwen3-VL - Network accessline 5340
Qwen3-VL also used the below settings for their benchmarking numbers, as mentioned [on GitHub](https://github.com/QwenLM/Qwen3-VL/tree/main?tab=readme-ov-file#generation-hyperparameters). - Network accessline 5359
[Credential-related source omitted] - Network accessline 5371
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 5373
2. **Let's first get an image!** You can also upload images as well. We shall use <https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/unsloth%20made%20with%20love.png>, which is just our mini logo showing how finetun - Network accessline 5375
[Credential-related source omitted] - Network accessline 5381
4. Let's get the 2nd image at <https://files.worldwildlife.org/wwfcmsprod/images/Sloth_Sitting_iStock_3_12_2014/story_full_width/8l7pbjmj29_iStock_000011145477Large_mini__1_.jpg> - Network accessline 5383
[Credential-related source omitted] - Network accessline 5391
[Credential-related source omitted] - Network accessline 5395
[Credential-related source omitted] - Network accessline 5399
[Credential-related source omitted] - Network accessline 5403
[Credential-related source omitted] - Network accessline 5407
[Credential-related source omitted] - Network accessline 5413
[Credential-related source omitted] - Network accessline 5454
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 5455
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 5456
git clone https://github.com/ggml-org/llama.cpp - Network accessline 5532
[Credential-related source omitted] - Network accessline 5534
We uploaded dynamic 4-bit quants to: <https://huggingface.co/unsloth/QwQ-32B-unsloth-bnb-4bit> - Network accessline 5536
Since vLLM 0.7.3 (2025 February 20th) <https://github.com/vllm-project/vllm/releases/tag/v0.7.3>, vLLM now supports loading Unsloth dynamic 4bit quants! - Network accessline 5538
All our GGUFs are at <https://huggingface.co/unsloth/QwQ-32B-GGUF>! - Network accessline 5548
According to the Min\_p paper <https://arxiv.org/pdf/2407.01082>, for more creative and diverse outputs, and if you still see repetitions, try disabling top\_p and top\_k! - Network accessline 5607
{% embed url="<https://www.youtube.com/watch?v=SoPE1cUz3Hs>" %} - Network accessline 5611
{% embed url="<https://www.youtube.com/watch?t=3289s&v=bbFEYPx9Hpo>" %} - Network accessline 5615
{% embed url="<https://www.youtube.com/watch?v=juOh1afy-IE>" %} - Network accessline 5617
{% embed url="<https://www.youtube.com/watch?v=oF0_eMhzRaQ>" %} - Network accessline 5650
You can then run the merged QAT lower precision model in vLLM, Unsloth and other systems for inference! These are all in the [Qwen3-4B QAT Colab notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\ - Access to secretsline 5696
[Credential-related source omitted] - Access to secretsline 5698
[Credential-related source omitted] - Network accessline 5822
<table data-full-width="true"><thead><tr><th>MoE Bits</th><th>Type</th><th>Disk Size</th><th>Accuracy</th><th>Link</th><th>Details</th></tr></thead><tbody><tr><td>1.58bit</td><td>UD-IQ1_S</td><td><strong>131GB</strong></td><td>Fair</td><td> - Network accessline 5843
5. To test our Flappy Bird example as mentioned in our blog post here: <https://unsloth.ai/blog/deepseekr1-dynamic>, we can produce the 2nd example like below using our 1.58bit dynamic quant: - Network accessline 5845
[Credential-related source omitted] - Network accessline 5874
<table><thead><tr><th width="249">Dynamic GGUFs</th><th>Dynamic 4-bit + FP8</th><th>16-bit Instruct</th></tr></thead><tbody><tr><td><ul><li><a href="https://huggingface.co/unsloth/granite-4.0-h-350m-GGUF">H-350M</a></li><li><a href="https:/ - Network accessline 5876
You can also view our [Granite-4.0 collection](https://huggingface.co/collections/unsloth/granite-40-68ddf64b4a8717dc22a9322d) for all uploads including Dynamic Float8 quants etc. - Network accessline 5908
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 5925
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 5927
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 5927
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 5937
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 5938
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 5939
git clone https://github.com/ggml-org/llama.cpp - Access to secretsline 5965
[Credential-related source omitted] - Access to secretsline 5966
[Credential-related source omitted] - Network accessline 6074
[Credential-related source omitted] - Network accessline 6101
* **LoRA:** 16-bit fine-tuning. It's slightly faster and slightly more accurate, but consumes significantly more VRAM (4× more than QLoRA). Recommended for 16-bit environments and scenarios where maximum accuracy is required. * **QLoRA:** 4 - Network accessline 6103
:sloth: *70B LLaMA fits in <48GB VRAM with QLoRA in Unsloth -* [*more details here*](https://unsloth.ai/blog/llama3-3)*.* - Network accessline 6147
[Read our blog post](https://unsloth.ai/blog/gradient) for more details. - Network accessline 6151
[Credential-related source omitted] - Network accessline 6155
[Credential-related source omitted] - Network accessline 6161
[Credential-related source omitted] - Network accessline 6169
A regularization technique that helps [prevent overfitting](#overfitting-poor-generalization-too-specialized) by randomly setting a fraction of the LoRA activations to zero during each training step. [Recent research suggests](https://arxiv - Network accessline 6174
Options are `True`, `False`, and `"unsloth"`. \ 🦥 *We recommend* `"unsloth"` *as it reduces memory usage by an extra 30% and supports extremely long context fine-tunes. You can read more on* [*our blog post about long context training*]( - Network accessline 6175
🦥 *We recommend* `"unsloth"` *as it reduces memory usage by an extra 30% and supports extremely long context fine-tunes. You can read more on* [*our blog post about long context training*](https://unsloth.ai/blog/long-context)*.*\\ - Network accessline 6179
An advanced feature that implements [**Rank-Stabilized LoRA**](https://arxiv.org/abs/2312.03732). If set to `True`, the effective scaling becomes `lora_alpha / sqrt(r)` instead of the standard `lora_alpha / r`. This can sometimes improve st - Network accessline 6181
An advanced technique, as proposed in [**LoftQ**](https://arxiv.org/abs/2310.08659), initializes LoRA matrices with the top 'r' singular vectors from the pretrained weights. This can improve accuracy but may cause a significant memory spike - Network accessline 6185
When validating that **LoRA** adapter weights have been updated after fine-tuning, avoid using **np.allclose()** for comparison. This method can miss subtle but meaningful changes, particularly in **LoRA A**, which is initialized with small - Network accessline 6206
[Credential-related source omitted] - Network accessline 6216
According to the [rsLoRA (rank stabilized lora) paper](https://arxiv.org/abs/2312.03732), we should instead scale alpha by the sqrt of the rank. Other options exist, but theoretically this is the optimum. The left plot shows other ranks and - Network accessline 6233
According to empirical experiments and research papers like the original [QLoRA paper](https://arxiv.org/pdf/2305.14314), it's best to apply LoRA to both attention and MLP layers. - Network accessline 6238
[Credential-related source omitted] - Network accessline 6257
The [QLoRA paper](https://arxiv.org/pdf/2305.14314) shows that masking out inputs and **training only on completions** (outputs or assistant messages) can further **increase accuracy** by a few percentage points (*1%*). Below demonstrates h - Network accessline 6278
The QLoRA paper states that **training on completions only** increases accuracy by quite a bit, especially for multi-turn conversational finetunes! We do this in our [conversational notebooks here](https://colab.research.google.com/github/u - Network accessline 6280
[Credential-related source omitted] - Network accessline 6327
***Acknowledgements:** A huge thank you to* [*Eyera*](https://huggingface.co/Orenguteng) *for contributing to this guide!* - Network accessline 6374
{% hint style="success" %} For **advanced GRPO** documentation on batching, generation and training parameters, [read our guide!](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/advanced-rl-documentation) - Network accessline 6375
For **advanced GRPO** documentation on batching, generation and training parameters, [read our guide!](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/advanced-rl-documentation) - Network accessline 6383
This article covers everything (from beginner to advanced) you need to know about GRPO, Reinforcement Learning (RL) and reward functions, along with tips, and the basics of using GRPO with [Unsloth](https://github.com/unslothai/unsloth). If - Network accessline 6404
[Credential-related source omitted] - Network accessline 6411
[Credential-related source omitted] - Network accessline 6430
[Credential-related source omitted] - Network accessline 6433
{% column %} OpenAI popularized the concept of [RLHF](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback) (Reinforcement Learning from Human Feedback), where we train an <mark style="background-color:red;">**"agent"**< - Network accessline 6434
OpenAI popularized the concept of [RLHF](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback) (Reinforcement Learning from Human Feedback), where we train an <mark style="background-color:red;">**"agent"**</mark> to pro - Network accessline 6443
[Credential-related source omitted] - Network accessline 6445
[Credential-related source omitted] - Network accessline 6450
{% column %} In order to do RLHF, [<mark style="background-color:red;">**PPO**</mark>](https://en.wikipedia.org/wiki/Proximal_policy_optimization) (Proximal policy optimization) was developed. The <mark style="background-color:blue;">**agen - Network accessline 6451
In order to do RLHF, [<mark style="background-color:red;">**PPO**</mark>](https://en.wikipedia.org/wiki/Proximal_policy_optimization) (Proximal policy optimization) was developed. The <mark style="background-color:blue;">**agent**</mark> is - Network accessline 6459
The formula for PPO looks quite complicated because it was designed to be stable. Visit our [AI Engineer talk](https://docs.unsloth.ai/ai-engineers-2025) we gave in 2025 about RL for more in depth maths derivations about PPO. - Network accessline 6466
[Credential-related source omitted] - Network accessline 6469
{% column %} DeepSeek developed [<mark style="background-color:red;">**GRPO**</mark>](https://unsloth.ai/blog/grpo) (Group Relative Policy Optimization) to train their R1 reasoning models. The key differences to PPO are: - Network accessline 6470
DeepSeek developed [<mark style="background-color:red;">**GRPO**</mark>](https://unsloth.ai/blog/grpo) (Group Relative Policy Optimization) to train their R1 reasoning models. The key differences to PPO are: - Network accessline 6482
2. Code output can be verified as having executed correctly or not. 3. Designing verifiable reward functions can be tough, and so most examples are math or code. 4. Use-cases for GRPO isn’t just for code or math—its reasoning process can en - Network accessline 6484
4. Use-cases for GRPO isn’t just for code or math—its reasoning process can enhance tasks like email automation, database retrieval, law, and medicine, greatly improving accuracy based on your dataset and reward function - the trick is to d - Network accessline 6494
[Credential-related source omitted] - Network accessline 6505
[Credential-related source omitted] - Network accessline 6530
[Credential-related source omitted] - Network accessline 6544
* With 15GB VRAM, Unsloth allows you to transform any model up to 17B parameters like Llama 3.1 (8B), Phi-4 (14B), Mistral (7B) or Qwen2.5 (7B) into a reasoning model * **Unsloth now supports** [**RL for Vision/multimodal**](https://docs.un - Network accessline 6545
* **Unsloth now supports** [**RL for Vision/multimodal**](https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl) **models!** - Network accessline 6548
{% content-ref url="reinforcement-learning-rl-guide/tutorial-train-your-own-reasoning-model-with-grpo" %} [tutorial-train-your-own-reasoning-model-with-grpo](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/tutorial-train - Network accessline 6549
[tutorial-train-your-own-reasoning-model-with-grpo](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/tutorial-train-your-own-reasoning-model-with-grpo) - Network accessline 6552
| [**gpt-oss-20b**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) **GSPO -** new | [**Qwen3-VL-8B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_ - Network accessline 6553
| -------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- - Network accessline 6554
| [**Qwen3 (4B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) - Advanced | [**DeepSeek-R1-0528-Qwen3-8B**](https://colab.research.google.com/github/unslothai/notebooks/blob/mai - Network accessline 6555
| [Gemma 3 (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(1B\)-GRPO.ipynb) | [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4_\(14B\) - Network accessline 6556
| [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-GRPO.ipynb) | [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\ - Network accessline 6558
{% hint style="success" %} **NEW!** We now support [**GSPO**](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/gspo-reinforcement-learning) and most other new GRPO techniques. You can play with the following arguments in - Network accessline 6559
**NEW!** We now support [**GSPO**](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/gspo-reinforcement-learning) and most other new GRPO techniques. You can play with the following arguments in GRPOConfig to enable: - Network accessline 6591
{% hint style="success" %} [**Aug 28 update**](https://docs.unsloth.ai/models/long-context-gpt-oss-training#new-saving-to-gguf-vllm-after-gpt-oss-training)**:** You can now export/save your QLoRA fine-tuned gpt-oss model to llama.cpp, vLLM, - Network accessline 6592
[**Aug 28 update**](https://docs.unsloth.ai/models/long-context-gpt-oss-training#new-saving-to-gguf-vllm-after-gpt-oss-training)**:** You can now export/save your QLoRA fine-tuned gpt-oss model to llama.cpp, vLLM, HF etc. - Network accessline 6594
We also introduced [Unsloth Flex Attention](https://docs.unsloth.ai/models/long-context-gpt-oss-training#introducing-unsloth-flex-attention-support) which enables **>8× longer context lengths**, **>50% less VRAM usage** and **>1.5× faster t - Network accessline 6597
> [**Fine-tune**](#fine-tuning-gpt-oss-with-unsloth) **gpt-oss-20b for free with our** [**Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-Fine-tuning.ipynb) - Network accessline 6599
Trained with [RL](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide), **gpt-oss-120b** rivals o4-mini and **gpt-oss-20b** rivals o3-mini. Both excel at function calling and CoT reasoning, surpassing o1 and GPT-4o. - Network accessline 6607
* 20B: [gpt-oss-**20B**](https://huggingface.co/unsloth/gpt-oss-20b-GGUF) - Network accessline 6608
* 120B: [gpt-oss-**120B**](https://huggingface.co/unsloth/gpt-oss-120b-GGUF) - Network accessline 6612
OpenAI released a standalone parsing and tokenization library called [Harmony](https://github.com/openai/harmony) which allows one to tokenize conversations to OpenAI's preferred format for gpt-oss. The official OpenAI [cookbook article](ht - Network accessline 6616
[Credential-related source omitted] - Network accessline 6637
[Credential-related source omitted] - Network accessline 6643
We made a [MXFP4 inference notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\)-Inference.ipynb) as well in Tesla T4 Colab! - Network accessline 6645
{% hint style="info" %} [Software emulation](https://triton-lang.org/main/python-api/generated/triton.language.dot_scaled.html) enables targeting hardware architectures without native microscaling operation support. Right now for such case, - Network accessline 6646
[Software emulation](https://triton-lang.org/main/python-api/generated/triton.language.dot_scaled.html) enables targeting hardware architectures without native microscaling operation support. Right now for such case, microscaled lhs/rhs are - Network accessline 6683
[Credential-related source omitted] - Network accessline 6685
To achieve inference speeds of 6+ tokens per second for our Dynamic 4-bit quant, have at least **14GB of unified memory** (combined VRAM and RAM) or **14GB of system RAM** alone. As a rule of thumb, your available memory should match or exc - Network accessline 6695
> **You can run gpt-oss-20b for free with our** [**Google Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\)-Inference.ipynb) - Network accessline 6703
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 6823
**Magistral-Small-2509** is a reasoning LLM developed by Mistral AI. It excels at coding and mathematics and supports multiple languages. Magistral supports a 128k token context window and was finetuned from [**Mistral-Small-3.2**](https:/ - Network accessline 6835
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run & fine-tune quantized Mistral LLMs with minimal accuracy loss. - Network accessline 6839
<table><thead><tr><th width="255.64999389648438">Dynamic 2.0 GGUF (to run)</th><th width="305.25">Dynamic 4-bit (to finetune/deploy)</th><th>Dynamic Float8</th></tr></thead><tbody><tr><td><ul><li><a href="https://huggingface.co/unsloth/Magi - Network accessline 6880
2. Run the model with our dynamic quant. We did not set the context length automatically, so it will just use Ollama's default set context length.\ Note you can call `ollama serve &`in another terminal if it fails! We include all suggest - Network accessline 6881
Note you can call `ollama serve &`in another terminal if it fails! We include all suggested parameters (temperature etc) in `params` in our Hugging Face upload! 3. Also Magistral supports 40K context lengths, so best to enable [**KV cache q - Network accessline 6882
3. Also Magistral supports 40K context lengths, so best to enable [**KV cache quantization**](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-set-the-quantization-type-for-the-kv-cache). We use 8bit quantization which saves - Network accessline 6883
4. **Ollama also sets the default context length to 4096**, as [mentioned here](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-specify-the-context-window-size). Use `OLLAMA_CONTEXT_LENGTH=8192` to change it to 8192. Magist - Network accessline 6887
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 6942
## From https://mlabonne.github.io/blog/posts/Quantize_Llama_2_models_using_ggml.html - Network accessline 6944
**URL:** llms-txt#from-https://mlabonne.github.io/blog/posts/quantize_llama_2_models_using_ggml.html - Network accessline 6981
bash apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 6982
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y git clone https://github.com/ggerganov/llama.cpp - Network accessline 6983
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 6984
git clone https://github.com/ggerganov/llama.cpp - Network accessline 6993
bash apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 6994
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y git clone https://github.com/ggerganov/llama.cpp - Network accessline 6995
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 6996
git clone https://github.com/ggerganov/llama.cpp - Network accessline 7024
Or follow the steps at <https://rentry.org/llama-cpp-conversions#merging-loras-into-a-model> using the model name "merged\_model" to merge to GGUF. - Network accessline 7034
* It might also be because your inference engine adds an unnecessary "start of sequence" token (or the lack of thereof on the contrary) so ensure you check both hypotheses! * <mark style="background-color:green;">**Use our conversational no - Network accessline 7035
* <mark style="background-color:green;">**Use our conversational notebooks to force the chat template - this will fix most issues.**</mark> * Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/ - Network accessline 7036
* Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) - Network accessline 7037
* Gemma-3 4B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) - Network accessline 7038
* Llama-3.2 3B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 7039
* Phi-4 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb) - Network accessline 7040
* Mistral v0.3 7B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb) - Network accessline 7041
* **More notebooks in our** [**notebooks docs**](https://docs.unsloth.ai/get-started/unsloth-notebooks) - Network accessline 7074
Microsoft's new Phi-4 reasoning models are now supported in Unsloth. The 'plus' variant performs on par with OpenAI's o1-mini, o3-mini and Sonnet 3.7. The 'plus' and standard reasoning models are 14B parameters while the 'mini' has 4B param - Network accessline 7076
All Phi-4 reasoning uploads use our [Unsloth Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) methodology. - Network accessline 7080
| Dynamic 2.0 GGUF (to run) - Network accessline 7082
| <ul><li><a href="https://huggingface.co/unsloth/Phi-4-reasoning-plus-GGUF/">Reasoning-plus</a> (14B)</li></ul><ul><li><a href="https://huggingface.co/unsloth/Phi-4-reasoning-GGUF">Reasoning</a> (14B)</li></ul><ul><li><a href="https://hugg - Network accessline 7121
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 7139
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 7141
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 7141
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 7161
Fine-tuning vision models enables model to excel at certain tasks normal LLMs won't be as good as such as object/movement detection. **You can also train** [**VLMs with RL**](https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl) - Network accessline 7163
* **NEW: Qwen3-VL (8B) Vision:** [**Notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision.ipynb) - Network accessline 7164
* **Gemma 3 (4B) Vision:** [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision.ipynb) - Network accessline 7165
* **Llama 3.2 Vision** fine-tuning for radiography: [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb)\ - Network accessline 7166
How can we assist medical professionals in analyzing Xrays, CT Scans & ultrasounds faster. * **Qwen2.5 VL** fine-tuning for converting handwriting to LaTeX: [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/n - Network accessline 7167
* **Qwen2.5 VL** fine-tuning for converting handwriting to LaTeX: [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_VL_\(7B\)-Vision.ipynb)\ - Network accessline 7168
This allows complex math formulas to be easily transcribed as LaTeX without manually writing it. * **Pixtral 12B 2409** vision fine-tuning for general Q\&A: [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/n - Network accessline 7169
* **Pixtral 12B 2409** vision fine-tuning for general Q\&A: [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Pixtral_\(12B\)-Vision.ipynb)\ - Network accessline 7180
The dataset for fine-tuning a vision or multimodal model is similar to standard question & answer pair [datasets ](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide), but this time, they also includes image inputs. F - Network accessline 7182
We'll be using a sampled version of the ROCO radiography dataset. You can access the dataset [here](https://www.google.com/url?q=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Funsloth%2FRadiology_mini). The dataset includes X-rays, CT scans and - Network accessline 7186
| Image - Network accessline 7188
[Credential-related source omitted] - Network accessline 7202
For more details, view our dataset section in the [notebook here](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb#scrollTo=vITh0KVJ10qX). - Network accessline 7307
[Reward Functions/Verifiers](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/..#reward-functions-verifier) lets us know if the model is doing well or not according to the dataset you have provided. Each generation run wi - Network accessline 7309
You can input your generations into an LLM like ChatGPT 4o or Llama 3.1 (8B) and design a reward function and verifier to evaluate it. For example, feed your generations into a LLM of your choice and set a rule: "If the answer sounds too ro - Network accessline 7322
[Credential-related source omitted] - Network accessline 7329
We have pre-selected hyperparameters for the most optimal results however you could change them. Read all about [parameters here](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide). For **advanced GRPO** - Network accessline 7331
[Credential-related source omitted] - Network accessline 7364
LLMs often struggle with tasks that involve complex environments. However, by applying [reinforcement learning](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) (RL) and designing a custom [reward function](https://docs. - Network accessline 7366
RL can be adapted for tasks such as auto kernel or strategy creation. This tutorial shows how to train **gpt-oss** with [**GRPO**](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide#from-rlhf-ppo-to-grpo-and-rlvr) and Unslo - Network accessline 7368
| [2048 notebook](https://colab.research.google.com/github/openai/gpt-oss/blob/main/examples/reinforcement-fine-tuning.ipynb) (Official OpenAI example) | [Kernel generation notebook](https://colab.research.google.com/github/unslothai/notebo - Network accessline 7392
Load the 20B model in 4‑bit QLoRA for memory efficiency, then wrap it with a LoRA adapter. You can also train it in 16-bit LoRA but it will use 4x more memory. For more settings view our [configuration guide](https://docs.unsloth.ai/get-sta - Network accessline 7601
!uv pip install -qqq \ "torch>=2.8.0" "triton>=3.4.0" {get_numpy} torchvision bitsandbytes "transformers==4.56.2" \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 7602
"torch>=2.8.0" "triton>=3.4.0" {get_numpy} torchvision bitsandbytes "transformers==4.56.2" \ "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ "unsloth[base] @ git+https://github.com/unslothai/unsloth" \ - Network accessline 7603
"unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo" \ - Network accessline 7604
"unsloth[base] @ git+https://github.com/unslothai/unsloth" \ - Network accessline 7605
git+https://github.com/triton-lang/triton.git@05b2c186c1b6c9a08375389d5efe9cb4c401c075#subdirectory=python/triton_kernels - Network accessline 7674
DeepSeek’s V3.1 and **Terminus** update introduces hybrid reasoning inference, combining 'think' and 'non-think' into one model. The full 671B parameter model requires 715GB of disk space. The quantized dynamic 2-bit version uses 245GB (-75 - Network accessline 7676
{% hint style="success" %} **NEW:** DeepSeek-V3.1-Terminus out now: [DeepSeek-V3.1-Terminus-GGUF](https://huggingface.co/unsloth/DeepSeek-V3.1-Terminus-GGUF)\ - Network accessline 7677
**NEW:** DeepSeek-V3.1-Terminus out now: [DeepSeek-V3.1-Terminus-GGUF](https://huggingface.co/unsloth/DeepSeek-V3.1-Terminus-GGUF)\ - Network accessline 7679
[**Sept 10, 2025 update:**](https://docs.unsloth.ai/new/unsloth-dynamic-ggufs-on-aider-polyglot) You asked for tougher benchmarks, so we’re showcasing Aider Polyglot results! Our Dynamic 3-bit DeepSeek V3.1 GGUF scores **75.6%**, surpassing - Network accessline 7684
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run & fine-tune quantized DeepSeek LLMs with minimal accuracy loss. - Network accessline 7708
1. DeepSeek V3.1 is a hybrid reasoning model, meaning you can change the chat template to enable reasoning. The chat template introduced `thinking = True` , but other models use `enable_thinking = True` . We added the option to use `enable_ - Network accessline 7709
2. llama.cpp's jinja renderer via [minja](https://github.com/google/minja) does not allow the use of extra arguments in the `.split()` command, so using `.split(text, 1)` works in Python, but not in minja. We had to change this to make llam - Network accessline 7716
According to [DeepSeek](https://huggingface.co/deepseek-ai/DeepSeek-V3.1), these are the recommended settings for V3.1 inference: - Network accessline 7774
{% step %} Open WebUI also made a [step-by-step tutorial](https://docs.openwebui.com/tutorials/integrations/deepseekr1-dynamic/) on how to run R1 and for V3.1, you will just need to replace R1 with the new V3.1 quant. - Network accessline 7775
Open WebUI also made a [step-by-step tutorial](https://docs.openwebui.com/tutorials/integrations/deepseekr1-dynamic/) on how to run R1 and for V3.1, you will just need to replace R1 with the new V3.1 quant. - Network accessline 7781
{% stepper %} {% step %} Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or jus - Network accessline 7783
Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 7812
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 7814
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 7814
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 7837
url = "https://huggingface.co/datasets/laion/OIG/resolve/main/unified_chip2.jsonl" - Access to secretsline 7935
[Credential-related source omitted] - Access to secretsline 7940
[Credential-related source omitted] - Access to secretsline 7941
[Credential-related source omitted] - Network accessline 7963
year = {2025}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF}} - Network accessline 7964
publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF}} } - Network accessline 7965
howpublished = {\url{https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF}} - Network accessline 7971
year = {2025}, publisher = {Github}, howpublished = {\url{https://github.com/unslothai/unsloth}} - Network accessline 7972
publisher = {Github}, howpublished = {\url{https://github.com/unslothai/unsloth}} } - Network accessline 7973
howpublished = {\url{https://github.com/unslothai/unsloth}} - Network accessline 8028
* For more detailed benchmarks, read our [Llama 3.3 Blog](https://unsloth.ai/blog/llama3-3).  - Network accessline 8029
* Benchmarking of Unsloth was also conducted by [🤗Hugging Face](https://huggingface.co/blog/unsloth-trl). - Network accessline 8031
Tested on H100 and [Blackwell](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) GPUs. We tested using the Alpaca Dataset, a batch size of 2, gradient accumulation steps of 4, rank = 32, and applied Q - Network accessline 8037
{% hint style="info" %} The more data you have, the less VRAM Unsloth uses due to our [gradient checkpointing](https://unsloth.ai/blog/long-context) algorithm + Apple's CCE algorithm! - Network accessline 8038
The more data you have, the less VRAM Unsloth uses due to our [gradient checkpointing](https://unsloth.ai/blog/long-context) algorithm + Apple's CCE algorithm! - Network accessline 8077
As shown at [OpenAI DevDay](https://x.com/UnslothAI/status/1976284209842118714), gpt-oss-20b was trained with RL and Unsloth on DGX Spark to auto-win 2048. You can train using Unsloth in a Docker container or virtual environment on DGX Spar - Network accessline 8079
[Credential-related source omitted] - Network accessline 8085
[Credential-related source omitted] - Network accessline 8094
First, build the Docker image using the DGX Spark Dockerfile which can be [found here](https://raw.githubusercontent.com/unslothai/notebooks/main/Dockerfile_DGX_Spark). You can also run the below in a Terminal in the DGX Spark: - Network accessline 8098
[Credential-related source omitted] - Dangerous shell operationline 8109
sudo apt update && sudo apt install -y wget - Network accessline 8109
sudo apt update && sudo apt install -y wget wget -O Dockerfile "https://raw.githubusercontent.com/unslothai/notebooks/main/Dockerfile_DGX_Spark" - Network accessline 8110
wget -O Dockerfile "https://raw.githubusercontent.com/unslothai/notebooks/main/Dockerfile_DGX_Spark" - Network accessline 8135
You can fine-tune DeepSeek-OCR to enhance its vision or language performance. In our Unsloth [**free fine-tuning notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\).ipynb), we demonstrat - Network accessline 8139
> **Our model upload that enables fine-tuning + more inference support:** [**DeepSeek-OCR**](https://huggingface.co/unsloth/DeepSeek-OCR) - Network accessline 8184
{% hint style="success" %} [**Aug 28 update**](https://docs.unsloth.ai/models/long-context-gpt-oss-training#introducing-unsloth-flex-attention-support)**:** You can now export/save your QLoRA fine-tuned gpt-oss model to llama.cpp, vLLM, HF - Network accessline 8185
[**Aug 28 update**](https://docs.unsloth.ai/models/long-context-gpt-oss-training#introducing-unsloth-flex-attention-support)**:** You can now export/save your QLoRA fine-tuned gpt-oss model to llama.cpp, vLLM, HF etc. - Network accessline 8187
We also introduced [Unsloth Flex Attention](https://docs.unsloth.ai/models/long-context-gpt-oss-training#introducing-unsloth-flex-attention-support) which enables **>8× longer context lengths**, **>50% less VRAM usage** and **>1.5× faster t - Network accessline 8190
> **Quickstart:** Fine-tune gpt-oss-20b for free with our: [Colab notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-Fine-tuning.ipynb) - Network accessline 8201
This section covers fine-tuning gpt-oss using our Google Colab [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks). You can also save and use the gpt-oss notebook into your favorite code editor and follow our [local gpt-oss g - Network accessline 8210
[Credential-related source omitted] - Network accessline 8212
[Credential-related source omitted] - Network accessline 8217
We’ll load **`gpt-oss-20b`** using Unsloth's [linearized version](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune/..#making-efficient-gpt-oss-fine-tuning-work) (as no other version will work).  - Network accessline 8226
[Credential-related source omitted] - Network accessline 8230
[Credential-related source omitted] - Network accessline 8235
Now it's time to adjust your training hyperparameters. For a deeper dive into how, when, and what to tune, check out our [detailed hyperparameters guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Network accessline 8237
{% hint style="info" %} To avoid [overfitting](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting), monitor your training loss and avoid setting these values too high. - Network accessline 8238
To avoid [overfitting](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide#avoiding-overfitting-and-underfitting), monitor your training loss and avoid setting these values too high.  - Network accessline 8243
[Credential-related source omitted] - Network accessline 8248
[Credential-related source omitted] - Network accessline 8251
For this example, we will use the [`HuggingFaceH4/Multilingual-Thinking`](https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking). This dataset contains chain-of-thought reasoning examples derived from user questions translated - Network accessline 8257
[Credential-related source omitted] - Network accessline 8265
[Credential-related source omitted] - Network accessline 8267
One unique feature of gpt-oss is its use of the [**OpenAI Harmony format**](https://github.com/openai/harmony)**,** which supports structured conversations, reasoning output, and tool calling. This format includes tags such as `<|start|>` , - Network accessline 8269
{% hint style="info" %} 🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 8270
🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 8273
Feel free to adapt the prompt and structure to suit your own dataset or use-case. For more guidance, refer to our [dataset guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide). - Network accessline 8276
We've pre-selected training hyperparameters for optimal results. However, you can modify them based on your specific use case. Refer to our [hyperparameters guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparamet - Network accessline 8280
[Credential-related source omitted] - Network accessline 8284
[Credential-related source omitted] - Network accessline 8293
[Credential-related source omitted] - Network accessline 8297
[Credential-related source omitted] - Network accessline 8316
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 8322
[Credential-related source omitted] - Network accessline 8330
{% hint style="info" %} We recommend downloading or incorporating elements from our Colab [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) into your local setup for easier use. - Network accessline 8331
We recommend downloading or incorporating elements from our Colab [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) into your local setup for easier use. - Network accessline 8339
Ensure your device is [Unsloth compatible](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) and you can read our detailed [installation guide](https://docs.unsloth.ai/get-started/install-and-update). - Network accessline 8364
[Credential-related source omitted] - Network accessline 8366
One unique feature of gpt-oss is its use of the [**OpenAI Harmony format**](https://github.com/openai/harmony)**,** which supports structured conversations, reasoning output, and tool calling. This format includes tags such as `<|start|>` , - Network accessline 8368
{% hint style="info" %} 🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 8369
🦥 Unsloth fixes the chat template to ensure it is correct. See this [tweet](https://x.com/danielhanchen/status/1953901104150065544) for technical details on our template fix. - Network accessline 8372
Feel free to adapt the prompt and structure to suit your own dataset or use-case. For more guidance, refer to our [dataset guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide). - Network accessline 8379
We've pre-selected training hyperparameters for optimal results. However, you can modify them based on your specific use case. Refer to our [hyperparameters guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparamet - Network accessline 8383
[Credential-related source omitted] - Network accessline 8387
[Credential-related source omitted] - Network accessline 8398
[Credential-related source omitted] - Network accessline 8402
[Credential-related source omitted] - Network accessline 8471
This can zero out all `completion_mask` entries when many completions are truncated, making `n_mask_per_reward = 0` and causing KL to become NaN. [See](https://github.com/unslothai/unsloth-zoo/blob/e705f7cb50aa3470a0b6e36052c61b7486a39133/u - Network accessline 8632
In our GitHub, we have a list of every chat template Unsloth uses including for Llama, Mistral, Phi-4 etc. So if you need any pointers on the formatting or use case, you can view them here: [github.com/unslothai/unsloth/blob/main/unsloth/ch - Network accessline 8636
* [Conversational](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 8637
* [ChatML](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb) - Network accessline 8638
* [Ollama](https://colab.research.google.com/drive/1WZDi7APtQ9VsvOrQSSC5DDtxq159j8iZ?usp=sharing) - Network accessline 8639
* [Text Classification](https://github.com/timothelaborie/text_classification_scripts/blob/main/unsloth_classification.ipynb) by Timotheeee - Network accessline 8640
* [Multiple Datasets](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) by Flail - Network accessline 8646
[Credential-related source omitted] - Network accessline 8650
[Credential-related source omitted] - Network accessline 8656
[Credential-related source omitted] - Network accessline 8662
[Credential-related source omitted] - Network accessline 8666
[Credential-related source omitted] - Network accessline 8670
[Credential-related source omitted] - Network accessline 8674
[Credential-related source omitted] - Network accessline 8678
[Credential-related source omitted] - Network accessline 8680
Or in the Titanic prediction task where you had to predict if a passenger died or survived in this Colab notebook which includes CSV and Excel uploading: <https://colab.research.google.com/drive/1VYkncZMfGFkeCEgN2IzbZIKEDkyQuJAS?usp=sharin - Network accessline 8682
[Credential-related source omitted] - Network accessline 8762
We’re excited to share that Unsloth Dynamic GGUFs shows how it's possible to quantize LLMs like [DeepSeek-V3.1](https://docs.unsloth.ai/models/deepseek-v3.1-how-to-run-locally) (671B) down to just **1-bit** or **3-bit**, and still be able t - Network accessline 8764
Previously, [we demonstrated](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) how Unsloth Dynamic GGUFs outperform other quantization methods on 5-shot MMLU and KL Divergence. Now, we’re showcasing their performance on independent - Network accessline 8766
[Credential-related source omitted] - Network accessline 8774
**Why the** [**Aider Polyglot**](https://aider.chat/docs/leaderboards/) **benchmark?** Aider is one of the most comprehensive measures of how well LLMs can write, code, follow instructions, and apply changes without human intervention, maki - Network accessline 8776
{% hint style="success" %} The **key advantage** of using the Unsloth package and models is our active role in ***fixing critical bugs*** in major models. We've collaborated directly with teams behind [Qwen3](https://www.reddit.com/r/LocalL - Network accessline 8777
The **key advantage** of using the Unsloth package and models is our active role in ***fixing critical bugs*** in major models. We've collaborated directly with teams behind [Qwen3](https://www.reddit.com/r/LocalLLaMA/comments/1kaodxu/qwen3 - Network accessline 8786
In Nov 2024, our [4-bit Dynamic](https://unsloth.ai/blog/dynamic-4bit) Quants showcased how you could largely restore QLoRA fine-tuning & model accuracy by just <mark style="background-color:green;">**selectively quantizing layers**</mark>. - Network accessline 8788
Our Dynamic GGUFs are even more effective when paired with our [imatrix calibration dataset](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs#whats-new-in-dynamic-v2.0), designed for chat and coding performance. All of this enabled - Network accessline 8795
[Credential-related source omitted] - Network accessline 8800
[Credential-related source omitted] - Network accessline 8804
We also showed dynamic benchmarks in <https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs> for Gemma 3 and Llama 4 Scout, showing how effective our methodology is: - Network accessline 8809
[Credential-related source omitted] - Network accessline 8812
[Credential-related source omitted] - Network accessline 8824
Benchmark experiments were mainly conducted by [David Sluys](https://www.linkedin.com/in/david-sluys-231348208/) (neolithic5452 on [Aider Discord](https://discord.com/channels/1131200896827654144/1408293692074360914)), a trusted community c - Network accessline 8863
[Credential-related source omitted] - Network accessline 8874
[Credential-related source omitted] - Network accessline 8890
[Credential-related source omitted] - Network accessline 8896
See [here](https://huggingface.co/unsloth/DeepSeek-V3.1-GGUF?chat_template=default\&format=true) for our fixed chat template or [here](https://huggingface.co/unsloth/DeepSeek-V3.1/raw/main/chat_template.jinja) for a raw jinja file. - Network accessline 8902
[Credential-related source omitted] - Network accessline 8906
Head over to our [DeepSeek V3.1 guide](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/deepseek-r1-how-to-run-locally/deepseek-r1-dynamic-1.58-bit) or to quickly get the dynamic 2bit version, do: - Network accessline 8925
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 8926
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 8927
git clone https://github.com/ggml-org/llama.cpp - Possible obfuscationline 9050
* <U+200B>**DeepSeek-R1-Distill-Llama-8B** is a fine-tuned version of Llama-3.1-8B. DeepSeek utilized data generated by DeepSeek-R1, to fine-tune Llama-3.1-8B. This process, known as distillation (a subcategory of fine-tuning), injects the data in - Network accessline 9052
With [Unsloth](https://github.com/unslothai/unsloth), you can fine-tune for free on Colab, Kaggle, or locally with just 3GB VRAM by using our [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks). By fine-tuning a pre-trained m - Network accessline 9068
You may have heard that fine-tuning does not make a model learn new knowledge or RAG performs better than fine-tuning. That is **false**. Read more FAQ + misconceptions [here](https://docs.unsloth.ai/beginner-start-here/faq-+-is-fine-tuning - Network accessline 9070
{% content-ref url="beginner-start-here/faq-+-is-fine-tuning-right-for-me" %} [faq-+-is-fine-tuning-right-for-me](https://docs.unsloth.ai/get-started/beginner-start-here/faq-+-is-fine-tuning-right-for-me) - Network accessline 9071
[faq-+-is-fine-tuning-right-for-me](https://docs.unsloth.ai/get-started/beginner-start-here/faq-+-is-fine-tuning-right-for-me) - Network accessline 9081
[Credential-related source omitted] - Network accessline 9085
We recommend starting with **Instruct models**, as they allow direct fine-tuning using conversational chat templates (ChatML, ShareGPT etc.) and require less data compared to **Base models** (which uses Alpaca, Vicuna etc). Learn more about - Network accessline 9087
* Model names ending in **`unsloth-bnb-4bit`** indicate they are [**Unsloth dynamic 4-bit**](https://unsloth.ai/blog/dynamic-4bit) **quants**. These models consume slightly more VRAM than standard BitsAndBytes 4-bit models but offer signifi - Network accessline 9099
We recommend starting with QLoRA, as it is one of the most accessible and effective methods for training models. Our [dynamic 4-bit](https://unsloth.ai/blog/dynamic-4bit) quants, the accuracy loss for QLoRA compared to LoRA is now largely r - Network accessline 9101
You can also do [Text-to-speech (TTS)](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning), [reasoning (GRPO)](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide), [vision](https://docs.unsloth.ai/basics/vision-f - Network accessline 9105
{% content-ref url="fine-tuning-llms-guide/what-model-should-i-use" %} [what-model-should-i-use](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/what-model-should-i-use) - Network accessline 9106
[what-model-should-i-use](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/what-model-should-i-use) - Network accessline 9111
* You will need to create a dataset usually with 2 columns - question and answer. The quality and amount will largely reflect the end result of your fine-tune so it's imperative to get this part right. * You can [synthetically generate data - Network accessline 9112
* You can [synthetically generate data](https://docs.unsloth.ai/get-started/datasets-guide#synthetic-data-generation) and structure your dataset (into QA pairs) using ChatGPT or local LLMs. - Network accessline 9113
* You can also use our new Synthetic Dataset notebook which automatically parses documents (PDFs, videos etc.), generates QA pairs and auto cleans data using local models like Llama 3.2. [Access the notebook here.](https://colab.research.go - Network accessline 9119
{% content-ref url="fine-tuning-llms-guide/datasets-guide" %} [datasets-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide) - Network accessline 9120
[datasets-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/datasets-guide) - Network accessline 9123
For most of our notebook examples, we utilize the [Alpaca dataset](https://docs.unsloth.ai/basics/tutorial-how-to-finetune-llama-3-and-use-in-ollama#id-6.-alpaca-dataset) however other notebooks like Vision will use different datasets which - Network accessline 9127
Learn how to choose the right [hyperparameters](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) using best practices from research and real-world experiments - and understand how each one affects your - Network accessline 9131
{% content-ref url="fine-tuning-llms-guide/lora-hyperparameters-guide" %} [lora-hyperparameters-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Network accessline 9132
[lora-hyperparameters-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/lora-hyperparameters-guide) - Network accessline 9137
We would recommend beginners to utilise our pre-made [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) first as it's the easiest way to get started with guided steps. However, if installing locally is a must, you can instal - Network accessline 9139
{% content-ref url="beginner-start-here/unsloth-requirements" %} [unsloth-requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) - Network accessline 9140
[unsloth-requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) - Network accessline 9145
{% content-ref url="install-and-update" %} [install-and-update](https://docs.unsloth.ai/get-started/install-and-update) - Network accessline 9146
[install-and-update](https://docs.unsloth.ai/get-started/install-and-update) - Network accessline 9155
[Credential-related source omitted] - Network accessline 9166
For testing, you can also take 20% of your training data and use that for testing. If you already used all of the training data, then you have to manually evaluate it. You can also use automatic eval tools like EleutherAI’s [lm-evaluation- - Network accessline 9170
[Credential-related source omitted] - Network accessline 9174
[Credential-related source omitted] - Network accessline 9180
{% content-ref url="../basics/running-and-saving-models" %} [running-and-saving-models](https://docs.unsloth.ai/basics/running-and-saving-models) - Network accessline 9181
[running-and-saving-models](https://docs.unsloth.ai/basics/running-and-saving-models) - Network accessline 9184
We can now save the finetuned model as a small 100MB file called a LoRA adapter like below. You can instead push to the Hugging Face hub as well if you want to upload your model! Remember to get a Hugging Face token via: <https://huggingfac - Network accessline 9186
[Credential-related source omitted] - Network accessline 9190
[Credential-related source omitted] - Network accessline 9194
To learn more about fine-tuning tips and tricks, head over to our blogs which provide tremendous and educational value: <https://unsloth.ai/blog/> - Network accessline 9196
If you need any help on fine-tuning, you can also join our Discord server [here](https://discord.gg/unsloth) or [Reddit r/unsloth](https://www.reddit.com/r/unsloth/). Thanks for reading and hopefully this was helpful! - Network accessline 9198
[Credential-related source omitted] - Network accessline 9245
# Fix up addCriterion issues # See https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl#qwen-2.5-vl-vision-rl-issues-and-quirks - Network accessline 9246
# See https://docs.unsloth.ai/new/vision-reinforcement-learning-vlm-rl#qwen-2.5-vl-vision-rl-issues-and-quirks - Network accessline 9292
[reinforcement-learning-rl-guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide "mention") - Network accessline 9294
***Authors:** A huge thank you to* [*Keith*](https://www.linkedin.com/in/keith-truongcao-7bb84a23b/) *and* [*Datta*](https://www.linkedin.com/in/datta0/) *for contributing to this article!* - Network accessline 9311
This was [reported](https://github.com/QwenLM/Qwen2.5-VL/issues/759) as well in Qwen2.5-VL-7B-Instruct output unexpected results "addCriterion". In fact we see this as well! We tried both non Unsloth, bfloat16 and float16 machines and other - Network accessline 9320
[Credential-related source omitted] - Network accessline 9324
[Credential-related source omitted] - Network accessline 9339
This update in addition adds GSPO ([Group Sequence Policy Optimization](https://arxiv.org/abs/2507.18071)) which is a variant of GRPO made by the Qwen team at Alibaba. They noticed that GRPO implicitly results in importance weights for each - Network accessline 9343
[Credential-related source omitted] - Network accessline 9345
[Credential-related source omitted] - Network accessline 9349
[Credential-related source omitted] - Network accessline 9353
[Credential-related source omitted] - Network accessline 9371
See our guide below for the complete process on how to save to [Ollama](https://github.com/ollama/ollama): - Network accessline 9373
{% content-ref url="../../get-started/fine-tuning-llms-guide/tutorial-how-to-finetune-llama-3-and-use-in-ollama" %} [tutorial-how-to-finetune-llama-3-and-use-in-ollama](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/tutorial-how - Network accessline 9374
[tutorial-how-to-finetune-llama-3-and-use-in-ollama](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide/tutorial-how-to-finetune-llama-3-and-use-in-ollama) - Network accessline 9379
You can save the finetuned model as a small 100MB file called a LoRA adapter like below. You can instead push to the Hugging Face hub as well if you want to upload your model! Remember to get a Hugging Face token via: <https://huggingface.c - Network accessline 9381
[Credential-related source omitted] - Network accessline 9385
[Credential-related source omitted] - Network accessline 9391
[Credential-related source omitted] - Network accessline 9395
[Credential-related source omitted] - Network accessline 9399
Head over to <https://github.com/ggerganov/llama.cpp> to learn more about GGUF. We also have some manual instructions of how to export to GGUF if you want here: <https://github.com/unslothai/unsloth/wiki#manually-saving-to-gguf> - Network accessline 9403
[Credential-related source omitted] - Network accessline 9407
[Credential-related source omitted] - Network accessline 9411
[Credential-related source omitted] - Network accessline 9417
[Credential-related source omitted] - Network accessline 9421
[Credential-related source omitted] - Network accessline 9425
[Credential-related source omitted] - Network accessline 9433
* It might also be because your inference engine adds an unnecessary "start of sequence" token (or the lack of thereof on the contrary) so ensure you check both hypotheses! * <mark style="background-color:green;">**Use our conversational no - Network accessline 9434
* <mark style="background-color:green;">**Use our conversational notebooks to force the chat template - this will fix most issues.**</mark> * Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/ - Network accessline 9435
* Qwen-3 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) - Network accessline 9436
* Gemma-3 4B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) - Network accessline 9437
* Llama-3.2 3B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb) - Network accessline 9438
* Phi-4 14B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb) - Network accessline 9439
* Mistral v0.3 7B Conversational notebook [**Open in Colab**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb) - Network accessline 9440
* **More notebooks in our** [**notebooks docs**](https://docs.unsloth.ai/get-started/unsloth-notebooks) - Network accessline 9463
{% hint style="success" %} [**Sept 10, 2025 update:**](https://docs.unsloth.ai/new/unsloth-dynamic-ggufs-on-aider-polyglot) You asked for tougher benchmarks, so we’re showcasing Aider Polyglot results! Our Dynamic 3-bit DeepSeek V3.1 GGUF s - Network accessline 9464
[**Sept 10, 2025 update:**](https://docs.unsloth.ai/new/unsloth-dynamic-ggufs-on-aider-polyglot) You asked for tougher benchmarks, so we’re showcasing Aider Polyglot results! Our Dynamic 3-bit DeepSeek V3.1 GGUF scores **75.6%**, surpassing - Network accessline 9466
The **key advantage** of using the Unsloth package and models is our active role in ***fixing critical bugs*** in major models. We've collaborated directly with teams behind [Qwen3](https://www.reddit.com/r/LocalLLaMA/comments/1kaodxu/qwen3 - Network accessline 9471
[Credential-related source omitted] - Network accessline 9485
| **Qwen3:** [0.6B](https://huggingface.co/unsloth/Qwen3-0.6B-GGUF) • [1.7B](https://huggingface.co/unsloth/Qwen3-1.7B-GGUF) • [4B](https://huggingface.co/unsloth/Qwen3-4B-GGUF) • [8B](https://huggingface.co/unsloth/Qwen3-8B-GGUF) • [14B](h - Network accessline 9486
| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- - Network accessline 9487
| **DeepSeek:** [R1-0528](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/deepseek-r1-0528-how-to-run-locally#model-uploads) • [V3-0324](https://huggingface.co/unsloth/DeepSeek-V3-0324-GGUF-UD) • [R1-Distill-Llama](ht - Network accessline 9488
| **Gemma 3:** [4B](https://huggingface.co/unsloth/gemma-3-4b-it-GGUF) • [12B](https://huggingface.co/unsloth/gemma-3-12b-it-GGUF) • [27B](https://huggingface.co/unsloth/gemma-3-27b-it-GGUF) • [QAT](https://huggingface.co/unsloth/gemma-3-12 - Network accessline 9494
[Accuracy is Not All You Need](https://arxiv.org/pdf/2407.09141) showcases how pruning layers, even by selecting unnecessary ones still yields vast differences in terms of "flips". A "flip" is defined as answers changing from incorrect to c - Network accessline 9496
[Credential-related source omitted] - Network accessline 9506
Most frameworks report perplexity and KL Divergence using a test set of Wikipedia articles. However, we noticed using the calibration dataset which is also Wikipedia related causes quants to overfit, and attain lower perplexity scores. We u - Network accessline 9514
[Credential-related source omitted] - Network accessline 9516
* Llama 3.1 (8B) Instruct has a MMLU 5 shot accuracy of 67.8% using a naive MMLU implementation. We find however Llama **tokenizes "A" and "\_A" (A with a space in front) as different token ids**. If we consider both spaced and non spaced t - Network accessline 9517
* Interestingly Llama 3 as per Eleuther AI's [LLM Harness](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/llama3/instruct/mmlu/_continuation_template_yaml) also appends <mark style="background-color:purple;">**" - Network accessline 9518
* There are many other subtle issues, and so to benchmark everything in a controlled environment, we designed our own MMLU implementation from scratch by investigating [github.com/hendrycks/test](https://github.com/hendrycks/test) directly, - Network accessline 9524
1. Q4\_0 GGUF - Quantizes all layers to Q4\_0 via the formula `w = q * block_scale` with each block having 32 weights. See [llama.cpp wiki ](https://github.com/ggml-org/llama.cpp/wiki/Tensor-Encoding-Schemes)for more details. - Network accessline 9525
2. int4 version - presumably [TorchAO int4 style](https://github.com/pytorch/ao/blob/main/torchao/quantization/README.md)? - Network accessline 9555
[Credential-related source omitted] - Network accessline 9596
* Llama 4 Scout changed the RoPE Scaling configuration in their official repo. We helped resolve issues in llama.cpp to enable this [change here](https://github.com/ggml-org/llama.cpp/pull/12889) - Network accessline 9598
[Credential-related source omitted] - Network accessline 9599
* Llama 4's QK Norm's epsilon for both Scout and Maverick should be from the config file - this means using 1e-05 and not 1e-06. We helped resolve these in [llama.cpp](https://github.com/ggml-org/llama.cpp/pull/12889) and [transformers](htt - Network accessline 9600
* The Llama 4 team and vLLM also independently fixed an issue with QK Norm being shared across all heads (should not be so) [here](https://github.com/vllm-project/vllm/pull/16311). MMLU Pro increased from 68.58% to 71.53% accuracy. - Network accessline 9601
* [Wolfram Ravenwolf](https://x.com/WolframRvnwlf/status/1909735579564331016) showcased how our GGUFs via llama.cpp attain much higher accuracy than third party inference providers - this was most likely a combination of the issues explaine - Network accessline 9603
[Credential-related source omitted] - Network accessline 9617
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 9618
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 9619
git clone https://github.com/ggml-org/llama.cpp - Network accessline 9652
[Credential-related source omitted] - Network accessline 9658
A huge thank you to Rohan Pandey for his [Flex Attention implementation](https://x.com/khoomeik/status/1955693558914310608), which directly inspired the development of Unsloth's Flex Attention implementation. - Network accessline 9664
OpenAI leveraged **Attention Sinks** from the Efficient Streaming Language Models with Attention Sinks [paper](https://arxiv.org/abs/2309.17453) which shows that you can use a small sliding window, except you must add a global attention on - Network accessline 9666
[Credential-related source omitted] - Network accessline 9672
[Credential-related source omitted] - Network accessline 9674
The paper also shows that the [Attention Is Off By One method](https://www.evanmiller.org/attention-is-off-by-one.html) does partially work, except one must also add a few extra sink tokens to get lower perplexities. **The paper shows that - Network accessline 9676
[Credential-related source omitted] - Network accessline 9680
Flex Attention <https://pytorch.org/blog/flexattention/> is extremely powerful as it provides the practitioner 2 customization routes for the attention mechanism - a **score modifier (f)** and a **masking function (M)**. - Network accessline 9692
By using some visualization utilities from [Flex Attention's Github repo](https://github.com/meta-pytorch/attention-gym), we can visualize this. Assume the sequence length was 16, and a sliding window of 5. On the left is the last sink colu - Network accessline 9698
[Credential-related source omitted] - Network accessline 9704
[Credential-related source omitted] - Network accessline 9708
**Interesting finding**: The official Flex Attention sliding window implementations considers the window size as the number of last tokens **PLUS ONE** as it includes the current token. The HuggingFace and GPT OSS implementations strictly o - Network accessline 9716
[Credential-related source omitted] - Network accessline 9722
[Credential-related source omitted] - Network accessline 9726
We also confirmed through OpenAI's official GPT-OSS implementation on whether we attend to the last N or N+1 tokens here: <https://github.com/openai/gpt-oss/blob/main/gpt_oss/torch/model.py> - Network accessline 9728
[Credential-related source omitted] - Network accessline 9736
[Credential-related source omitted] - Network accessline 9770
To run inference on the merged model, you can use vLLM and Llama.cpp among others. OpenAI recommends these [inference settings](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune/..#recommended-settings) for both models: `tempe - Network accessline 9774
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 9794
We [recently collaborated with Hugging Face](https://github.com/huggingface/transformers/pull/40197) to resolve inference issues by using OpenAI’s kernels and ensuring that `swiglu_limit = 7.0` is correctly applied during MXFP4 inference. - Network accessline 9800
[Credential-related source omitted] - Network accessline 9812
[Credential-related source omitted] - Network accessline 9816
OpenAI's sink token implementation is [provided here](https://github.com/openai/gpt-oss/blob/main/gpt_oss/torch/model.py). We provide it below: - Network accessline 9820
The HuggingFace transformers implementation is [provided here](https://github.com/huggingface/transformers/blob/main/src/transformers/models/gpt_oss/modeling_gpt_oss.py). We also provide it below: - Access to secretsline 9868
[Credential-related source omitted] - Access to secretsline 9876
[Credential-related source omitted] - Dangerous shell operationline 9887
* Use `USER_PASSWORD` for sudo operations inside container - Network accessline 9949
{% columns %} {% column %} With Unsloth and TorchAO’s QAT support, you can also fine-tune a model in Unsloth and seamlessly export it to [ExecuTorch](https://github.com/pytorch/executorch) (PyTorch’s solution for on-device inference) and de - Network accessline 9951
With Unsloth and TorchAO’s QAT support, you can also fine-tune a model in Unsloth and seamlessly export it to [ExecuTorch](https://github.com/pytorch/executorch) (PyTorch’s solution for on-device inference) and deploy it directly on mobile. - Network accessline 9958
[Credential-related source omitted] - Network accessline 9966
Then **try QAT with our free** [**Qwen3 (4B) notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) - Network accessline 9986
DeepSeek developed [GRPO](https://unsloth.ai/blog/grpo) (Group Relative Policy Optimization) to train their R1 reasoning models. - Network accessline 9988
These instructions are for our pre-made Google Colab [notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks). If you are installing Unsloth locally, you can also copy our notebooks inside your favorite code editor. We'll be using - Network accessline 9990
| [**gpt-oss-20b**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) **-** GSPO | [**Qwen2.5-VL**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_ - Network accessline 9992
| [**Qwen3 (4B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) - Advanced | [**DeepSeek-R1-0528-Qwen3-8B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb - Network accessline 9997
If you're using our Colab notebook, click **Runtime > Run all**. We'd highly recommend you checking out our [Fine-tuning Guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide) before getting started. - Network accessline 9999
If installing locally, ensure you have the correct [requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) and use `pip install unsloth` on Linux or follow our [Windows install ](https://docs.unsloth.ai/ - Network accessline 10001
[Credential-related source omitted] - Network accessline 10006
Before we get started, it is recommended to learn more about GRPO, reward functions and how they work. Read more about them including [tips & tricks](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/..#basics-tips)[ here] - Network accessline 10013
We have pre-selected optimal settings for the best results for you already and you can change the model to whichever you want listed in our [supported models](https://docs.unsloth.ai/get-started/all-our-models). Would not recommend changing - Network accessline 10015
{% hint style="success" %} For **advanced GRPO** documentation on batching, generation and training parameters, [read our guide!](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/advanced-rl-documentation) - Network accessline 10016
For **advanced GRPO** documentation on batching, generation and training parameters, [read our guide!](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/advanced-rl-documentation) - Network accessline 10019
[Credential-related source omitted] - Network accessline 10022
We have pre-selected OpenAI's [GSM8K](https://huggingface.co/datasets/openai/gsm8k) dataset which contains grade school math problems but you could change it to your own or any public one on Hugging Face. You can read more about [datasets h - Network accessline 10026
[Credential-related source omitted] - Network accessline 10047
{% hint style="success" %} **NEW!** Qwen3 got an update in July 2025. Run & fine-tune the latest model: [**Qwen-2507**](https://docs.unsloth.ai/models/qwen3-how-to-run-and-fine-tune/qwen3-2507) - Network accessline 10048
**NEW!** Qwen3 got an update in July 2025. Run & fine-tune the latest model: [**Qwen-2507**](https://docs.unsloth.ai/models/qwen3-how-to-run-and-fine-tune/qwen3-2507) - Network accessline 10051
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run & fine-tune quantized Qwen LLMs with minimal accuracy loss. - Network accessline 10055
[Unsloth](https://github.com/unslothai/unsloth) also now supports fine-tuning and [Reinforcement Learning (RL)](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) of Qwen3 and Qwen3 MOE models — 2x faster, with 70% less VR - Network accessline 10061
| Dynamic 2.0 GGUF (to run) - Network accessline 10063
| <ul><li><a href="https://huggingface.co/unsloth/Qwen3-0.6B-GGUF">0.6B</a></li><li><a href="https://huggingface.co/unsloth/Qwen3-1.7B-GGUF">1.7B</a></li><li><a href="https://huggingface.co/unsloth/Qwen3-4B-GGUF">4B</a></li><li><a href="htt - Network accessline 10098
Qwen3 models come with built-in "thinking mode" to boost reasoning and improve response quality - similar to how [QwQ-32B](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms/qwq-32b-how-to-run-effectively) worked. Instru - Network accessline 10136
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 10183
## Go to https://docs.unsloth.ai for advanced tips like - Network accessline 10185
**URL:** llms-txt#go-to-https://docs.unsloth.ai-for-advanced-tips-like - Network accessline 10195
We're introducing GSPO which is a variant of [GRPO](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/..#from-rlhf-ppo-to-grpo-and-rlvr) made by the Qwen team at Alibaba. They noticed the observation that when GRPO takes i - Network accessline 10197
* Use our free GSPO notebooks for: [**gpt-oss-20b**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) and [**Qwen2.5-VL**](https://colab.research.google.com/github/unslothai/notebooks/blo - Network accessline 10201
[Credential-related source omitted] - Network accessline 10203
[Credential-related source omitted] - Network accessline 10207
[Credential-related source omitted] - Network accessline 10211
[Credential-related source omitted] - Network accessline 10266
With [Unsloth](https://github.com/unslothai/unsloth), you can fine-tune TTS models 1.5x faster with 50% less memory than other implementations with Flash Attention 2. This support includes Sesame CSM, Orpheus, and models supported by transf - Network accessline 10272
We've uploaded TTS models (original and quantized variants) to our [Hugging Face page](https://huggingface.co/collections/unsloth/text-to-speech-tts-models-68007ab12522e96be1e02155). - Network accessline 10276
| [Sesame-CSM (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Sesame_CSM_\(1B\)-TTS.ipynb) | [Orpheus-TTS (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Orpheus_\(3B\)-TTS.ipy - Network accessline 10278
| [Spark-TTS (0.5B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Spark_TTS_\(0_5B\).ipynb) | [Llasa-TTS (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llasa_TTS_\(1B\).ipynb) - Network accessline 10312
At minimum, a TTS fine-tuning dataset consists of **audio clips and their corresponding transcripts** (text). Let’s use the [*Elise* dataset](https://huggingface.co/datasets/MrDragonFox/Elise) which is \~3 hour single-speaker English speech - Network accessline 10314
* [`MrDragonFox/Elise`](https://huggingface.co/datasets/MrDragonFox/Elise) – an augmented version with **emotion tags** (e.g. \<sigh>, \<laughs>) embedded in the transcripts. These tags in angle brackets indicate expressions (laughter, sigh - Network accessline 10315
* [`Jinsaryko/Elise`](https://huggingface.co/datasets/Jinsaryko/Elise) – base version with transcripts without special tags. - Network accessline 10361
You can now run **Grok 2** (aka Grok 2.5), the 270B parameter model by xAI. Full precision requires **539GB**, while the Unsloth Dynamic 3-bit version shrinks size down to just **118GB** (a 75% reduction). GGUF: [Grok-2-GGUF](https://huggin - Network accessline 10363
The **3-bit Q3\_K\_XL** model runs on a single **128GB Mac** or **24GB VRAM + 128GB RAM**, achieving **5+ tokens/s** inference. Thanks to the llama.cpp team and community for [supporting Grok 2](https://github.com/ggml-org/llama.cpp/pull/15 - Network accessline 10365
All uploads use Unsloth [Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) for SOTA 5-shot MMLU and KL Divergence performance, meaning you can run quantized Grok LLMs with minimal accuracy loss. - Network accessline 10399
{% stepper %} {% step %} Install the specific `llama.cpp` PR for Grok 2 on [GitHub here](https://github.com/ggml-org/llama.cpp/pull/15539). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if - Network accessline 10401
Install the specific `llama.cpp` PR for Grok 2 on [GitHub here](https://github.com/ggml-org/llama.cpp/pull/15539). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or - Network accessline 10425
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 10426
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 10427
git clone https://github.com/ggml-org/llama.cpp cd llama.cpp && git fetch origin pull/15539/head:MASTER && git checkout MASTER && cd .. cmake llama.cpp -B llama.cpp/build \ - Network accessline 10481
See <https://docs.sglang.ai/get_started/install.html> for more details - Network accessline 10546
<table data-full-width="false"><thead><tr><th>MoE Bits</th><th>Type</th><th>Disk Size</th><th>Link</th><th>Details</th></tr></thead><tbody><tr><td>1.78bit</td><td>IQ1_S</td><td>33.8GB</td><td><a href="https://huggingface.co/unsloth/Llama-4- - Network accessline 10554
| MoE Bits | Type | Disk Size | HF Link | | -------- | --------- | --------- | ---------------------------------------------------------------- - Network accessline 10555
| -------- | --------- | --------- | --------------------------------------------------------------------------------------------------- | | 1.78bit | IQ1\_S | 122GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E- - Network accessline 10556
| 1.78bit | IQ1\_S | 122GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-IQ1_S) | - Network accessline 10557
| 1.93bit | IQ1\_M | 128GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-IQ1_M) | - Network accessline 10558
| 2.42-bit | IQ2\_XXS | 140GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-IQ2_XXS) | - Network accessline 10559
| 2.71-bit | Q2\_K\_XL | 151B | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-Q2_K_XL) | - Network accessline 10560
| 3.5-bit | Q3\_K\_XL | 193GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-Q3_K_XL) | - Network accessline 10561
| 4.5-bit | Q4\_K\_XL | 243GB | [Link](https://huggingface.co/unsloth/Llama-4-Maverick-17B-128E-Instruct-GGUF/tree/main/UD-Q4_K_XL) | - Network accessline 10574
* A BOS token of `<|begin_of_text|>` is auto added during tokenization (do NOT add it manually!)  * According to <https://www.llama.com/docs/model-cards-and-prompt-formats/llama4_omni/>, there is an <mark style="background-color:yellow - Network accessline 10575
* According to <https://www.llama.com/docs/model-cards-and-prompt-formats/llama4_omni/>, there is an <mark style="background-color:yellow;">**suggested optional system prompt**</mark>, which is listed below: - Network accessline 10579
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 10581
2. Download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose Q4\_K\_M, or other quantized versions (like BF16 full precision). More versions at: <https://huggingface.co/unsloth/Llama-4-Scout-17B-16 - Network accessline 10607
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 10608
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 10609
git clone https://github.com/ggml-org/llama.cpp - Access to secretsline 10634
[Credential-related source omitted] - Network accessline 10741
[Credential-related source omitted] - Network accessline 10763
Unsloth supports fine-tuning of DeepSeek-OCR. Since the default model isn’t fine-tunable, we added changes from the [Stranger Vision HF](https://huggingface.co/strangervisionhf) team, to then enable fine-tuning. As usual, Unsloth trains Dee - Network accessline 10767
* DeepSeek-OCR: [Fine-tuning only notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\).ipynb) - Network accessline 10768
* DeepSeek-OCR: [Fine-tuning + Evaluation notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\)-Eval.ipynb) (A100) - Network accessline 10800
You can now train OpenAI [gpt-oss](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune) with RL and GRPO via [Unsloth](https://github.com/unslothai/unsloth). Unsloth now offers the <mark style="background-color:$success;">**fast - Network accessline 10802
Since reinforcement learning (RL) on gpt-oss isn't yet vLLM compatible, we had to rewrite the inference code from Transformers code to deliver 3x faster inference for gpt-oss at \~21 tokens/s. For BF16, Unsloth also achieves the fastest inf - Network accessline 10804
* **Free notebook:** [**gpt-oss-20b GRPO Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb)\ - Network accessline 10807
[Credential-related source omitted] - Network accessline 10811
Unsloth is the only framework to support 4-bit RL for gpt-oss. All performance gains are due to Unsloth's unique [weight sharing](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide#what-unsloth-offers-for-rl), [Flex Attenti - Network accessline 10813
{% hint style="warning" %} Reminder: <mark style="background-color:$info;">**Flash Attention 3 (FA3) is**</mark> [<mark style="background-color:$info;">**unsuitable for gpt-oss**</mark>](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and - Network accessline 10814
Reminder: <mark style="background-color:$info;">**Flash Attention 3 (FA3) is**</mark> [<mark style="background-color:$info;">**unsuitable for gpt-oss**</mark>](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune/long-context-gpt - Network accessline 10821
[Credential-related source omitted] - Network accessline 10823
Inference is crucial in RL training, since we need it to generate candidate solutions before maximizing some reward function ([see here](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) for a more detailed explanation). - Network accessline 10825
vLLM does not support RL for gpt-oss since it lacks BF16 training and LoRA support for gpt-oss. Without Unsloth, only training via full precision BF16 works, making <mark style="background-color:$warning;">memory use</mark> <mark style="bac - Network accessline 10833
We had to change our implementation for attention sinks as [described here](https://docs.unsloth.ai/models/gpt-oss-how-to-run-and-fine-tune/long-context-gpt-oss-training) to allow generation to work with left padding. We had to get the logs - Network accessline 10855
The harder part is batch generation. Sequences differ in length, so padding complicates mask creation. Flex Attention had a lot of [challenges](https://github.com/meta-pytorch/attention-gym/issues/15#issuecomment-2284148665) and dynamic mas - Network accessline 10857
> *Quote from* [*https://github.com/meta-pytorch/attention-gym/issues/15#issuecomment-2284148665*](https://github.com/meta-pytorch/attention-gym/issues/15#issuecomment-2284148665) - Network accessline 10871
[Credential-related source omitted] - Network accessline 10886
It's the reason models learn to modify unit tests to pass coding challenges, and these are critical blockers for real world deployment. Some other good examples are from [Wikipedia](https://en.wikipedia.org/wiki/Reward_hacking). - Network accessline 10888
<div align="center"><figure><img src="https://i.pinimg.com/originals/55/e0/1b/55e01b94a9c5546b61b59ae300811c83.gif" alt="" width="188"><figcaption></figcaption></figure></div> - Network accessline 10890
In our [free gpt-oss RL notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) we explore how to counter reward hacking in a code generation setting and showcase tangible solutions to - Network accessline 10908
LLMs often struggle with tasks that involve complex environments. However, by applying [reinforcement learning](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) (RL) and designing a custom [reward function](https://docs. - Network accessline 10910
RL can be adapted for tasks such as auto kernel or strategy creation. This tutorial shows how to train **gpt-oss** with [**GRPO**](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide#from-rlhf-ppo-to-grpo-and-rlvr) and Unslo - Network accessline 10914
| [2048 notebook](https://colab.research.google.com/github/openai/gpt-oss/blob/main/examples/reinforcement-fine-tuning.ipynb) (Official OpenAI example) | [Kernel generation notebook](https://colab.research.google.com/github/unslothai/notebo - Network accessline 10974
Unsloth now supports NVIDIA’s Blackwell architecture GPUs, including RTX 50-series GPUs (5060–5090), RTX PRO 6000, and GPUS such as B200, B40, GB100, GB102 and more! You can read the official [NVIDIA blogpost here](https://developer.nvidia. - Network accessline 10976
Unsloth is now compatible with every NVIDIA GPU from 2018+ including the [DGX Spark](https://docs.unsloth.ai/basics/fine-tuning-llms-with-nvidia-dgx-spark-and-unsloth). - Network accessline 10978
> **Our new** [**Docker image**](#docker) **supports Blackwell. Run the Docker image and start training!** [**Guide**](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) - Network accessline 11024
By the end of this tutorial, you will create a custom chatbot by **finetuning Llama-3** with [**Unsloth**](https://github.com/unslothai/unsloth) for free. It can run locally via [**Ollama**](https://github.com/ollama/ollama) on your PC, or - Network accessline 11026
[Credential-related source omitted] - Network accessline 11028
**Unsloth** makes finetuning much easier, and can automatically export the finetuned model to **Ollama** with integrated automatic `Modelfile` creation! If you need help, you can join our Discord server: <https://discord.com/invite/unsloth> - Network accessline 11030
{% hint style="warning" %} **If you’d like to copy or save the code, everything is available in our** [**Ollama Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb)**. You c - Network accessline 11031
**If you’d like to copy or save the code, everything is available in our** [**Ollama Colab notebook**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb)**. You can use it directly there or - Network accessline 11036
[Unsloth](https://github.com/unslothai/unsloth) makes finetuning LLMs like Llama-3, Mistral, Phi-3 and Gemma 2x faster, use 70% less memory, and with no degradation in accuracy! We will be using Google Colab which provides a free GPU during - Network accessline 11038
* [Ollama Llama-3 Alpaca](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb) (notebook which we will be using) - Network accessline 11039
* [CSV/Excel Ollama Guide](https://colab.research.google.com/drive/1VYkncZMfGFkeCEgN2IzbZIKEDkyQuJAS?usp=sharing) - Network accessline 11043
[Credential-related source omitted] - Network accessline 11047
[Ollama ](https://github.com/ollama/ollama)allows you to run language models from your own computer in a quick and simple way! It quietly launches a program which can run a language model like Llama-3 in the background. If you suddenly want - Network accessline 11049
[Credential-related source omitted] - Network accessline 11053
[Credential-related source omitted] - Network accessline 11063
[Credential-related source omitted] - Network accessline 11071
[Credential-related source omitted] - Network accessline 11083
[Credential-related source omitted] - Network accessline 11089
[Credential-related source omitted] - Network accessline 11110
Options include `True`, `False` and `"unsloth"`. We suggest `"unsloth"` since we reduce memory usage by an extra 30% and support extremely long context finetunes.You can read up here: <https://unsloth.ai/blog/long-context> for more details. - Network accessline 11121
[Credential-related source omitted] - Network accessline 11125
You can access the GPT4 version of the Alpaca dataset here: <https://huggingface.co/datasets/vicgalle/alpaca-gpt4>. An older first version of the dataset is here: <https://github.com/tatsu-lab/stanford_alpaca>. Below shows some examples of - Network accessline 11127
[Credential-related source omitted] - Network accessline 11131
[Credential-related source omitted] - Network accessline 11137
[Credential-related source omitted] - Network accessline 11143
[Credential-related source omitted] - Network accessline 11147
[Credential-related source omitted] - Network accessline 11151
To access the Titanic finetuning notebook or if you want to upload a CSV or Excel file, go here: <https://colab.research.google.com/drive/1VYkncZMfGFkeCEgN2IzbZIKEDkyQuJAS?usp=sharing> - Network accessline 11153
[Credential-related source omitted] - Network accessline 11163
[Credential-related source omitted] - Network accessline 11189
[Credential-related source omitted] - Network accessline 11193
[Credential-related source omitted] - Network accessline 11199
[Credential-related source omitted] - Network accessline 11205
[Credential-related source omitted] - Network accessline 11209
[Credential-related source omitted] - Network accessline 11213
[Credential-related source omitted] - Network accessline 11217
[Credential-related source omitted] - Network accessline 11221
[Credential-related source omitted] - Network accessline 11223
Or in the Titanic prediction task where you had to predict if a passenger died or survived in this Colab notebook which includes CSV and Excel uploading: <https://colab.research.google.com/drive/1VYkncZMfGFkeCEgN2IzbZIKEDkyQuJAS?usp=sharin - Network accessline 11225
[Credential-related source omitted] - Network accessline 11231
[Credential-related source omitted] - Network accessline 11246
[Credential-related source omitted] - Network accessline 11252
[Credential-related source omitted] - Network accessline 11256
[Credential-related source omitted] - Network accessline 11262
We can now save the finetuned model as a small 100MB file called a LoRA adapter like below. You can instead push to the Hugging Face hub as well if you want to upload your model! Remember to get a Hugging Face token via <https://huggingface - Network accessline 11264
[Credential-related source omitted] - Network accessline 11268
[Credential-related source omitted] - Network accessline 11274
[Credential-related source omitted] - Network accessline 11278
[Credential-related source omitted] - Network accessline 11282
Head over to <https://github.com/ggerganov/llama.cpp> to learn more about GGUF. We also have some manual instructions of how to export to GGUF if you want here: <https://github.com/unslothai/unsloth/wiki#manually-saving-to-gguf> - Network accessline 11286
[Credential-related source omitted] - Network accessline 11290
[Credential-related source omitted] - Network accessline 11294
[Credential-related source omitted] - Network accessline 11300
[Credential-related source omitted] - Network accessline 11304
[Credential-related source omitted] - Network accessline 11310
[Credential-related source omitted] - Network accessline 11314
[Credential-related source omitted] - Network accessline 11316
[Credential-related source omitted] - Network accessline 11320
[Credential-related source omitted] - Network accessline 11324
[Credential-related source omitted] - Network accessline 11328
If you want to learn how to do reward modelling, do continued pretraining, export to vLLM or GGUF, do text completion, or learn more about finetuning tips and tricks, head over to our [Github](https://github.com/unslothai/unsloth#-finetune- - Network accessline 11330
If you need any help on finetuning, you can also join our Discord server [here](https://discord.gg/unsloth). If you want help with Ollama, you can also join their server [here](https://discord.gg/ollama). - Network accessline 11334
To access our Alpaca dataset example click [here](https://colab.research.google.com/drive/1WZDi7APtQ9VsvOrQSSC5DDtxq159j8iZ?usp=sharing), and our CSV / Excel finetuning guide is [here](https://colab.research.google.com/drive/1VYkncZMfGFkeCE - Network accessline 11369
## https://github.com/ggerganov/llama.cpp/blob/master/examples/quantize/quantize.cpp#L19 - Network accessline 11371
**URL:** llms-txt#https://github.com/ggerganov/llama.cpp/blob/master/examples/quantize/quantize.cpp#l19 - Network accessline 11396
Google releases Gemma 3 with a new 270M model and the previous 1B, 4B, 12B, and 27B sizes. The 270M and 1B are text-only, while larger models handle both text and vision. We provide GGUFs, and a guide of how to run it effectively, and how t - Network accessline 11398
{% hint style="success" %} **NEW Aug 14, 2025 Update:** Try our fine-tuning [Gemma 3 (270M) notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(270M\).ipynb) and [GGUFs to run](https://huggingface.co - Network accessline 11399
**NEW Aug 14, 2025 Update:** Try our fine-tuning [Gemma 3 (270M) notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(270M\).ipynb) and [GGUFs to run](https://huggingface.co/collections/unsloth/gemma- - Network accessline 11401
Also see our [Gemma 3n Guide](https://docs.unsloth.ai/models/gemma-3-how-to-run-and-fine-tune/gemma-3n-how-to-run-and-fine-tune). - Network accessline 11408
* Fine-tune Gemma 3 (4B) with vision support using our [free Colab notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision.ipynb) - Network accessline 11417
| GGUF - Network accessline 11419
| <ul><li><a href="https://huggingface.co/unsloth/gemma-3-270m-it-GGUF">270M</a> - new</li><li><a href="https://huggingface.co/unsloth/gemma-3-1b-it-GGUF">1B</a></li><li><a href="https://huggingface.co/unsloth/gemma-3-4b-it-GGUF">4B</a></li - Network accessline 11444
To run the models on your phone, we recommend using any mobile app that can run GGUFs locally on edge devices like phones. After fine-tuning you can export it to GGUF then run it locally on your phone. Ensure your phone has enough RAM/power - Network accessline 11458
1. Obtain the latest `llama.cpp` on [GitHub here](https://github.com/ggml-org/llama.cpp). You can follow the build instructions below as well. Change `-DGGML_CUDA=ON` to `-DGGML_CUDA=OFF` if you don't have a GPU or just want CPU inference. - Network accessline 11462
3. **OR** download the model via (after installing `pip install huggingface_hub hf_transfer` ). You can choose Q4\_K\_M, or other quantized versions (like BF16 full precision). More versions at: <https://huggingface.co/unsloth/gemma-3-27b-i - Network accessline 11479
apt-get update apt-get install pciutils -y curl -fsSL https://ollama.com/install.sh | sh - Dangerous shell operationline 11481
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 11481
curl -fsSL https://ollama.com/install.sh | sh - Network accessline 11491
apt-get update apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 11492
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y - Network accessline 11493
git clone https://github.com/ggerganov/llama.cpp - Network accessline 11514
At [Unsloth](https://app.gitbook.com/o/HpyELzcNe0topgVLGCZY/s/xhOjnexMCB3dmuQFQ2Zq/), our mission is to make AI as accurate and accessible as possible. Train, run, evaluate and save gpt-oss, Llama, DeepSeek, TTS, Qwen, Mistral, Gemma LLMs 2 - Network accessline 11518
<a href="beginner-start-here" class="button primary">Get started</a> <a href="https://github.com/unslothai/unsloth" class="button secondary">Our GitHub</a> - Network accessline 11520
[Credential-related source omitted] - Network accessline 11523
{% column %} {% content-ref url="fine-tuning-llms-guide" %} [fine-tuning-llms-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide) - Network accessline 11524
{% content-ref url="fine-tuning-llms-guide" %} [fine-tuning-llms-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide) {% endcontent-ref %} - Network accessline 11525
[fine-tuning-llms-guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide) - Network accessline 11528
{% content-ref url="unsloth-notebooks" %} [unsloth-notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) - Network accessline 11529
[unsloth-notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) - Network accessline 11532
{% column %} {% content-ref url="all-our-models" %} [all-our-models](https://docs.unsloth.ai/get-started/all-our-models) - Network accessline 11533
{% content-ref url="all-our-models" %} [all-our-models](https://docs.unsloth.ai/get-started/all-our-models) {% endcontent-ref %} - Network accessline 11534
[all-our-models](https://docs.unsloth.ai/get-started/all-our-models) - Network accessline 11537
{% content-ref url="../models/tutorials-how-to-fine-tune-and-run-llms" %} [tutorials-how-to-fine-tune-and-run-llms](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms) - Network accessline 11538
[tutorials-how-to-fine-tune-and-run-llms](https://docs.unsloth.ai/models/tutorials-how-to-fine-tune-and-run-llms) - Network accessline 11543
[Credential-related source omitted] - Network accessline 11545
* Unsloth streamlines model training locally and on Colab/Kaggle, covering loading, quantization, training, evaluation, saving, exporting, and integration with inference engines like Ollama, llama.cpp, and vLLM. * We directly collaborate wi - Network accessline 11546
* We directly collaborate with teams behind [gpt-oss](https://docs.unsloth.ai/new/gpt-oss-how-to-run-and-fine-tune#unsloth-fixes-for-gpt-oss), [Qwen3](https://www.reddit.com/r/LocalLLaMA/comments/1kaodxu/qwen3_unsloth_dynamic_ggufs_128k_con - Network accessline 11547
* Unsloth is the only training framework to support all model types: [vision](https://docs.unsloth.ai/basics/vision-fine-tuning), [text-to-speech (TTS)](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning), BERT, [reinforcement l - Network accessline 11549
* Supports **full-finetuning**, pretraining, 4-bit, 16-bit and **8-bit** training. * The most efficient RL library, using 80% less VRAM. Supports GRPO, GSPO etc. * Supports **all models**: [TTS,](https://docs.unsloth.ai/basics/text-to-speec - Network accessline 11550
* The most efficient RL library, using 80% less VRAM. Supports GRPO, GSPO etc. * Supports **all models**: [TTS,](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning) multimodal, [BERT](https://docs.unsloth.ai/get-started/unsloth-n - Network accessline 11551
* Supports **all models**: [TTS,](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning) multimodal, [BERT](https://docs.unsloth.ai/get-started/unsloth-notebooks#other-important-notebooks) and more. Any model that works in transform - Network accessline 11552
* **0% loss in accuracy** - no approximation methods - all exact. * [MultiGPU](https://docs.unsloth.ai/basics/multi-gpu-training-with-unsloth) works already but a much better version is coming! * Unsloth supports Linux, Windows, Colab, Kagg - Network accessline 11553
* [MultiGPU](https://docs.unsloth.ai/basics/multi-gpu-training-with-unsloth) works already but a much better version is coming! - Network accessline 11554
* Unsloth supports Linux, Windows, Colab, Kaggle, **NVIDIA** and [**AMD**](https://docs.unsloth.ai/new/fine-tuning-llms-on-amd-gpus-with-unsloth) & **Intel**. See: - Network accessline 11556
{% content-ref url="beginner-start-here/unsloth-requirements" %} [unsloth-requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) - Network accessline 11557
[unsloth-requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements) - Network accessline 11562
Use our official **Docker image**: `unsloth/unsloth`. Read our [**Docker guide**](https://docs.unsloth.ai/get-started/install-and-update/docker)**.** - Network accessline 11564
For Windows install instructions, see [here](https://docs.unsloth.ai/get-started/install-and-update/windows-installation). - Network accessline 11566
{% content-ref url="install-and-update" %} [install-and-update](https://docs.unsloth.ai/get-started/install-and-update) - Network accessline 11567
[install-and-update](https://docs.unsloth.ai/get-started/install-and-update) - Network accessline 11572
[**Fine-tuning** an LLM](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide) customizes its behavior, enhances domain knowledge, and optimizes performance for specific tasks. By fine-tuning a pre-trained model (e.g. Llama-3.1-8B) on - Network accessline 11578
[**Reinforcement Learning (RL)**](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) is where an "agent" learns to make decisions by interacting with an environment and receiving **feedback** in the form of **rewards** or - Network accessline 11592
{% content-ref url="beginner-start-here/faq-+-is-fine-tuning-right-for-me" %} [faq-+-is-fine-tuning-right-for-me](https://docs.unsloth.ai/get-started/beginner-start-here/faq-+-is-fine-tuning-right-for-me) - Network accessline 11593
[faq-+-is-fine-tuning-right-for-me](https://docs.unsloth.ai/get-started/beginner-start-here/faq-+-is-fine-tuning-right-for-me) - Network accessline 11596
{% content-ref url="reinforcement-learning-rl-guide" %} [reinforcement-learning-rl-guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) - Network accessline 11597
[reinforcement-learning-rl-guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) - Network accessline 11600
[Credential-related source omitted] - Network accessline 11706
Local training can be complex due to dependency hell or breaking environments. Unsloth’s [Docker image](https://hub.docker.com/r/unsloth/unsloth) can bypass these issues. No setup is needed: pull and run the image and start training. - Network accessline 11708
* **Unsloth official Docker image:** [**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) - Network accessline 11712
Unsloth’s Docker image is stable, up-to-date and works in [supported setups](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements#system-requirements) like Windows. - Network accessline 11728
Install Docker via [Linux](https://docs.docker.com/engine/install/) or [Desktop](https://docs.docker.com/desktop/) (other).\ - Network accessline 11729
Then install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installation): - Dangerous shell operationline 11732
</strong>sudo apt-get update && sudo apt-get install -y \ - Network accessline 11739
[Credential-related source omitted] - Network accessline 11744
[**`unsloth/unsloth`**](https://hub.docker.com/r/unsloth/unsloth) is Unsloth's only Docker image. For [Blackwell](https://docs.unsloth.ai/basics/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) and 50-series GPUs, use this same im - Network accessline 11746
[Credential-related source omitted] - Network accessline 11751
Go to [http://localhost:8888](http://localhost:8888/) and open Unsloth. - Network accessline 11753
[Credential-related source omitted] - Network accessline 11757
[Credential-related source omitted] - Network accessline 11762
If you're new, follow our step-by-step [Fine-tuning Guide](https://docs.unsloth.ai/get-started/fine-tuning-llms-guide), [RL Guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) or just save/copy any of our premade [no - Network accessline 11764
[Credential-related source omitted] - Access to secretsline 11791
[Credential-related source omitted] - Access to secretsline 11793
[Credential-related source omitted] - Network accessline 11812
[Credential-related source omitted] - Network accessline 11822
[Credential-related source omitted] - Network accessline 11848
It's the reason models learn to modify unit tests to pass coding challenges, and these are critical blockers for real world deployment. Some other good examples are from [Wikipedia](https://en.wikipedia.org/wiki/Reward_hacking). - Network accessline 11850
<div align="center"><figure><img src="https://i.pinimg.com/originals/55/e0/1b/55e01b94a9c5546b61b59ae300811c83.gif" alt="" width="188"><figcaption></figcaption></figure></div> - Network accessline 11852
**Can you counter reward hacking? Yes!** In our [free gpt-oss RL notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) we explore how to counter reward hacking in a code generation s - Network accessline 11876
Unsloth works on Linux, Windows, NVIDIA, AMD, Google Colab and more. See our [system requirements](https://docs.unsloth.ai/get-started/beginner-start-here/unsloth-requirements). - Network accessline 11918
See <https://docs.vllm.ai/en/stable/getting_started/installation> for more details - Access to secretsline 11960
[Credential-related source omitted] - Network accessline 12004
{% hint style="warning" %} Do **NOT** use this if you have [Conda](https://docs.unsloth.ai/get-started/install-and-update/conda-install). - Network accessline 12005
Do **NOT** use this if you have [Conda](https://docs.unsloth.ai/get-started/install-and-update/conda-install). - Network accessline 12029
pip uninstall unsloth unsloth_zoo -y && pip install --no-deps git+https://github.com/unslothai/unsloth_zoo.git && pip install --no-deps git+https://github.com/unslothai/unsloth.git - Network accessline 12034
pip install --upgrade --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git - Network accessline 12035
pip install --upgrade --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth-zoo.git - Network accessline 12040
pip install --upgrade pip pip install "unsloth[cu121-torch240] @ git+https://github.com/unslothai/unsloth.git" - Network accessline 12041
pip install "unsloth[cu121-torch240] @ git+https://github.com/unslothai/unsloth.git"
bundled/skills/usfiscaldata/SKILL.md
- Network accessline 13
**Base URL:** `https://api.fiscaldata.treasury.gov/services/api/fiscal_service` - Network accessline 21
BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" - Network accessline 23
# Get the current national debt (Debt to the Penny) resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={ - Network accessline 24
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={ - Network accessline 33
# Get Treasury exchange rates for recent quarters resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={ - Network accessline 34
resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={ - Network accessline 131
params = params or {} params["page[size]"] = 10000 # max size to minimize requests resp = requests.get(f"{BASE_URL}{endpoint}", params=params) - Network accessline 132
params["page[size]"] = 10000 # max size to minimize requests resp = requests.get(f"{BASE_URL}{endpoint}", params=params) result = resp.json() - Network accessline 133
resp = requests.get(f"{BASE_URL}{endpoint}", params=params) - Network accessline 144
# Sum all deposits/withdrawals by record_date and transaction type resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={ - Network accessline 145
resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={
bundled/skills/usfiscaldata/references/api-basics.md
- Network accessline 16
Base URL: https://api.fiscaldata.treasury.gov/services/api/fiscal_service - Network accessline 20
Full URL: https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny?fields=record_date,tot_pub_debt_out_amt&sort=-record_date&page[size]=5 - Network accessline 21
https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny?fields=record_date,tot_pub_debt_out_amt&sort=-record_date&page[size]=5 - Network accessline 68
def get_with_retry(url, params, retries=3): for attempt in range(retries): resp = requests.get(url, params=params) - Network accessline 69
for attempt in range(retries): resp = requests.get(url, params=params) if resp.status_code == 429: - Network accessline 70
resp = requests.get(url, params=params) - Network accessline 86
The [Fiscal Service Data Registry](https://fiscal.treasury.gov/data-registry/index.html) contains field definitions, authoritative sources, data types, and formats across federal government data.
bundled/skills/usfiscaldata/references/datasets-debt.md
- Network accessline 20
# Current national debt resp = requests.get( - Network accessline 21
resp = requests.get( - Network accessline 22
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny", - Network accessline 28
# Debt over the last year resp = requests.get( - Network accessline 29
resp = requests.get( - Network accessline 30
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny", - Network accessline 56
# Full historical debt series resp = requests.get( - Network accessline 57
resp = requests.get( - Network accessline 58
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/historical_debt_outstanding", - Network accessline 105
# TROR data, sorted by funding type resp = requests.get( - Network accessline 106
resp = requests.get( - Network accessline 107
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/debt/tror", - Network accessline 137
# Get total interest expense by month resp = requests.get( - Network accessline 138
resp = requests.get( - Network accessline 139
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/interest_expense",
bundled/skills/usfiscaldata/references/datasets-fiscal.md
- Network accessline 38
# Get current Treasury General Account (TGA) balance resp = requests.get( - Network accessline 39
resp = requests.get( - Network accessline 40
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/dts/operating_cash_balance", - Network accessline 46
# Get deposits and withdrawals for a specific period resp = requests.get( - Network accessline 47
resp = requests.get( - Network accessline 48
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/dts/deposits_withdrawals_operating_cash", - Network accessline 60
# Get sum of today's transaction amounts by transaction type resp = requests.get( - Network accessline 61
resp = requests.get( - Network accessline 62
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/dts/deposits_withdrawals_operating_cash", - Network accessline 114
# MTS Table 1: Summary of receipts and outlays resp = requests.get( - Network accessline 115
resp = requests.get( - Network accessline 116
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/mts/mts_table_1", - Network accessline 124
# MTS Table 9: Get line 120 (Total Receipts) for most recent period resp = requests.get( - Network accessline 125
resp = requests.get( - Network accessline 126
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/mts/mts_table_9",
bundled/skills/usfiscaldata/references/datasets-interest-rates.md
- Network accessline 20
# Get average rates for all marketable securities, most recent month resp = requests.get( - Network accessline 21
resp = requests.get( - Network accessline 22
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/avg_interest_rates", - Network accessline 33
# Historical rate for a specific security type resp = requests.get( - Network accessline 34
resp = requests.get( - Network accessline 35
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/avg_interest_rates", - Network accessline 78
# Get all current exchange rates (latest quarter) resp = requests.get( - Network accessline 79
resp = requests.get( - Network accessline 80
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/rates_of_exchange", - Network accessline 89
# Euro rate history resp = requests.get( - Network accessline 90
resp = requests.get( - Network accessline 91
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/rates_of_exchange",
bundled/skills/usfiscaldata/references/datasets-securities.md
- Network accessline 27
# Get recent 10-year Treasury note auctions resp = requests.get( - Network accessline 28
resp = requests.get( - Network accessline 29
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query", - Network accessline 38
# Get all auctions in 2024 resp = requests.get( - Network accessline 39
resp = requests.get( - Network accessline 40
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query", - Network accessline 66
# Get upcoming auctions resp = requests.get( - Network accessline 67
resp = requests.get( - Network accessline 68
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/upcoming_auctions", - Network accessline 108
# Current I Bond rates resp = requests.get( - Network accessline 109
resp = requests.get( - Network accessline 110
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/i_bond_interest_rates",
bundled/skills/usfiscaldata/references/examples.md
- Network accessline 11
BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" - Network accessline 13
def fetch(endpoint, **params): - Network accessline 14
resp = requests.get(f"{BASE_URL}{endpoint}", params=params) - Network accessline 22
# Current total public debt result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 23
result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 29
# Debt trend over last 5 years result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 30
result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 44
# All current Treasury exchange rates result = fetch("/v1/accounting/od/rates_of_exchange", - Network accessline 45
result = fetch("/v1/accounting/od/rates_of_exchange", - Network accessline 67
# Recent 10-year note auctions result = fetch("/v1/accounting/od/auctions_query", - Network accessline 68
result = fetch("/v1/accounting/od/auctions_query", - Network accessline 80
# Auction yield trend: 2-year vs 10-year def get_auction_yields(term, n=24): result = fetch("/v1/accounting/od/auctions_query", - Network accessline 81
def get_auction_yields(term, n=24): result = fetch("/v1/accounting/od/auctions_query", fields="record_date,security_term,accepted_comp_bid_rate_amt", - Network accessline 82
result = fetch("/v1/accounting/od/auctions_query", - Network accessline 102
# Recent Treasury General Account (TGA) balance result = fetch("/v1/accounting/dts/operating_cash_balance", - Network accessline 103
result = fetch("/v1/accounting/dts/operating_cash_balance", - Network accessline 111
# Monthly total receipts and withdrawals result = fetch("/v1/accounting/dts/deposits_withdrawals_operating_cash", - Network accessline 112
result = fetch("/v1/accounting/dts/deposits_withdrawals_operating_cash", - Network accessline 125
# Federal budget receipts and outlays (MTS Table 1) result = fetch("/v1/accounting/mts/mts_table_1", - Network accessline 126
result = fetch("/v1/accounting/mts/mts_table_1", - Network accessline 141
# Average interest rates on all marketable Treasury securities result = fetch("/v2/accounting/od/avg_interest_rates", - Network accessline 142
result = fetch("/v2/accounting/od/avg_interest_rates", - Network accessline 153
# I Bond rates history result = fetch("/v2/accounting/od/i_bond_interest_rates", - Network accessline 154
result = fetch("/v2/accounting/od/i_bond_interest_rates", - Network accessline 169
# Total debt at end of FY fy_end = f"{fy}-09-30" result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 170
fy_end = f"{fy}-09-30" result = fetch("/v2/accounting/od/debt_to_penny", filter=f"record_date:lte:{fy_end}", - Network accessline 171
result = fetch("/v2/accounting/od/debt_to_penny", - Network accessline 176
# Interest expense for FY result = fetch("/v2/accounting/od/interest_expense", - Network accessline 177
result = fetch("/v2/accounting/od/interest_expense", - Network accessline 207
BASE_URL <- "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" - Network accessline 246
result = fetch("/v2/accounting/od/debt_to_penny", **{"page[size]": 1}) - Network accessline 256
Browse the full list of 54 datasets and 182 endpoints at: - `https://fiscaldata.treasury.gov/datasets/` — searchable dataset catalog - Network accessline 257
- `https://fiscaldata.treasury.gov/datasets/` — searchable dataset catalog - Network accessline 258
- `https://fiscaldata.treasury.gov/api-documentation/#list-of-endpoints-table` — full endpoint table
bundled/skills/usfiscaldata/references/parameters.md
- Network accessline 124
base = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" - Network accessline 127
while True: resp = requests.get(f"{base}{endpoint}", params=params) - Network accessline 128
resp = requests.get(f"{base}{endpoint}", params=params) - Network accessline 149
"page[number]": 1 } resp = requests.get( - Network accessline 150
} resp = requests.get( "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/rates_of_exchange", - Network accessline 151
resp = requests.get( - Network accessline 152
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/rates_of_exchange",
bundled/skills/usfiscaldata/references/response-format.md
- Network accessline 92
resp = requests.get(url, params=params) - Network accessline 118
def api_to_dataframe(endpoint, params=None): """Fetch API data and return a typed DataFrame.""" base = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" - Network accessline 119
"""Fetch API data and return a typed DataFrame.""" base = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" resp = requests.get(f"{base}{endpoint}", params=params) - Network accessline 120
base = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service" resp = requests.get(f"{base}{endpoint}", params=params) resp.raise_for_status() - Network accessline 121
resp = requests.get(f"{base}{endpoint}", params=params) - Network accessline 157
resp = requests.get( - Network accessline 158
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny", - Network accessline 171
resp = requests.get( - Network accessline 172
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/debt_to_penny",
bundled/skills/uspto-database/SKILL.md
- Network accessline 38
- Access to patent data through June 30, 2025 - 45 requests/minute rate limit - **Base URL**: `https://search.patentsview.org/api/v1/` - Network accessline 40
- **Base URL**: `https://search.patentsview.org/api/v1/` - Network accessline 49
- Trademark status, ownership, prosecution history - Search by serial or registration number - **Base URL**: `https://tsdrapi.uspto.gov/ts/cd/` - Network accessline 51
- **Base URL**: `https://tsdrapi.uspto.gov/ts/cd/` - Network accessline 69
USPTO APIs require an API key. Register at: **https://account.uspto.gov/api-manager/** - Network accessline 70
**https://account.uspto.gov/api-manager/** - Network accessline 72
API key for **PatentSearch API** is provided by PatentsView. Register at: **https://patentsview.org/api-v01-information-page** - Network accessline 73
**https://patentsview.org/api-v01-information-page** - Access to secretsline 77
[Credential-related source omitted] - Access to secretsline 78
[Credential-related source omitted] - Network accessline 153
url = "https://search.patentsview.org/api/v1/patent" - Access to secretsline 155
[Credential-related source omitted] - Network accessline 172
response = requests.post(url, headers=headers, json=query) - Access to secretsline 354
[Credential-related source omitted] - Access to secretsline 356
[Credential-related source omitted] - Network accessline 404
**Base URL**: `https://assignment-api.uspto.gov/patent/v1.4/` - Network accessline 411
[Credential-related source omitted] - Access to secretsline 411
[Credential-related source omitted] - Network accessline 412
url = f"https://assignment-api.uspto.gov/patent/v1.4/assignment/patent/{patent_number}" - Access to secretsline 413
[Credential-related source omitted] - Network accessline 415
response = requests.get(url, headers=headers) - Access to secretsline 419
[Credential-related source omitted] - Network accessline 434
[Credential-related source omitted] - Access to secretsline 434
[Credential-related source omitted] - Network accessline 435
url = "https://assignment-api.uspto.gov/patent/v1.4/assignment/search" - Access to secretsline 436
[Credential-related source omitted] - Network accessline 439
response = requests.post(url, headers=headers, json=data) - Access to secretsline 501
[Credential-related source omitted] - Access to secretsline 511
[Credential-related source omitted] - Network accessline 520
# 3. Get assignment history import requests assign_url = f"https://assignment-api.uspto.gov/patent/v1.4/assignment/patent/{patent_number}" - Network accessline 521
[Credential-related source omitted] - Network accessline 522
[Credential-related source omitted] - Network accessline 523
[Credential-related source omitted] - Access to secretsline 523
[Credential-related source omitted] - Network accessline 585
### API Documentation - **PatentSearch API**: https://search.patentsview.org/docs/ - Network accessline 586
- **PatentSearch API**: https://search.patentsview.org/docs/ - Network accessline 587
- **USPTO Developer Portal**: https://developer.uspto.gov/ - Network accessline 588
- **USPTO Open Data Portal**: https://data.uspto.gov/ - Network accessline 589
- **API Key Registration**: https://account.uspto.gov/api-manager/ - Network accessline 591
### Python Libraries - **uspto-opendata-python**: https://pypi.org/project/uspto-opendata-python/ - Network accessline 592
- **uspto-opendata-python**: https://pypi.org/project/uspto-opendata-python/ - Network accessline 593
- **USPTO Docs**: https://docs.ip-tools.org/uspto-opendata-python/
bundled/skills/uspto-database/references/additional_apis.md
- Access to secretsline 56
[Credential-related source omitted] - Network accessline 124
**Base URL:** `https://assignment-api.uspto.gov/patent/` - Network accessline 168
[Credential-related source omitted] - Access to secretsline 168
[Credential-related source omitted] - Network accessline 169
[Credential-related source omitted] - Network accessline 170
url = f"https://assignment-api.uspto.gov/patent/v1.4/assignment/patent/{patent_number}" - Access to secretsline 171
[Credential-related source omitted] - Network accessline 173
response = requests.get(url, headers=headers) - Network accessline 179
[Credential-related source omitted] - Access to secretsline 179
[Credential-related source omitted] - Network accessline 180
[Credential-related source omitted] - Network accessline 181
url = "https://assignment-api.uspto.gov/patent/v1.4/assignment/search" - Access to secretsline 182
[Credential-related source omitted] - Network accessline 185
response = requests.post(url, headers=headers, json=data) - Access to secretsline 295
[Credential-related source omitted] - Access to secretsline 300
[Credential-related source omitted] - Access to secretsline 303
[Credential-related source omitted] - Access to secretsline 312
[Credential-related source omitted] - Access to secretsline 319
[Credential-related source omitted] - Access to secretsline 322
[Credential-related source omitted] - Access to secretsline 325
[Credential-related source omitted] - Access to secretsline 328
[Credential-related source omitted] - Access to secretsline 331
[Credential-related source omitted] - Access to secretsline 334
[Credential-related source omitted] - Access to secretsline 342
[Credential-related source omitted] - Access to secretsline 347
[Credential-related source omitted] - Access to secretsline 355
[Credential-related source omitted] - Access to secretsline 356
[Credential-related source omitted] - Access to secretsline 357
[Credential-related source omitted] - Network accessline 384
All APIs require registration at: **https://account.uspto.gov/api-manager/** - Network accessline 385
**https://account.uspto.gov/api-manager/** - Network accessline 391
- **Developer Portal**: https://developer.uspto.gov/ - Network accessline 392
- **Open Data Portal**: https://data.uspto.gov/ - Network accessline 393
- **API Catalog**: https://developer.uspto.gov/api-catalog
bundled/skills/uspto-database/references/patentsearch_api.md
- Network accessline 7
**Base URL:** `https://search.patentsview.org/api/v1/` - Access to secretsline 14
[Credential-related source omitted] - Network accessline 17
Register for an API key at: https://account.uspto.gov/api-manager/ - Network accessline 176
[Credential-related source omitted] - Access to secretsline 176
[Credential-related source omitted] - Access to secretsline 177
[Credential-related source omitted] - Network accessline 197
url = "https://search.patentsview.org/api/v1/patent" - Access to secretsline 199
[Credential-related source omitted] - Network accessline 214
response = requests.post(url, headers=headers, json=data) - Network accessline 234
Refer to the full field dictionary at: https://search.patentsview.org/docs/ - Network accessline 264
- **Official Documentation**: https://search.patentsview.org/docs/ - Network accessline 265
- **API Key Registration**: https://account.uspto.gov/api-manager/
bundled/skills/uspto-database/references/peds_api.md
- Network accessline 209
- **Library Documentation**: https://docs.ip-tools.org/uspto-opendata-python/ - Network accessline 210
- **PyPI Package**: https://pypi.org/project/uspto-opendata-python/ - Network accessline 211
- **GitHub Repository**: https://github.com/ip-tools/uspto-opendata-python - Network accessline 212
- **USPTO PEDS Portal**: https://ped.uspto.gov/
bundled/skills/uspto-database/references/trademark_api.md
- Network accessline 18
**Base URL:** `https://tsdrapi.uspto.gov/ts/cd/` - Network accessline 22
Requires API key registration at: https://account.uspto.gov/api-manager/ - Access to secretsline 26
[Credential-related source omitted] - Network accessline 39
[Credential-related source omitted] - Network accessline 40
"https://tsdrapi.uspto.gov/ts/cd/casedocs/sn87654321/info.json" - Network accessline 111
[Credential-related source omitted] - Access to secretsline 111
[Credential-related source omitted] - Network accessline 112
[Credential-related source omitted] - Network accessline 113
url = f"https://tsdrapi.uspto.gov/ts/cd/casedocs/sn{serial_number}/info.json" - Access to secretsline 114
[Credential-related source omitted] - Network accessline 116
response = requests.get(url, headers=headers) - Access to secretsline 123
[Credential-related source omitted] - Network accessline 141
**Base URL:** `https://assignment-api.uspto.gov/trademark/` - Access to secretsline 147
[Credential-related source omitted] - Network accessline 228
[Credential-related source omitted] - Access to secretsline 228
[Credential-related source omitted] - Network accessline 229
[Credential-related source omitted] - Network accessline 230
url = f"https://assignment-api.uspto.gov/trademark/v1.4/assignment/application/{registration_number}" - Access to secretsline 231
[Credential-related source omitted] - Network accessline 233
response = requests.get(url, headers=headers) - Access to secretsline 240
[Credential-related source omitted] - Access to secretsline 263
[Credential-related source omitted] - Access to secretsline 265
[Credential-related source omitted] - Access to secretsline 288
[Credential-related source omitted] - Access to secretsline 290
[Credential-related source omitted] - Access to secretsline 311
[Credential-related source omitted] - Access to secretsline 321
[Credential-related source omitted] - Network accessline 354
- **TSDR API**: https://developer.uspto.gov/api-catalog/tsdr-data-api - Network accessline 355
- **Assignment API**: https://developer.uspto.gov/api-catalog/trademark-assignment-search-data-api - Network accessline 356
- **API Key Registration**: https://account.uspto.gov/api-manager/ - Network accessline 357
- **Trademark Search**: https://tmsearch.uspto.gov/ - Network accessline 358
- **Swagger Documentation**: https://developer.uspto.gov/swagger/tsdr-api-v1
bundled/skills/uspto-database/scripts/patent_search.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 8
Requires: - requests library: pip install requests - USPTO API key from https://account.uspto.gov/api-manager/ - Network accessline 10
- USPTO API key from https://account.uspto.gov/api-manager/ - Access to secretsline 13
[Credential-related source omitted] - Network accessline 27
BASE_URL = "https://search.patentsview.org/api/v1" - Access to secretsline 29
[Credential-related source omitted] - Access to secretsline 34
[Credential-related source omitted] - Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 37
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted] - Access to secretsline 41
[Credential-related source omitted] - Network accessline 70
response = requests.post(url, headers=self.headers, json=data)
bundled/skills/uspto-database/scripts/peds_client.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/uspto-database/scripts/trademark_client.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 8
Requires: - requests library: pip install requests - USPTO API key from https://account.uspto.gov/api-manager/ - Network accessline 10
- USPTO API key from https://account.uspto.gov/api-manager/ - Access to secretsline 13
[Credential-related source omitted] - Network accessline 26
TSDR_BASE_URL = "https://tsdrapi.uspto.gov/ts/cd" - Network accessline 27
ASSIGNMENT_BASE_URL = "https://assignment-api.uspto.gov/trademark" - Access to secretsline 29
[Credential-related source omitted] - Access to secretsline 34
[Credential-related source omitted] - Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 37
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted] - Access to secretsline 40
[Credential-related source omitted] - Network accessline 54
try: response = requests.get(url, headers=self.headers) - Network accessline 55
response = requests.get(url, headers=self.headers) - Network accessline 75
try: response = requests.get(url, headers=self.headers) - Network accessline 76
response = requests.get(url, headers=self.headers) - Network accessline 256
Environment: Set USPTO_API_KEY environment variable with your API key from: https://account.uspto.gov/api-manager/ - Network accessline 257
[Credential-related source omitted] - Access to secretsline 257
[Credential-related source omitted] - Network accessline 258
https://account.uspto.gov/api-manager/ - Access to secretsline 273
[Credential-related source omitted] - Access to secretsline 278
[Credential-related source omitted]
bundled/skills/ux-researcher-designer/scripts/persona_generator.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/venue-templates/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 423
**Journal Author Guidelines**: - Nature: https://www.nature.com/nature/for-authors - Network accessline 424
- Nature: https://www.nature.com/nature/for-authors - Network accessline 425
- Science: https://www.science.org/content/page/instructions-authors - Network accessline 426
- PLOS: https://plos.org/resources/for-authors/ - Network accessline 427
- Cell Press: https://www.cell.com/author-guidelines - Network accessline 429
**Conference Formatting**: - NeurIPS: https://neurips.cc/Conferences/2024/CallForPapers - Network accessline 430
- NeurIPS: https://neurips.cc/Conferences/2024/CallForPapers - Network accessline 431
- ICML: https://icml.cc/Conferences/2024/StyleAuthorInstructions - Network accessline 432
- CVPR: https://cvpr.thecvf.com/Conferences/2024/AuthorGuidelines - Network accessline 434
**Grant Resources**: - NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 435
- NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 436
- NIH Forms: https://grants.nih.gov/grants/how-to-apply-application-guide.html - Network accessline 437
- DOE Funding: https://science.osti.gov/grants
bundled/skills/venue-templates/assets/journals/neurips_article.tex
- Network accessline 264
Provide links to code repository (anonymized for review, e.g., anonymous GitHub): \begin{itemize} \item Code: \url{https://anonymous.4open.science/r/project-XXXX} - Network accessline 265
\begin{itemize} \item Code: \url{https://anonymous.4open.science/r/project-XXXX} \item Data: Available upon request / at [repository] - Network accessline 266
\item Code: \url{https://anonymous.4open.science/r/project-XXXX}
bundled/skills/venue-templates/assets/posters/beamerposter_academic.tex
- Network accessline 267
\begin{minipage}[t]{0.3\textwidth} \begin{center} \qrcode[height=3cm]{https://yourlab.university.edu/paper}\\ - Network accessline 268
\begin{center} \qrcode[height=3cm]{https://yourlab.university.edu/paper}\\ \small Scan for full paper\\and supplementary materials - Network accessline 269
\qrcode[height=3cm]{https://yourlab.university.edu/paper}\\
bundled/skills/venue-templates/references/conferences_formatting.md
- Network accessline 53
**Website**: https://neurips.cc/ - Network accessline 85
**Website**: https://icml.cc/ - Network accessline 114
**Website**: https://iclr.cc/ - Network accessline 143
**Website**: https://cvpr.thecvf.com/ - Network accessline 166
**Website**: https://aaai.org/conference/aaai/ - Network accessline 205
**Website**: https://chi.acm.org/ - Network accessline 227
**Website**: https://kdd.org/ - Network accessline 252
**Website**: https://www.emnlp.org/ - Network accessline 290
**Website**: https://www.usenix.org/conference/usenixsecurity - Network accessline 333
**Website**: https://www.iscb.org/ismb - Network accessline 355
**Website**: https://www.recomb.org/ - Network accessline 376
**Website**: https://psb.stanford.edu/
bundled/skills/venue-templates/references/grants_requirements.md
- Network accessline 196
**Resources**: - NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 197
- NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 198
- NSF Fastlane: https://www.fastlane.nsf.gov/ - Network accessline 391
**Resources**: - NIH Application Guide: https://grants.nih.gov/grants/how-to-apply-application-guide.html - Network accessline 392
- NIH Application Guide: https://grants.nih.gov/grants/how-to-apply-application-guide.html - Network accessline 393
- SF424 Forms: https://grants.nih.gov/grants/how-to-apply-application-guide/forms-e/general-forms-e.pdf - Network accessline 497
**Resources**: - DOE Office of Science Funding: https://science.osti.gov/grants - Network accessline 498
- DOE Office of Science Funding: https://science.osti.gov/grants - Network accessline 499
- EERE Funding: https://www.energy.gov/eere/funding/eere-funding-opportunities - Network accessline 613
**Resources**: - DARPA Opportunities: https://www.darpa.mil/work-with-us/opportunities - Network accessline 614
- DARPA Opportunities: https://www.darpa.mil/work-with-us/opportunities - Network accessline 759
### Grant Writing Guides - NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 760
- NSF PAPPG: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg - Network accessline 761
- NIH Application Guide: https://grants.nih.gov/grants/how-to-apply-application-guide.html - Network accessline 762
- GrantForward (database): https://www.grantforward.com/ - Network accessline 763
- Pivot (database): https://pivot.proquest.com/
bundled/skills/venue-templates/references/journals_formatting.md
- Network accessline 40
**Author Guidelines**: https://www.nature.com/nature/for-authors - Network accessline 108
**Author Guidelines**: https://www.science.org/content/page/instructions-authors - Network accessline 161
**Author Guidelines**: https://journals.plos.org/plosone/s/submission-guidelines - Network accessline 205
**Author Guidelines**: https://www.cell.com/cell/authors - Network accessline 246
**Author Guidelines**: https://journals.ieeeauthorcenter.ieee.org/ - Network accessline 278
- **References**: ACM style - Format: Author. Year. Title. Journal vol, issue (Year), pages. DOI - Example: James D. Watson and Francis H. C. Crick. 1953. Molecular structure of nucleic acids. Nature 171, 4356 (1953), 737-738. https://d - Network accessline 279
- Format: Author. Year. Title. Journal vol, issue (Year), pages. DOI - Example: James D. Watson and Francis H. C. Crick. 1953. Molecular structure of nucleic acids. Nature 171, 4356 (1953), 737-738. https://doi.org/10.1038/171737a0 - **Fi - Network accessline 280
- Example: James D. Watson and Francis H. C. Crick. 1953. Molecular structure of nucleic acids. Nature 171, 4356 (1953), 737-738. https://doi.org/10.1038/171737a0 - Network accessline 287
**Author Guidelines**: https://www.acm.org/publications/authors - Network accessline 336
**Author Guidelines**: https://www.elsevier.com/authors (select specific journal) - Network accessline 361
**Author Guidelines**: https://www.biomedcentral.com/getpublished - Network accessline 388
**Author Guidelines**: https://www.frontiersin.org/guidelines/author-guidelines
bundled/skills/venue-templates/references/posters_guidelines.md
- Network accessline 188
### Color Contrast Tools - WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 189
- WebAIM Contrast Checker: https://webaim.org/resources/contrastchecker/ - Network accessline 190
- Coblis (Color Blindness Simulator): https://www.color-blindness.com/coblis-color-blindness-simulator/ - Network accessline 289
**Sources**: - Noun Project: https://thenounproject.com/ - Network accessline 290
- Noun Project: https://thenounproject.com/ - Network accessline 291
- BioRender: https://biorender.com/ (scientific illustrations) - Network accessline 292
- Font Awesome: https://fontawesome.com/ (icons) - Network accessline 435
### QR Code Generators - QR Code Generator: https://www.qr-code-generator.com/ - Network accessline 436
- QR Code Generator: https://www.qr-code-generator.com/ - Network accessline 437
- QRStuff: https://www.qrstuff.com/ - Network accessline 600
### Online Resources - Better Posters Blog: https://betterposters.blogspot.com/ - Network accessline 601
- Better Posters Blog: https://betterposters.blogspot.com/ - Network accessline 602
- Colorblind Safe Palettes: https://colorbrewer2.org/ - Network accessline 603
- BioRender (scientific illustrations): https://biorender.com/ - Network accessline 604
- Poster Design Guide (Colin Purrington): https://colinpurrington.com/tips/poster-design/
bundled/skills/venue-templates/scripts/customize_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/venue-templates/scripts/query_template.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/venue-templates/scripts/validate_format.py
bundled/skills/vercel-deploy/assets/vercel-small.svg
- Network accessline 1
<svg width="16" height="16" viewBox="0 0 1155 1155" fill="none" xmlns="http://www.w3.org/2000/svg" aria-hidden="true">
bundled/skills/vercel-deploy/scripts/deploy.sh
- Executable scriptline 1
#!/bin/bash - Network accessline 9
DEPLOY_ENDPOINT="https://codex-deploy-skills.vercel.sh/api/deploy" - Dangerous shell operationline 175
rm -rf "$TEMP_DIR" - Access to secretsline 201
[Credential-related source omitted] - Access to secretsline 204
[Credential-related source omitted] - Network accessline 238
echo "Deploying..." >&2 RESPONSE=$(curl -s -X POST "$DEPLOY_ENDPOINT" -F "file=@$TARBALL" -F "framework=$FRAMEWORK") - Network accessline 239
RESPONSE=$(curl -s -X POST "$DEPLOY_ENDPOINT" -F "file=@$TARBALL" -F "framework=$FRAMEWORK") - Network accessline 265
while [ $ATTEMPT -lt $MAX_ATTEMPTS ]; do HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" "$PREVIEW_URL") - Network accessline 266
HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" "$PREVIEW_URL")
bundled/skills/verification-quality-assurance/SKILL.md
- Network accessline 523
# Export to Prometheus npx claude-flow@alpha truth --format json | \ curl -X POST https://pushgateway.example.com/metrics/job/claude-flow \ - Network accessline 524
npx claude-flow@alpha truth --format json | curl -X POST https://pushgateway.example.com/metrics/job/claude-flow - Network accessline 525
curl -X POST https://pushgateway.example.com/metrics/job/claude-flow \ - Network accessline 528
[Credential-related source omitted] - Network accessline 529
[Credential-related source omitted] - Access to secretsline 529
[Credential-related source omitted] - Network accessline 530
[Credential-related source omitted] - Access to secretsline 530
[Credential-related source omitted] - Network accessline 534
# Custom webhook npx claude-flow@alpha truth --format json | \ curl -X POST https://metrics.example.com/api/truth \ - Network accessline 535
npx claude-flow@alpha truth --format json | curl -X POST https://metrics.example.com/api/truth - Network accessline 536
curl -X POST https://metrics.example.com/api/truth \
bundled/skills/video-studio/SKILL.md
bundled/skills/video-studio/scripts/video_studio.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 91
[Credential-related source omitted] - Network accessline 94
if vectcut_base_url: try: req = urllib.request.Request(vectcut_base_url, method="GET") - Network accessline 95
try: req = urllib.request.Request(vectcut_base_url, method="GET") with urllib.request.urlopen(req, timeout=2.0) as resp: - Network accessline 96
req = urllib.request.Request(vectcut_base_url, method="GET") - Network accessline 97
with urllib.request.urlopen(req, timeout=2.0) as resp: - Network accessline 192
# FFmpeg drawtext escaping rules are finicky; this is a conservative subset. # See: https://ffmpeg.org/ffmpeg-filters.html#drawtext-1 - Network accessline 193
# See: https://ffmpeg.org/ffmpeg-filters.html#drawtext-1
bundled/skills/visualization-best-practices/SKILL.md
- Broad permissionsline 1
Read, Write, Edit, Bash, Grep
bundled/skills/vscode-release-notes-writer/examples/v1_109.md
- Network accessline 17
These release notes cover the Insiders build of VS Code and continue to evolve as new features are added. To try the latest updates, [download Insiders](https://code.visualstudio.com/insiders). - Network accessline 18
To read these release notes online, go to [code.visualstudio.com/updates](https://code.visualstudio.com/updates). - Network accessline 20
You can still track our progress in the [Commit log](https://github.com/Microsoft/vscode/commits/main) and our list of [Closed issues](https://github.com/Microsoft/vscode/issues?q=is%3Aissue+is%3Aclosed+milestone%3A%22January+2026%22). - Network accessline 43
* The terminal tool now supports a `timeout` parameter to control how long terminal commands run before timing out, preventing unnecessary polling commands. [#286598](https://github.com/microsoft/vscode/issues/286598) - Network accessline 45
* Updated the list of npm commands that are safe for automatic execution. [#286463](https://github.com/microsoft/vscode/issues/286463) - Network accessline 47
* The terminal suggest toolbar no longer shows the selection mode option when quick suggestions are disabled, reducing confusion. [#286440](https://github.com/microsoft/vscode/issues/286440) - Network accessline 49
* The `terminal.integrated.suggest.quickSuggestions` setting can now be configured in the Settings editor instead of requiring manual JSON editing. [#286075](https://github.com/microsoft/vscode/issues/286075) - Network accessline 51
* Added a `workbench.mcp.startServer` command to start a specific or all MCP servers to discover their tools. [#283959](https://github.com/microsoft/vscode/issues/283959) - Network accessline 53
* Exploration work on rich integrated web browser using WebContentsView or controlledframe to overcome limitations of the current iframe-based Simple Browser. [#277298](https://github.com/microsoft/vscode/issues/277298) - Network accessline 55
* A new proposed API enables extensions to show buttons inline after the input box in quick inputs, in addition to the title bar location. [#221397](https://github.com/microsoft/vscode/issues/221397) - Network accessline 59
* You can now import a chat session into the Chat view instead of only opening it in a new editor tab. [#283954](https://github.com/microsoft/vscode/issues/283954) - Network accessline 61
* Fixed an issue where auto approval information for the fetch tool was not visible when hovering over the tool call. [#282238](https://github.com/microsoft/vscode/issues/282238) - Network accessline 63
* Added built-in support for MCP Apps, enabling servers to provide custom UI for tool invocation. [#260218](https://github.com/microsoft/vscode/issues/260218) - Network accessline 67
* The quick input now supports overflow buttons, enabling secondary actions to be placed in an overflow menu. [#285213](https://github.com/microsoft/vscode/issues/285213)
bundled/skills/vscode-release-notes-writer/images/vscode-insiders-banner-medium.png
- Network accessline 1
version https://git-lfs.github.com/spec/v1
bundled/skills/vscode-release-notes-writer/template-release-note-endgame.md
- Network accessline 32
>If you'd like to read these release notes online, go to [Updates](https://code.visualstudio.com/updates) on [code.visualstudio.com](https://code.visualstudio.com).<br> - Network accessline 34
> **Insiders: Want to try new features as soon as possible?**<br> > You can download the nightly Insiders build and try the latest updates as soon as they are available.<br> > [Download Insiders](https://code.visualstudio.com/insiders)<br> - Network accessline 36
> [Download Insiders](https://code.visualstudio.com/insiders)<br> - Network accessline 109
The [Remote Development extensions](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack), allow you to use a [Dev Container](https://code.visualstudio.com/docs/devcontainers/containers), remote m - Network accessline 115
You can learn more about these features in the [Remote Development release notes](https://github.com/microsoft/vscode-docs/blob/main/remote-release-notes/v1_<release number>.md). - Network accessline 140
>If you'd like to read release notes for previous VS Code versions, go to [Updates](https://code.visualstudio.com/updates) on [code.visualstudio.com](https://code.visualstudio.com).
bundled/skills/vscode-release-notes-writer/template-release-note-insiders.md
- Network accessline 17
These release notes cover the Insiders build of VS Code and continue to evolve as new features are added. To try the latest updates, [download Insiders](https://code.visualstudio.com/insiders). - Network accessline 18
To read these release notes online, go to [code.visualstudio.com/updates](https://code.visualstudio.com/updates). - Network accessline 20
You can still track our progress in the [Commit log](https://github.com/Microsoft/vscode/commits/main) and our list of [Closed issues](https://github.com/Microsoft/vscode/issues?q=is%3Aissue+is%3Aclosed+milestone%3A%22<Month>+<Year>%22). - Network accessline 41
* Feature description with link to issue. _[#issue-number](https://github.com/microsoft/vscode/issues/issue-number)_
bundled/skills/webthinker-deep-research/SKILL.md
- Access to secretsline 49
[Credential-related source omitted]
bundled/skills/webthinker-deep-research/scripts/init_webthinker_run.py
- Executable scriptline 1
#!/usr/bin/env python3
bundled/skills/weights-and-biases/SKILL.md
- Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 543
[Credential-related source omitted] - Network accessline 578
- **Documentation**: https://docs.wandb.ai - Network accessline 579
- **GitHub**: https://github.com/wandb/wandb (10.5k+ stars) - Network accessline 580
- **Examples**: https://github.com/wandb/examples - Network accessline 581
- **Community**: https://wandb.ai/community - Network accessline 582
- **Discord**: https://wandb.me/discord
bundled/skills/weights-and-biases/references/artifacts.md
- Network accessline 433
# HTTP reference dataset.add_reference('https://example.com/data.zip') - Network accessline 434
dataset.add_reference('https://example.com/data.zip') - Network accessline 582
- **Artifacts Documentation**: https://docs.wandb.ai/guides/artifacts - Network accessline 583
- **Model Registry**: https://docs.wandb.ai/guides/model-registry - Network accessline 584
- **Best Practices**: https://wandb.ai/site/articles/versioning-data-and-models-in-ml
bundled/skills/weights-and-biases/references/integrations.md
- Network accessline 696
- **Integrations Guide**: https://docs.wandb.ai/guides/integrations - Network accessline 697
- **HuggingFace**: https://docs.wandb.ai/guides/integrations/huggingface - Network accessline 698
- **PyTorch Lightning**: https://docs.wandb.ai/guides/integrations/lightning - Network accessline 699
- **Keras**: https://docs.wandb.ai/guides/integrations/keras - Network accessline 700
- **Examples**: https://github.com/wandb/examples
bundled/skills/weights-and-biases/references/sweeps.md
- Access to secretsline 538
[Credential-related source omitted] - Network accessline 845
- **Sweeps Documentation**: https://docs.wandb.ai/guides/sweeps - Network accessline 846
- **Configuration Reference**: https://docs.wandb.ai/guides/sweeps/configuration - Network accessline 847
- **Examples**: https://github.com/wandb/examples/tree/master/examples/wandb-sweeps
bundled/skills/xan/scripts/xan.ps1
- Executable scriptline 1
Executable file
bundled/skills/xlsx/LICENSE.txt
- Network accessline 6
exists, use is governed by Anthropic's Consumer Terms of Service or Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms - Network accessline 7
Commercial Terms of Service, as applicable: https://www.anthropic.com/legal/consumer-terms https://www.anthropic.com/legal/commercial-terms - Network accessline 8
https://www.anthropic.com/legal/consumer-terms - Network accessline 9
https://www.anthropic.com/legal/commercial-terms
bundled/skills/xlsx/recalc.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 35
macro_content = '''<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE script:module PUBLIC "-//OpenOffice.org//DTD OfficeDocument 1.0//EN" "module.dtd"> <script:module xmlns:script="http://openoffice.org/2000/script" script:name="Module1" scr - Network accessline 36
<!DOCTYPE script:module PUBLIC "-//OpenOffice.org//DTD OfficeDocument 1.0//EN" "module.dtd"> <script:module xmlns:script="http://openoffice.org/2000/script" script:name="Module1" script:language="StarBasic"> Sub RecalculateAndSave() - Network accessline 37
<script:module xmlns:script="http://openoffice.org/2000/script" script:name="Module1" script:language="StarBasic">
bundled/skills/yeet/LICENSE.txt
bundled/skills/yeet/assets/yeet-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
bundled/skills/zarr-python/SKILL.md
- Network accessline 768
- **Official Documentation**: https://zarr.readthedocs.io/ - Network accessline 769
- **Zarr Specifications**: https://zarr-specs.readthedocs.io/ - Network accessline 770
- **GitHub Repository**: https://github.com/zarr-developers/zarr-python - Network accessline 771
- **Community Chat**: https://gitter.im/zarr-developers/community - Network accessline 773
**Related Libraries**: - **Xarray**: https://docs.xarray.dev/ (labeled arrays) - Network accessline 774
- **Xarray**: https://docs.xarray.dev/ (labeled arrays) - Network accessline 775
- **Dask**: https://docs.dask.org/ (parallel computing) - Network accessline 776
- **NumCodecs**: https://numcodecs.readthedocs.io/ (compression codecs)
check.ps1
- Executable scriptline 1
Executable file
check.sh
- Executable scriptline 1
#!/usr/bin/env bash
config/benchmark-results.json
- Network accessline 3
"study_id": "full-skills-comparison", "publication": { "repository": "https://github.com/foryourhealth111-pixel/vibeskills-benchmark", - Network accessline 4
"publication": { "repository": "https://github.com/foryourhealth111-pixel/vibeskills-benchmark", "commit": "ef907ebf8370807794371ba445dd22611a00d92e", - Network accessline 5
"repository": "https://github.com/foryourhealth111-pixel/vibeskills-benchmark",
config/connector-provider-policy.json
config/gitnexus-overlays.json
- Network accessline 73
"调用" ], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 74
], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] }, - Network accessline 75
"upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 105
"回归" ], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 106
], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] }, - Network accessline 107
"upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 133
"联动" ], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 134
], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] }, - Network accessline 135
"upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 163
"对齐" ], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] - Network accessline 164
], "upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"] } - Network accessline 165
"upstream_refs": ["https://github.com/abhigyanpatwari/GitNexus"]
config/llm-acceleration-policy.json
config/opencode/opencode.json.example
config/prompt-asset-boost.json
- Network accessline 30
"type": "mock", "model": "your-model-id", "base_url": "https://your-openai-compatible-endpoint/v1", - Network accessline 31
"model": "your-model-id", "base_url": "https://your-openai-compatible-endpoint/v1", "mock_response_path": "scripts/verify/fixtures/prompt-asset-boost.mock.json", - Network accessline 32
"base_url": "https://your-openai-compatible-endpoint/v1",
config/router-provider-registry.json
config/ruc-nlpir-overlays.json
- Network accessline 42
"出处" ], "upstream_refs": ["https://github.com/RUC-NLPIR/FlashRAG"] - Network accessline 43
], "upstream_refs": ["https://github.com/RUC-NLPIR/FlashRAG"] }, - Network accessline 44
"upstream_refs": ["https://github.com/RUC-NLPIR/FlashRAG"] - Network accessline 66
"可审计调研" ], "upstream_refs": ["https://github.com/RUC-NLPIR/WebThinker"] - Network accessline 67
], "upstream_refs": ["https://github.com/RUC-NLPIR/WebThinker"] } - Network accessline 68
"upstream_refs": ["https://github.com/RUC-NLPIR/WebThinker"]
config/ruc-nlpir-runtime.json
- Network accessline 5
"repos": { "FlashRAG": { "upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", - Network accessline 6
"FlashRAG": { "upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", "path": "${VCO_EXTERNAL_ROOT}/ruc-nlpir/FlashRAG", - Network accessline 7
"upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", - Network accessline 12
}, "WebThinker": { "upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", - Network accessline 13
"WebThinker": { "upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", "path": "${VCO_EXTERNAL_ROOT}/ruc-nlpir/WebThinker", - Network accessline 14
"upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", - Network accessline 25
}, "llm": { "base_url_default": "https://your-openai-compatible-endpoint/v1", - Network accessline 26
"llm": { "base_url_default": "https://your-openai-compatible-endpoint/v1", "model_default": "your-model-id", - Network accessline 27
"base_url_default": "https://your-openai-compatible-endpoint/v1", - Access to secretsline 29
[Credential-related source omitted] - Access to secretsline 36
[Credential-related source omitted] - Access to secretsline 38
[Credential-related source omitted]
config/secrets-policy.json
- Access to secretsline 24
[Credential-related source omitted]
config/settings.template.claude.json
- Access to secretsline 3
[Credential-related source omitted]
config/tool-registry.json
- Access to secretsline 99
[Credential-related source omitted]
config/turix-cua-overlays.json
- Network accessline 65
"录屏" ], "upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"] - Network accessline 66
], "upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"] }, - Network accessline 67
"upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"] - Network accessline 98
"recording" ], "upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"] - Network accessline 99
], "upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"] } - Network accessline 100
"upstream_refs": ["https://github.com/TurixAI/TuriX-CUA"]
config/upstream-corpus-manifest.json
- Network accessline 120
{ "slug": "activepieces", "repo_url": "https://github.com/activepieces/activepieces", - Network accessline 121
"slug": "activepieces", "repo_url": "https://github.com/activepieces/activepieces", "default_branch": "main", - Network accessline 122
"repo_url": "https://github.com/activepieces/activepieces", - Network accessline 138
{ "slug": "agent-s", "repo_url": "https://github.com/simular-ai/Agent-S", - Network accessline 139
"slug": "agent-s", "repo_url": "https://github.com/simular-ai/Agent-S", "default_branch": "main", - Network accessline 140
"repo_url": "https://github.com/simular-ai/Agent-S", - Network accessline 155
{ "slug": "agent-squad", "repo_url": "https://github.com/awslabs/agent-squad", - Network accessline 156
"slug": "agent-squad", "repo_url": "https://github.com/awslabs/agent-squad", "default_branch": "main", - Network accessline 157
"repo_url": "https://github.com/awslabs/agent-squad", - Network accessline 177
{ "slug": "antigravity-awesome-skills", "repo_url": "https://github.com/sickn33/antigravity-awesome-skills", - Network accessline 178
"slug": "antigravity-awesome-skills", "repo_url": "https://github.com/sickn33/antigravity-awesome-skills", "default_branch": "main", - Network accessline 179
"repo_url": "https://github.com/sickn33/antigravity-awesome-skills", - Network accessline 198
{ "slug": "awesome-agent-skills", "repo_url": "https://github.com/VoltAgent/awesome-agent-skills", - Network accessline 199
"slug": "awesome-agent-skills", "repo_url": "https://github.com/VoltAgent/awesome-agent-skills", "default_branch": "main", - Network accessline 200
"repo_url": "https://github.com/VoltAgent/awesome-agent-skills", - Network accessline 219
{ "slug": "awesome-ai-agents-e2b", "repo_url": "https://github.com/e2b-dev/awesome-ai-agents", - Network accessline 220
"slug": "awesome-ai-agents-e2b", "repo_url": "https://github.com/e2b-dev/awesome-ai-agents", "default_branch": "main", - Network accessline 221
"repo_url": "https://github.com/e2b-dev/awesome-ai-agents", - Network accessline 241
{ "slug": "awesome-ai-tools", "repo_url": "https://github.com/mahseema/awesome-ai-tools", - Network accessline 242
"slug": "awesome-ai-tools", "repo_url": "https://github.com/mahseema/awesome-ai-tools", "default_branch": "main", - Network accessline 243
"repo_url": "https://github.com/mahseema/awesome-ai-tools", - Network accessline 263
{ "slug": "awesome-claude-code-subagents", "repo_url": "https://github.com/VoltAgent/awesome-claude-code-subagents", - Network accessline 264
"slug": "awesome-claude-code-subagents", "repo_url": "https://github.com/VoltAgent/awesome-claude-code-subagents", "default_branch": "main", - Network accessline 265
"repo_url": "https://github.com/VoltAgent/awesome-claude-code-subagents", - Network accessline 284
{ "slug": "awesome-claude-skills-composio", "repo_url": "https://github.com/ComposioHQ/awesome-claude-skills", - Network accessline 285
"slug": "awesome-claude-skills-composio", "repo_url": "https://github.com/ComposioHQ/awesome-claude-skills", "default_branch": "master", - Network accessline 286
"repo_url": "https://github.com/ComposioHQ/awesome-claude-skills", - Network accessline 305
{ "slug": "awesome-mcp-servers", "repo_url": "https://github.com/punkpeye/awesome-mcp-servers", - Network accessline 306
"slug": "awesome-mcp-servers", "repo_url": "https://github.com/punkpeye/awesome-mcp-servers", "default_branch": "main", - Network accessline 307
"repo_url": "https://github.com/punkpeye/awesome-mcp-servers", - Network accessline 322
{ "slug": "awesome-vibe-coding", "repo_url": "https://github.com/filipecalegario/awesome-vibe-coding", - Network accessline 323
"slug": "awesome-vibe-coding", "repo_url": "https://github.com/filipecalegario/awesome-vibe-coding", "default_branch": "main", - Network accessline 324
"repo_url": "https://github.com/filipecalegario/awesome-vibe-coding", - Network accessline 343
{ "slug": "browser-use", "repo_url": "https://github.com/browser-use/browser-use", - Network accessline 344
"slug": "browser-use", "repo_url": "https://github.com/browser-use/browser-use", "default_branch": "main", - Network accessline 345
"repo_url": "https://github.com/browser-use/browser-use", - Network accessline 363
{ "slug": "claude-skills", "repo_url": "https://github.com/Jeffallan/claude-skills", - Network accessline 364
"slug": "claude-skills", "repo_url": "https://github.com/Jeffallan/claude-skills", "default_branch": "main", - Network accessline 365
"repo_url": "https://github.com/Jeffallan/claude-skills", - Network accessline 384
{ "slug": "composio", "repo_url": "https://github.com/ComposioHQ/composio", - Network accessline 385
"slug": "composio", "repo_url": "https://github.com/ComposioHQ/composio", "default_branch": "next", - Network accessline 386
"repo_url": "https://github.com/ComposioHQ/composio", - Network accessline 401
{ "slug": "docling", "repo_url": "https://github.com/docling-project/docling", - Network accessline 402
"slug": "docling", "repo_url": "https://github.com/docling-project/docling", "default_branch": "main", - Network accessline 403
"repo_url": "https://github.com/docling-project/docling", - Network accessline 418
{ "slug": "letta", "repo_url": "https://github.com/letta-ai/letta", - Network accessline 419
"slug": "letta", "repo_url": "https://github.com/letta-ai/letta", "default_branch": "main", - Network accessline 420
"repo_url": "https://github.com/letta-ai/letta", - Network accessline 435
{ "slug": "mem0", "repo_url": "https://github.com/mem0ai/mem0", - Network accessline 436
"slug": "mem0", "repo_url": "https://github.com/mem0ai/mem0", "default_branch": "main", - Network accessline 437
"repo_url": "https://github.com/mem0ai/mem0", - Network accessline 454
{ "slug": "prompt-engineering-guide", "repo_url": "https://github.com/dair-ai/Prompt-Engineering-Guide", - Network accessline 455
"slug": "prompt-engineering-guide", "repo_url": "https://github.com/dair-ai/Prompt-Engineering-Guide", "default_branch": "main", - Network accessline 456
"repo_url": "https://github.com/dair-ai/Prompt-Engineering-Guide", - Network accessline 471
{ "slug": "vibe-coding-cn", "repo_url": "https://github.com/tukuaiai/vibe-coding-cn", - Network accessline 472
"slug": "vibe-coding-cn", "repo_url": "https://github.com/tukuaiai/vibe-coding-cn", "default_branch": "develop", - Network accessline 473
"repo_url": "https://github.com/tukuaiai/vibe-coding-cn",
config/upstream-lock.json
- Network accessline 5
{ "id": "obra/superpowers", "upstream_repo": "https://github.com/obra/superpowers", - Network accessline 6
"id": "obra/superpowers", "upstream_repo": "https://github.com/obra/superpowers", "upstream_ref": "main", - Network accessline 7
"upstream_repo": "https://github.com/obra/superpowers", - Network accessline 25
{ "id": "frankbria/ralph-claude-code", "upstream_repo": "https://github.com/frankbria/ralph-claude-code", - Network accessline 26
"id": "frankbria/ralph-claude-code", "upstream_repo": "https://github.com/frankbria/ralph-claude-code", "upstream_ref": "main", - Network accessline 27
"upstream_repo": "https://github.com/frankbria/ralph-claude-code", - Network accessline 45
{ "id": "f/prompts.chat", "upstream_repo": "https://github.com/f/prompts.chat", - Network accessline 46
"id": "f/prompts.chat", "upstream_repo": "https://github.com/f/prompts.chat", "upstream_ref": "main", - Network accessline 47
"upstream_repo": "https://github.com/f/prompts.chat", - Network accessline 60
{ "id": "SuperClaude-Org/SuperClaude_Framework", "upstream_repo": "https://github.com/SuperClaude-Org/SuperClaude_Framework", - Network accessline 61
"id": "SuperClaude-Org/SuperClaude_Framework", "upstream_repo": "https://github.com/SuperClaude-Org/SuperClaude_Framework", "upstream_ref": "master", - Network accessline 62
"upstream_repo": "https://github.com/SuperClaude-Org/SuperClaude_Framework", - Network accessline 75
{ "id": "feiskyer/claude-code-settings", "upstream_repo": "https://github.com/feiskyer/claude-code-settings", - Network accessline 76
"id": "feiskyer/claude-code-settings", "upstream_repo": "https://github.com/feiskyer/claude-code-settings", "upstream_ref": "main", - Network accessline 77
"upstream_repo": "https://github.com/feiskyer/claude-code-settings", - Network accessline 95
{ "id": "github/spec-kit", "upstream_repo": "https://github.com/github/spec-kit", - Network accessline 96
"id": "github/spec-kit", "upstream_repo": "https://github.com/github/spec-kit", "upstream_ref": "main", - Network accessline 97
"upstream_repo": "https://github.com/github/spec-kit", - Network accessline 115
{ "id": "medialab/xan", "upstream_repo": "https://github.com/medialab/xan", - Network accessline 116
"id": "medialab/xan", "upstream_repo": "https://github.com/medialab/xan", "upstream_ref": "master", - Network accessline 117
"upstream_repo": "https://github.com/medialab/xan", - Network accessline 130
{ "id": "Done-0/fuck-u-code", "upstream_repo": "https://github.com/Done-0/fuck-u-code", - Network accessline 131
"id": "Done-0/fuck-u-code", "upstream_repo": "https://github.com/Done-0/fuck-u-code", "upstream_ref": "main", - Network accessline 132
"upstream_repo": "https://github.com/Done-0/fuck-u-code", - Network accessline 145
{ "id": "ivy-llc/ivy", "upstream_repo": "https://github.com/ivy-llc/ivy", - Network accessline 146
"id": "ivy-llc/ivy", "upstream_repo": "https://github.com/ivy-llc/ivy", "upstream_ref": "main", - Network accessline 147
"upstream_repo": "https://github.com/ivy-llc/ivy", - Network accessline 160
{ "id": "GokuMohandas/Made-With-ML", "upstream_repo": "https://github.com/GokuMohandas/Made-With-ML", - Network accessline 161
"id": "GokuMohandas/Made-With-ML", "upstream_repo": "https://github.com/GokuMohandas/Made-With-ML", "upstream_ref": "main", - Network accessline 162
"upstream_repo": "https://github.com/GokuMohandas/Made-With-ML", - Network accessline 175
{ "id": "zedr/clean-code-python", "upstream_repo": "https://github.com/zedr/clean-code-python", - Network accessline 176
"id": "zedr/clean-code-python", "upstream_repo": "https://github.com/zedr/clean-code-python", "upstream_ref": "master", - Network accessline 177
"upstream_repo": "https://github.com/zedr/clean-code-python", - Network accessline 190
{ "id": "donnemartin/system-design-primer", "upstream_repo": "https://github.com/donnemartin/system-design-primer", - Network accessline 191
"id": "donnemartin/system-design-primer", "upstream_repo": "https://github.com/donnemartin/system-design-primer", "upstream_ref": "master", - Network accessline 192
"upstream_repo": "https://github.com/donnemartin/system-design-primer", - Network accessline 205
{ "id": "xlite-dev/LeetCUDA", "upstream_repo": "https://github.com/xlite-dev/LeetCUDA", - Network accessline 206
"id": "xlite-dev/LeetCUDA", "upstream_repo": "https://github.com/xlite-dev/LeetCUDA", "upstream_ref": "master", - Network accessline 207
"upstream_repo": "https://github.com/xlite-dev/LeetCUDA", - Network accessline 220
{ "id": "RUC-NLPIR/FlashRAG", "upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", - Network accessline 221
"id": "RUC-NLPIR/FlashRAG", "upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", "upstream_ref": "6aca76d1325c0eed9e00fba6ec692bf8b8a52b39", - Network accessline 222
"upstream_repo": "https://github.com/RUC-NLPIR/FlashRAG", - Network accessline 238
{ "id": "RUC-NLPIR/WebThinker", "upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", - Network accessline 239
"id": "RUC-NLPIR/WebThinker", "upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", "upstream_ref": "db387eb3261de9b5e2db7d2d7fb20af2aceb7882", - Network accessline 240
"upstream_repo": "https://github.com/RUC-NLPIR/WebThinker", - Network accessline 256
{ "id": "mem0ai/mem0", "upstream_repo": "https://github.com/mem0ai/mem0", - Network accessline 257
"id": "mem0ai/mem0", "upstream_repo": "https://github.com/mem0ai/mem0", "upstream_ref": "main", - Network accessline 258
"upstream_repo": "https://github.com/mem0ai/mem0", - Network accessline 271
{ "id": "letta-ai/letta", "upstream_repo": "https://github.com/letta-ai/letta", - Network accessline 272
"id": "letta-ai/letta", "upstream_repo": "https://github.com/letta-ai/letta", "upstream_ref": "main", - Network accessline 273
"upstream_repo": "https://github.com/letta-ai/letta", - Network accessline 286
{ "id": "dair-ai/Prompt-Engineering-Guide", "upstream_repo": "https://github.com/dair-ai/Prompt-Engineering-Guide", - Network accessline 287
"id": "dair-ai/Prompt-Engineering-Guide", "upstream_repo": "https://github.com/dair-ai/Prompt-Engineering-Guide", "upstream_ref": "main", - Network accessline 288
"upstream_repo": "https://github.com/dair-ai/Prompt-Engineering-Guide", - Network accessline 301
{ "id": "browser-use/browser-use", "upstream_repo": "https://github.com/browser-use/browser-use", - Network accessline 302
"id": "browser-use/browser-use", "upstream_repo": "https://github.com/browser-use/browser-use", "upstream_ref": "main", - Network accessline 303
"upstream_repo": "https://github.com/browser-use/browser-use", - Network accessline 316
{ "id": "simular-ai/Agent-S", "upstream_repo": "https://github.com/simular-ai/Agent-S", - Network accessline 317
"id": "simular-ai/Agent-S", "upstream_repo": "https://github.com/simular-ai/Agent-S", "upstream_ref": "main", - Network accessline 318
"upstream_repo": "https://github.com/simular-ai/Agent-S", - Network accessline 331
{ "id": "x1xhlol/system-prompts-and-models-of-ai-tools", "upstream_repo": "https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools", - Network accessline 332
"id": "x1xhlol/system-prompts-and-models-of-ai-tools", "upstream_repo": "https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools", "upstream_ref": "main", - Network accessline 333
"upstream_repo": "https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools", - Network accessline 346
{ "id": "muratcankoylan/Agent-Skills-for-Context-Engineering", "upstream_repo": "https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering", - Network accessline 347
"id": "muratcankoylan/Agent-Skills-for-Context-Engineering", "upstream_repo": "https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering", "upstream_ref": "main", - Network accessline 348
"upstream_repo": "https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering", - Network accessline 361
{ "id": "awslabs/agent-squad", "upstream_repo": "https://github.com/awslabs/agent-squad", - Network accessline 362
"id": "awslabs/agent-squad", "upstream_repo": "https://github.com/awslabs/agent-squad", "upstream_ref": "main", - Network accessline 363
"upstream_repo": "https://github.com/awslabs/agent-squad", - Network accessline 382
{ "id": "sickn33/antigravity-awesome-skills", "upstream_repo": "https://github.com/sickn33/antigravity-awesome-skills", - Network accessline 383
"id": "sickn33/antigravity-awesome-skills", "upstream_repo": "https://github.com/sickn33/antigravity-awesome-skills", "upstream_ref": "main", - Network accessline 384
"upstream_repo": "https://github.com/sickn33/antigravity-awesome-skills", - Network accessline 403
{ "id": "VoltAgent/awesome-agent-skills", "upstream_repo": "https://github.com/VoltAgent/awesome-agent-skills", - Network accessline 404
"id": "VoltAgent/awesome-agent-skills", "upstream_repo": "https://github.com/VoltAgent/awesome-agent-skills", "upstream_ref": "main", - Network accessline 405
"upstream_repo": "https://github.com/VoltAgent/awesome-agent-skills", - Network accessline 424
{ "id": "VoltAgent/awesome-claude-code-subagents", "upstream_repo": "https://github.com/VoltAgent/awesome-claude-code-subagents", - Network accessline 425
"id": "VoltAgent/awesome-claude-code-subagents", "upstream_repo": "https://github.com/VoltAgent/awesome-claude-code-subagents", "upstream_ref": "main", - Network accessline 426
"upstream_repo": "https://github.com/VoltAgent/awesome-claude-code-subagents", - Network accessline 445
{ "id": "ComposioHQ/awesome-claude-skills", "upstream_repo": "https://github.com/ComposioHQ/awesome-claude-skills", - Network accessline 446
"id": "ComposioHQ/awesome-claude-skills", "upstream_repo": "https://github.com/ComposioHQ/awesome-claude-skills", "upstream_ref": "master", - Network accessline 447
"upstream_repo": "https://github.com/ComposioHQ/awesome-claude-skills", - Network accessline 466
{ "id": "Jeffallan/claude-skills", "upstream_repo": "https://github.com/Jeffallan/claude-skills", - Network accessline 467
"id": "Jeffallan/claude-skills", "upstream_repo": "https://github.com/Jeffallan/claude-skills", "upstream_ref": "main", - Network accessline 468
"upstream_repo": "https://github.com/Jeffallan/claude-skills", - Network accessline 487
{ "id": "e2b-dev/awesome-ai-agents", "upstream_repo": "https://github.com/e2b-dev/awesome-ai-agents", - Network accessline 488
"id": "e2b-dev/awesome-ai-agents", "upstream_repo": "https://github.com/e2b-dev/awesome-ai-agents", "upstream_ref": "main", - Network accessline 489
"upstream_repo": "https://github.com/e2b-dev/awesome-ai-agents", - Network accessline 508
{ "id": "mahseema/awesome-ai-tools", "upstream_repo": "https://github.com/mahseema/awesome-ai-tools", - Network accessline 509
"id": "mahseema/awesome-ai-tools", "upstream_repo": "https://github.com/mahseema/awesome-ai-tools", "upstream_ref": "main", - Network accessline 510
"upstream_repo": "https://github.com/mahseema/awesome-ai-tools", - Network accessline 529
{ "id": "filipecalegario/awesome-vibe-coding", "upstream_repo": "https://github.com/filipecalegario/awesome-vibe-coding", - Network accessline 530
"id": "filipecalegario/awesome-vibe-coding", "upstream_repo": "https://github.com/filipecalegario/awesome-vibe-coding", "upstream_ref": "main", - Network accessline 531
"upstream_repo": "https://github.com/filipecalegario/awesome-vibe-coding", - Network accessline 550
{ "id": "tukuaiai/vibe-coding-cn", "upstream_repo": "https://github.com/tukuaiai/vibe-coding-cn", - Network accessline 551
"id": "tukuaiai/vibe-coding-cn", "upstream_repo": "https://github.com/tukuaiai/vibe-coding-cn", "upstream_ref": "develop", - Network accessline 552
"upstream_repo": "https://github.com/tukuaiai/vibe-coding-cn",
config/version-governance.json
- Network accessline 10
"canonical_root": ".", "official_self_repo": { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 11
"official_self_repo": { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main" - Network accessline 12
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git",
docs/README.md
docs/assets/install-cta-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 300 54" role="img" aria-labelledby="title desc">
docs/assets/install-cta-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 300 54" role="img" aria-labelledby="title desc">
docs/assets/install-cta-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 300 54" role="img" aria-labelledby="title desc">
docs/assets/install-cta-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 300 54" role="img" aria-labelledby="title desc">
docs/assets/readme-chapter-01-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-01-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-01-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-01-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-02-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-02-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-02-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-02-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-03-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-03-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-03-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-03-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-04-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-04-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-04-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-04-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-05-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-05-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-05-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-chapter-05-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 140" role="img" aria-labelledby="title">
docs/assets/readme-preface-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 600" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 600" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-cn-mobile-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 960" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-cn-mobile-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 960" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 660" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 660" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-en-mobile-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 360 920" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-en-mobile-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 360 920" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 600" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 600" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-cn-mobile-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 960" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-cn-mobile-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 960" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 660" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 660" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-en-mobile-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 360 920" role="img" aria-labelledby="title desc">
docs/assets/readme-preface-v2-en-mobile-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 360 920" role="img" aria-labelledby="title desc">
docs/assets/readme-tagline-cn-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 94" role="img" aria-labelledby="title">
docs/assets/readme-tagline-cn-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 94" role="img" aria-labelledby="title">
docs/assets/readme-tagline-en-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 94" role="img" aria-labelledby="title">
docs/assets/readme-tagline-en-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 94" role="img" aria-labelledby="title">
docs/assets/readme-wave-divider-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 720 32" role="img" aria-label="">
docs/assets/readme-wave-divider-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 720 32" role="img" aria-label="">
docs/assets/readme-wordmark-dark.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 132" role="img" aria-labelledby="title">
docs/assets/readme-wordmark-light.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 960 132" role="img" aria-labelledby="title">
docs/assets/vibeskills-harness-overview-cn.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="520" viewBox="0 0 1200 520" role="img" aria-labelledby="title desc">
docs/assets/vibeskills-harness-overview-en.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="520" viewBox="0 0 1200 520" role="img" aria-labelledby="title desc">
docs/cases/ml-experiment/assets/vector/class-balance.svg
- Network accessline 1
<?xml version="1.0" encoding="utf-8" standalone="no"?> <!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 2
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> <svg xmlns:xlink="http://www.w3.org/1999/xlink" width="450.256992pt" height="290.310433pt" viewBox="0 0 450.256992 290.310433" xmlns="http: - Network accessline 3
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 4
<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="450.256992pt" height="290.310433pt" viewBox="0 0 450.256992 290.310433" xmlns="http://www.w3.org/2000/svg" version="1.1"> - Network accessline 5
<metadata> <rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <cc:Work> - Network accessline 6
<rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> - Network accessline 7
<cc:Work> <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> <dc:date>2026-07-18T12:36:18.264482</dc:date> - Network accessline 8
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> - Network accessline 11
<dc:creator> <cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> - Network accessline 12
<cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> </cc:Agent> - Network accessline 13
<dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title>
docs/cases/ml-experiment/assets/vector/confusion-matrix.svg
- Network accessline 1
<?xml version="1.0" encoding="utf-8" standalone="no"?> <!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 2
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> <svg xmlns:xlink="http://www.w3.org/1999/xlink" width="748.03721pt" height="331.576687pt" viewBox="0 0 748.03721 331.576687" xmlns="http:// - Network accessline 3
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 4
<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="748.03721pt" height="331.576687pt" viewBox="0 0 748.03721 331.576687" xmlns="http://www.w3.org/2000/svg" version="1.1"> - Network accessline 5
<metadata> <rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <cc:Work> - Network accessline 6
<rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> - Network accessline 7
<cc:Work> <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> <dc:date>2026-07-18T12:36:19.760748</dc:date> - Network accessline 8
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> - Network accessline 11
<dc:creator> <cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> - Network accessline 12
<cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> </cc:Agent> - Network accessline 13
<dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title>
docs/cases/ml-experiment/assets/vector/cv-performance-distribution.svg
- Network accessline 1
<?xml version="1.0" encoding="utf-8" standalone="no"?> <!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 2
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> <svg xmlns:xlink="http://www.w3.org/1999/xlink" width="809.967773pt" height="306.952492pt" viewBox="0 0 809.967773 306.952492" xmlns="http: - Network accessline 3
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 4
<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="809.967773pt" height="306.952492pt" viewBox="0 0 809.967773 306.952492" xmlns="http://www.w3.org/2000/svg" version="1.1"> - Network accessline 5
<metadata> <rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <cc:Work> - Network accessline 6
<rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> - Network accessline 7
<cc:Work> <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> <dc:date>2026-07-18T12:36:19.141906</dc:date> - Network accessline 8
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> - Network accessline 11
<dc:creator> <cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> - Network accessline 12
<cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> </cc:Agent> - Network accessline 13
<dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title>
docs/cases/ml-experiment/assets/vector/roc-and-pr-curves.svg
- Network accessline 1
<?xml version="1.0" encoding="utf-8" standalone="no"?> <!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 2
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> <svg xmlns:xlink="http://www.w3.org/1999/xlink" width="601.546676pt" height="320.920492pt" viewBox="0 0 601.546676 320.920492" xmlns="http: - Network accessline 3
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"> - Network accessline 4
<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="601.546676pt" height="320.920492pt" viewBox="0 0 601.546676 320.920492" xmlns="http://www.w3.org/2000/svg" version="1.1"> - Network accessline 5
<metadata> <rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <cc:Work> - Network accessline 6
<rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> - Network accessline 7
<cc:Work> <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> <dc:date>2026-07-18T12:36:18.682783</dc:date> - Network accessline 8
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/> - Network accessline 11
<dc:creator> <cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> - Network accessline 12
<cc:Agent> <dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title> </cc:Agent> - Network accessline 13
<dc:title>Matplotlib v3.11.1, https://matplotlib.org/</dc:title>
docs/cases/ml-experiment/reproduce/compute_uncertainty.py
- Executable scriptline 1
Executable file
docs/cases/ml-experiment/reproduce/create_data_audit.py
- Executable scriptline 1
Executable file
docs/cases/ml-experiment/reproduce/make_figures.py
- Executable scriptline 1
Executable file
docs/cases/ml-experiment/reproduce/reproduce.ps1
- Executable scriptline 1
Executable file
docs/cases/ml-experiment/reproduce/run_experiment.py
- Executable scriptline 1
Executable file
docs/install/README.en.md
- Network accessline 3
The public install path starts from a published release zip. Download the asset ending in `-public.zip` from the [latest stable release](https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest), extract it outside the managed
docs/install/README.md
- Network accessline 3
公开安装使用发布版本 zip。请从[最新稳定版 Release](https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest) 下载名称以 `-public.zip` 结尾的安装包，解压到受管 Skills 目录之外，然后从解压目录运行脚本。
install.ps1
- Executable scriptline 1
Executable file
install.sh
- Executable scriptline 1
#!/usr/bin/env bash
packages/adapter-sdk/src/vgo_adapters/__init__.py
- Executable scriptline 1
Executable file
packages/adapter-sdk/src/vgo_adapters/descriptor_loader.py
- Executable scriptline 1
Executable file
packages/adapter-sdk/src/vgo_adapters/target_root_resolver.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/__init__.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/adapter_descriptor.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/adapter_registry_support.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/canonical_vibe_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/catalog_descriptor.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/discoverable_entry_surface.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/entry_root_guard.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/git_provenance.py
packages/contracts/src/vgo_contracts/governance_runtime_roles.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/host_launch_receipt.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/host_runtime_readiness.py
packages/contracts/src/vgo_contracts/install_ledger.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/installed_runtime_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/live_governance_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/mirror_topology_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/module_execution_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/runtime_packet.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/runtime_surface_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/target_root_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/tdd_evidence_contract.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/verification_scenario.py
- Executable scriptline 1
Executable file
packages/contracts/src/vgo_contracts/workspace_memory_identity.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/__init__.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/_bootstrap.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/_io.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/_path_safety.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/adapter_registry.py
packages/installer-core/src/vgo_installer/discoverable_wrappers.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/global_instruction_contract.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/global_instruction_merge.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/global_instruction_service.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/host_closure.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/install_plan.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/install_runtime.py
packages/installer-core/src/vgo_installer/ledger_service.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/materializer.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/profile_inventory.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/repair.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/runtime_packaging.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/simple_skill_installer.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/uninstall_plan.py
- Executable scriptline 1
Executable file
packages/installer-core/src/vgo_installer/uninstall_runtime.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/installer-core/src/vgo_installer/uninstall_service.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/runtime-core/src/vgo_runtime/__init__.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/artifact_contract.py
packages/runtime-core/src/vgo_runtime/canonical_entry.py
packages/runtime-core/src/vgo_runtime/compatibility_exit.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/custom_admission.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/entry_locator.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/entry_policy.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/governance.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/grade_intent.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/__init__.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/_io.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/capability_bridge.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/codex_plugins.py
packages/runtime-core/src/vgo_runtime/kernel/codex_skill_policy.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/executor.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/finder.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/host_skill_roots.py
packages/runtime-core/src/vgo_runtime/kernel/loop.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/module_assignments.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/planner.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/run_state.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/skill_index.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/skill_manifest.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/skill_resources.py
packages/runtime-core/src/vgo_runtime/kernel/task_card.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/text_tokens.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/verifier.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/kernel/work_plan.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/memory.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/planning.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/powershell_bridge.py
packages/runtime-core/src/vgo_runtime/process_tree.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/route_index.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/router_contract_runtime.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/runtime_bridge.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/runtime-core/src/vgo_runtime/runtime_summary.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/runtime_support.py
- Executable scriptline 1
Executable file - Access to secretsline 202
[Credential-related source omitted] - Access to secretsline 203
[Credential-related source omitted] - Access to secretsline 205
[Credential-related source omitted] - Access to secretsline 206
[Credential-related source omitted] - Access to secretsline 224
[Credential-related source omitted] - Access to secretsline 246
[Credential-related source omitted]
packages/runtime-core/src/vgo_runtime/runtime_truth.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/skill_authority.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/stage_machine.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/stage_stop.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/task_intent.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/workspace_memory.py
- Executable scriptline 1
Executable file
packages/runtime-core/src/vgo_runtime/workspace_memory_schema.py
- Executable scriptline 1
Executable file
packages/skill-catalog/src/vgo_catalog/__init__.py
- Executable scriptline 1
Executable file
packages/skill-catalog/src/vgo_catalog/_bootstrap.py
- Executable scriptline 1
Executable file
packages/skill-catalog/src/vgo_catalog/exporter.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/__init__.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/_bootstrap.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/_io.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/_repo.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/bio_science_pack_consolidation_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/bootstrap_doctor.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/bootstrap_doctor_runtime.py
packages/verification-core/src/vgo_verify/bootstrap_doctor_support.py
packages/verification-core/src/vgo_verify/code_quality_pack_consolidation_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/gate_engine.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/global_pack_consolidation_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/ml_skills_pruning_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/opencode_preview_smoke.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/opencode_preview_smoke_runtime.py
packages/verification-core/src/vgo_verify/opencode_preview_smoke_support.py
- Executable scriptline 1
Executable file - Network accessline 62
def build_real_opencode_config(_target_root: Path) -> dict[str, Any]: return { '$schema': 'https://opencode.ai/config.json', - Network accessline 63
return { '$schema': 'https://opencode.ai/config.json', 'theme': 'system', - Network accessline 64
'$schema': 'https://opencode.ai/config.json',
packages/verification-core/src/vgo_verify/policies.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/proof_publication.py
- Executable scriptline 1
Executable file - Access to secretsline 70
[Credential-related source omitted] - Access to secretsline 108
[Credential-related source omitted] - Access to secretsline 276
[Credential-related source omitted] - Network accessline 278
if repository: links = { "ci": f"https://github.com/{repository}/actions", - Network accessline 279
links = { "ci": f"https://github.com/{repository}/actions", "latest_release": f"https://github.com/{repository}/releases/latest", - Network accessline 280
"ci": f"https://github.com/{repository}/actions", - Network accessline 281
"latest_release": f"https://github.com/{repository}/releases/latest",
packages/verification-core/src/vgo_verify/release_notes_quality.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/release_notes_quality_runtime.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/release_notes_quality_support.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/release_truth.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/router_ai_connectivity_probe.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/router_ai_probe_advice.py
- Executable scriptline 1
Executable file - Network accessline 48
normalized = provider_type.strip().lower() if normalized in {"openai", "openai-compatible", "mock"}: return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" - Network accessline 49
if normalized in {"openai", "openai-compatible", "mock"}: return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" return resolve_first_value(base_url_names, settings_values) - Network accessline 50
return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" - Access to secretsline 212
[Credential-related source omitted] - Access to secretsline 213
[Credential-related source omitted] - Access to secretsline 227
[Credential-related source omitted] - Access to secretsline 276
[Credential-related source omitted] - Access to secretsline 331
[Credential-related source omitted] - Network accessline 414
should_try_anthropic_fallback = ( status != "ok" and normalized_base_url not in {"", "https://api.openai.com/v1", "https://api.openai.com"} - Network accessline 415
status != "ok" and normalized_base_url not in {"", "https://api.openai.com/v1", "https://api.openai.com"} and "openai.com" not in normalized_base_url - Network accessline 416
and normalized_base_url not in {"", "https://api.openai.com/v1", "https://api.openai.com"} - Access to secretsline 426
[Credential-related source omitted]
packages/verification-core/src/vgo_verify/router_ai_probe_support.py
- Executable scriptline 1
Executable file - Access to secretsline 19
[Credential-related source omitted] - Access to secretsline 22
[Credential-related source omitted] - Access to secretsline 73
[Credential-related source omitted] - Network accessline 204
payload = request_spec.get("json_body") body = json.dumps(payload, ensure_ascii=False).encode("utf-8") req = urllib.request.Request(url=url, data=body, headers=headers, method="POST") - Network accessline 205
body = json.dumps(payload, ensure_ascii=False).encode("utf-8") req = urllib.request.Request(url=url, data=body, headers=headers, method="POST") timeout_seconds = max(1.0, timeout_ms / 1000.0) - Network accessline 206
req = urllib.request.Request(url=url, data=body, headers=headers, method="POST") - Network accessline 210
try: with urllib.request.urlopen(req, timeout=timeout_seconds) as response: - Network accessline 211
with urllib.request.urlopen(req, timeout=timeout_seconds) as response:
packages/verification-core/src/vgo_verify/router_ai_probe_vector.py
- Executable scriptline 1
Executable file - Network accessline 27
normalized = provider_type.strip().lower() if normalized in {"openai", "openai-compatible"}: return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" - Network accessline 28
if normalized in {"openai", "openai-compatible"}: return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" return None - Network accessline 29
return resolve_first_value(base_url_names, settings_values) or "https://api.openai.com/v1" - Access to secretsline 62
[Credential-related source omitted] - Access to secretsline 63
[Credential-related source omitted] - Access to secretsline 100
[Credential-related source omitted]
packages/verification-core/src/vgo_verify/router_bridge_gate.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/router_bridge_gate_runtime.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/router_bridge_gate_support.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_coherence.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_coherence_runtime.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_coherence_support.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_delivery_acceptance.py
- Executable scriptline 1
#!/usr/bin/env python3
packages/verification-core/src/vgo_verify/runtime_delivery_acceptance_runtime.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_delivery_acceptance_support.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/runtime_freshness.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/scenario_runner.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/test_baseline_audit.py
packages/verification-core/src/vgo_verify/workflow_acceptance.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/workflow_acceptance_runtime.py
- Executable scriptline 1
Executable file
packages/verification-core/src/vgo_verify/workflow_acceptance_support.py
- Executable scriptline 1
Executable file
references/fixtures/runtime/vibe-sessions/20260413T131910Z-pr153-rabbit-review-fix/skeleton-receipt.json
- Network accessline 6
"branch": "fix/pr153-rabbit", "head": "235e6e1a021bfc39b0284a4636fc6c2bdb68b318", "origin": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 7
"head": "235e6e1a021bfc39b0284a4636fc6c2bdb68b318", "origin": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "pr": { - Network accessline 8
"origin": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git",
references/index.md
schemas/host-capability.schema.json
schemas/router-provider.schema.json
schemas/skill-compatibility.schema.json
schemas/skill-contract-index.v1.schema.json
schemas/skill-contract.v1.schema.json
schemas/skill.schema.json
scripts.check.upstream.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/bootstrap/one-shot-setup.ps1
- Executable scriptline 1
Executable file
scripts/bootstrap/one-shot-setup.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/bootstrap/scaffold-claude-preview.ps1
- Executable scriptline 1
Executable file
scripts/bootstrap/scaffold-claude-preview.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/bootstrap/sync-local-compat.ps1
- Executable scriptline 1
Executable file
scripts/build/assemble_distribution.py
- Executable scriptline 1
Executable file
scripts/build/sync_adapter_registry.py
- Executable scriptline 1
Executable file
scripts/build/sync_dist_release_manifests.py
- Executable scriptline 1
Executable file
scripts/build/sync_runtime_core_packaging_profiles.py
- Executable scriptline 1
Executable file
scripts/build/sync_version_governance_runtime_roles.py
- Executable scriptline 1
Executable file
scripts/common/AntiProxyGoalDrift.ps1
- Executable scriptline 1
Executable file
scripts/common/NodeLaunchWrapper.ps1
- Executable scriptline 1
Executable file
scripts/common/ProcessLedger.ps1
- Executable scriptline 1
Executable file
scripts/common/ProtectedDocumentCleanup.ps1
- Executable scriptline 1
Executable file
scripts/common/Resolve-VgoAdapter.ps1
- Executable scriptline 1
Executable file
scripts/common/adapter_registry_query.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/common/python_helpers.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/common/resolve_vgo_adapter.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/common/runtime_contracts.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/common/vibe-governance-helpers.ps1
- Executable scriptline 1
Executable file
scripts/common/vibe-wave-gate-runner.ps1
- Executable scriptline 1
Executable file
scripts/governance/Invoke-NodeProcessAudit.ps1
- Executable scriptline 1
Executable file
scripts/governance/Invoke-NodeZombieCleanup.ps1
- Executable scriptline 1
Executable file
scripts/governance/audit-upstream.ps1
- Executable scriptline 1
Executable file - Network accessline 43
param([string]$RepoUrl) $u = Normalize-GitHubRepoUrl -Url $RepoUrl if ($u -notmatch "^https://github\.com/([^/]+)/([^/]+)$") { return $null } - Network accessline 44
$u = Normalize-GitHubRepoUrl -Url $RepoUrl if ($u -notmatch "^https://github\.com/([^/]+)/([^/]+)$") { return $null } return [pscustomobject]@{ - Network accessline 45
if ($u -notmatch "^https://github\.com/([^/]+)/([^/]+)$") { return $null } - Access to secretsline 54
[Credential-related source omitted] - Access to secretsline 55
[Credential-related source omitted] - Network accessline 349
$repoToSources = @{} foreach ($entry in $allEntries) { if (-not $entry.repo_url.StartsWith('https://github.com/')) { continue } - Network accessline 350
foreach ($entry in $allEntries) { if (-not $entry.repo_url.StartsWith('https://github.com/')) { continue } if (-not $repoToSources.ContainsKey($entry.repo_url)) { - Network accessline 351
if (-not $entry.repo_url.StartsWith('https://github.com/')) { continue } - Network accessline 405
if (-not $NoGitHub) { $repoInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders - Network accessline 406
$repoInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders - Network accessline 417
} if (-not [string]::IsNullOrWhiteSpace($defaultBranch)) { $headInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/commits/{2}" -f $parsed.owner, $parsed.repo, $defaultBranch) -Headers $githubHeaders - Network accessline 418
if (-not [string]::IsNullOrWhiteSpace($defaultBranch)) { $headInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/commits/{2}" -f $parsed.owner, $parsed.repo, $defaultBranch) -Headers $githubHeaders - Network accessline 419
$headInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/commits/{2}" -f $parsed.owner, $parsed.repo, $defaultBranch) -Headers $githubHeaders - Network accessline 427
} } $releaseInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/releases/latest" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders - Network accessline 428
} $releaseInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/releases/latest" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders if ($releaseInfo) { - Network accessline 429
$releaseInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/releases/latest" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders - Network accessline 433
} if ([string]::IsNullOrWhiteSpace($latestTag)) { $tagInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/tags?per_page=1&page=1" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders - Network accessline 434
if ([string]::IsNullOrWhiteSpace($latestTag)) { $tagInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/tags?per_page=1&page=1" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders if ($tagInfo - - Network accessline 435
$tagInfo = Try-InvokeRestJson -Url ("https://api.github.com/repos/{0}/{1}/tags?per_page=1&page=1" -f $parsed.owner, $parsed.repo) -Headers $githubHeaders
scripts/governance/export-repo-cleanliness-inventory.ps1
- Executable scriptline 1
Executable file
scripts/governance/install-local-worktree-excludes.ps1
- Executable scriptline 1
Executable file
scripts/governance/invoke-mem0-policy.ps1
- Executable scriptline 1
Executable file
scripts/governance/invoke-openspec-governance.ps1
- Executable scriptline 1
Executable file
scripts/governance/new-origin-record.ps1
- Executable scriptline 1
Executable file
scripts/governance/phase-end-cleanup.ps1
- Executable scriptline 1
Executable file
scripts/governance/publish-absorption-soft-rollout.ps1
- Executable scriptline 1
Executable file
scripts/governance/publish-openspec-soft-rollout.ps1
- Executable scriptline 1
Executable file
scripts/governance/release-cut.ps1
- Executable scriptline 1
Executable file
scripts/governance/set-gsd-overlay-rollout.ps1
- Executable scriptline 1
Executable file
scripts/governance/set-openspec-rollout.ps1
- Executable scriptline 1
Executable file
scripts/governance/sync-bundled-vibe.ps1
- Executable scriptline 1
Executable file
scripts/install/Install-VgoAdapter.ps1
- Executable scriptline 1
Executable file
scripts/install/install_vgo_adapter.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/overlay/suggest-browserops-provider.ps1
- Executable scriptline 1
Executable file
scripts/overlay/suggest-overlays.ps1
- Executable scriptline 1
Executable file
scripts/release/build_release_bundle.py
- Executable scriptline 1
Executable file
scripts/research/build-eval-slicing-catalog.ps1
- Executable scriptline 1
Executable file
scripts/research/build-watch-portfolio-review.ps1
- Executable scriptline 1
Executable file
scripts/research/build-xl-operator-checklist.ps1
- Executable scriptline 1
Executable file
scripts/research/extract-prompt-signals.ps1
- Executable scriptline 1
Executable file
scripts/research/generate-vco-suggestions.ps1
- Executable scriptline 1
Executable file
scripts/research/sync-mcp-catalog.ps1
- Executable scriptline 1
Executable file
scripts/research/vibe-adaptive-train.ps1
- Executable scriptline 1
Executable file
scripts/router/invoke-pack-route.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/router/modules/00-core-utils.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/01-openai-responses.ps1
- Executable scriptline 1
Executable file - Network accessline 3
$script:OpenAiDefaultBaseUrl = "https://api.openai.com/v1" - Access to secretsline 44
[Credential-related source omitted] - Access to secretsline 242
[Credential-related source omitted] - Access to secretsline 253
[Credential-related source omitted] - Access to secretsline 354
[Credential-related source omitted] - Access to secretsline 364
[Credential-related source omitted] - Access to secretsline 442
[Credential-related source omitted] - Access to secretsline 452
[Credential-related source omitted] - Access to secretsline 526
[Credential-related source omitted] - Access to secretsline 537
[Credential-related source omitted]
scripts/router/modules/10-observability.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/11-route-probe.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/12-heartbeat.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/19-custom-admission.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/20-routing-rules.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/21-capability-interview.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/22-intent-contract.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/30-openspec.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/31-gsd-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/32-prompt-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/33-memory-governance.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/34-data-scale-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/35-quality-debt-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/36-framework-interop-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/37-ml-lifecycle-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/38-python-clean-code-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/39-system-design-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/40-cuda-kernel-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/42-ai-rerank-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/43-retrieval-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/44-dialectic-team-gate.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/44-exploration-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/45-daily-dialectic-guard.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/47-closure-overlay.ps1
- Executable scriptline 1
Executable file
scripts/router/modules/48-llm-acceleration-overlay.ps1
- Executable scriptline 1
Executable file - Access to secretsline 31
[Credential-related source omitted] - Access to secretsline 88
[Credential-related source omitted] - Access to secretsline 602
[Credential-related source omitted] - Access to secretsline 848
[Credential-related source omitted] - Access to secretsline 855
[Credential-related source omitted] - Access to secretsline 858
[Credential-related source omitted] - Access to secretsline 1121
[Credential-related source omitted] - Network accessline 1150
$normalizedBaseUrl = ([string]$BaseUrl).Trim().ToLowerInvariant() if (-not $normalizedBaseUrl) { return $false } if ($normalizedBaseUrl -eq "https://api.openai.com" -or $normalizedBaseUrl -eq "https://api.openai.com/v1") { return $f - Network accessline 1151
if (-not $normalizedBaseUrl) { return $false } if ($normalizedBaseUrl -eq "https://api.openai.com" -or $normalizedBaseUrl -eq "https://api.openai.com/v1") { return $false } if ($normalizedBaseUrl -match "openai\.com") { return $fals - Network accessline 1152
if ($normalizedBaseUrl -eq "https://api.openai.com" -or $normalizedBaseUrl -eq "https://api.openai.com/v1") { return $false } - Access to secretsline 1259
[Credential-related source omitted] - Access to secretsline 1263
[Credential-related source omitted] - Access to secretsline 1267
[Credential-related source omitted] - Access to secretsline 1271
[Credential-related source omitted] - Access to secretsline 1299
[Credential-related source omitted] - Access to secretsline 1395
[Credential-related source omitted] - Access to secretsline 1399
[Credential-related source omitted] - Access to secretsline 1652
[Credential-related source omitted] - Access to secretsline 2014
[Credential-related source omitted]
scripts/router/modules/49-prompt-asset-boost.ps1
scripts/router/resolve-pack-route.ps1
- Executable scriptline 1
Executable file
scripts/router/runtime_neutral/custom_admission.py
- Executable scriptline 1
Executable file
scripts/router/runtime_neutral/router_contract.py
- Executable scriptline 1
Executable file
scripts/ruc-nlpir/preflight.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Freeze-RuntimeInputPacket.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-AntiProxyGoalDriftCompaction.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-DeepInterview.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-PhaseCleanup.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-PlanExecute.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-SkeletonCheck.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Invoke-VibeCanonicalEntry.ps1
- Executable scriptline 1
Executable file
scripts/runtime/VibeMemoryActivation.Common.ps1
- Executable scriptline 1
Executable file
scripts/runtime/VibeMemoryBackends.Common.ps1
- Executable scriptline 1
Executable file
scripts/runtime/VibeRuntime.Common.ps1
- Executable scriptline 1
Executable file
scripts/runtime/VibeSkillRouting.Common.ps1
- Executable scriptline 1
Executable file
scripts/runtime/VibeWorkspaceMemory.Common.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Write-RequirementDoc.ps1
- Executable scriptline 1
Executable file
scripts/runtime/Write-XlPlan.ps1
- Executable scriptline 1
Executable file
scripts/runtime/invoke-vibe-runtime.ps1
- Executable scriptline 1
Executable file
scripts/runtime/memory_backend_driver.py
- Executable scriptline 1
Executable file
scripts/runtime/skill_authority_driver.py
- Executable scriptline 1
Executable file
scripts/runtime/workspace_memory_driver.py
- Executable scriptline 1
Executable file
scripts/setup/check-kvm-host-readiness.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/setup/check-windows-eval-iso-readiness.sh
- Executable scriptline 1
#!/usr/bin/env bash - Network accessline 4
ISO_PATH="${HOME}/Downloads/windows11-eval.iso" SOURCE_URL="https://aka.ms/Win11E-ISO-25H2-en-us" - Network accessline 5
SOURCE_URL="https://aka.ms/Win11E-ISO-25H2-en-us" - Dangerous shell operationline 34
trap 'rm -f "${HEADERS}"' EXIT - Network accessline 36
if curl -I -L --max-time 30 -D "${HEADERS}" -o /dev/null "${SOURCE_URL}" >/dev/null 2>&1; then
scripts/setup/check-windows-proof-vm-state.sh
- Executable scriptline 1
#!/usr/bin/env bash
scripts/setup/export-codex-settings-sanitized.ps1
scripts/setup/fetch-windows11-eval-iso.sh
- Executable scriptline 1
#!/usr/bin/env bash - Network accessline 4
SOURCE_URL="https://aka.ms/Win11E-ISO-25H2-en-us" - Network accessline 81
if ! command -v curl >/dev/null 2>&1; then - Network accessline 82
echo "[ERROR] curl is required." >&2 - Dangerous shell operationline 87
trap 'rm -f "${HEADERS}"' EXIT - Network accessline 89
curl -I -L -D "${HEADERS}" -o /dev/null "${SOURCE_URL}" >/dev/null 2>&1 - Network accessline 108
if [[ -z "${FINAL_URL}" ]]; then FINAL_URL="${SOURCE_URL}" - Network accessline 109
FINAL_URL="${SOURCE_URL}" - Network accessline 116
if [[ "${PRINT_ONLY}" == "1" ]]; then printf 'source_url=%s\n' "${SOURCE_URL}" - Network accessline 117
printf 'source_url=%s\n' "${SOURCE_URL}" - Network accessline 118
printf 'final_url=%s\n' "${FINAL_URL}" - Network accessline 137
echo "[INFO] Official source: ${SOURCE_URL}" - Network accessline 162
curl -L --fail --progress-bar -C - -o "${PARTIAL_PATH}" "${FINAL_URL}"
scripts/setup/install-local-vm-host.sh
scripts/setup/persist-codex-openai-env.ps1
scripts/setup/run-windows-proof-vm.sh
- Executable scriptline 1
#!/usr/bin/env bash - Network accessline 150
if [[ -z "${ISO_PATH}" && -z "${DISK_IMAGE_PATH}" ]]; then echo "[ERROR] Either --iso or --disk-image is required." >&2 echo "[INFO] Official Windows ISO entry: https://www.microsoft.com/en-us/software-download/windows10iso" >&2 - Network accessline 151
echo "[ERROR] Either --iso or --disk-image is required." >&2 echo "[INFO] Official Windows ISO entry: https://www.microsoft.com/en-us/software-download/windows10iso" >&2 exit 1 - Network accessline 152
echo "[INFO] Official Windows ISO entry: https://www.microsoft.com/en-us/software-download/windows10iso" >&2 - Dangerous shell operationline 301
rm -f "${TPM_SOCKET}" "${TPM_PIDFILE}" - Dangerous shell operationline 315
rm -f "${PIDFILE}" "${MONITOR_SOCKET}" "${QMP_SOCKET}" - Access to secretsline 378
[Credential-related source omitted] - Dangerous shell operationline 387
rm -f "${BOOT_KEY_LOG}" - Access to secretsline 388
[Credential-related source omitted] - Access to secretsline 402
[Credential-related source omitted] - Access to secretsline 403
[Credential-related source omitted]
scripts/setup/send-qmp-boot-keys.py
scripts/setup/send-qmp-text.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 85
sock: socket.socket | None = None try: sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) - Network accessline 86
try: sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) sock.settimeout(SOCKET_TIMEOUT_SECONDS) - Network accessline 87
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
scripts/setup/show-windows-proof-media-options.sh
- Executable scriptline 1
#!/usr/bin/env bash - Network accessline 15
1. Windows 11 Enterprise Evaluation ISO https://www.microsoft.com/en-us/evalcenter/download-windows-11-enterprise - Network accessline 16
https://www.microsoft.com/en-us/evalcenter/download-windows-11-enterprise - Network accessline 21
2. Windows developer virtual machines https://developer.microsoft.com/en-us/windows/downloads/virtual-machines/ - Network accessline 22
https://developer.microsoft.com/en-us/windows/downloads/virtual-machines/ - Network accessline 29
3. Windows 11 and Microsoft 365 Deployment Lab Kit https://www.microsoft.com/en-us/evalcenter/download-windows-11-office-365-lab-kit - Network accessline 30
https://www.microsoft.com/en-us/evalcenter/download-windows-11-office-365-lab-kit
scripts/setup/stop-windows-proof-vm.sh
scripts/setup/sync-codex-settings-to-user-env.ps1
scripts/uninstall/Uninstall-VgoAdapter.ps1
- Executable scriptline 1
Executable file
scripts/uninstall/uninstall_vgo_adapter.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/cer-compare.ps1
- Executable scriptline 1
Executable file
scripts/verify/lib/VibeOfflineSkillsAudit.Suites.ps1
- Executable scriptline 1
Executable file
scripts/verify/lib/VibeOfflineSkillsAudit.ps1
- Executable scriptline 1
Executable file
scripts/verify/lib/VibeRouteAudit.Suites.ps1
- Executable scriptline 1
Executable file
scripts/verify/lib/VibeRouteAudit.ps1
- Executable scriptline 1
Executable file
scripts/verify/live-document-gate.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/probe-scientific-packs.ps1
- Executable scriptline 1
Executable file
scripts/verify/publish-proof.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/_bootstrap.py
- Executable scriptline 1
Executable file
scripts/verify/runtime_neutral/bio_science_pack_consolidation_audit.py
- Executable scriptline 1
Executable file
scripts/verify/runtime_neutral/bootstrap_doctor.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/code_quality_pack_consolidation_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/coherence_gate.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/freshness_gate.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/global_pack_consolidation_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/ml_skills_pruning_audit.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/opencode_preview_smoke.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/release_notes_quality.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/release_truth_gate.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/router_ai_connectivity_probe.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/router_bridge_gate.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/runtime_delivery_acceptance.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/runtime_neutral/workflow_acceptance_runner.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/skill-metadata-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/test-baseline-audit.py
- Executable scriptline 1
#!/usr/bin/env python3
scripts/verify/tool-governance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vgo-adapter-closure-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vgo-adapter-target-root-guard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-adaptive-routing-readiness-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ai-rerank-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-bio-science-pack-consolidation-audit-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-bom-frontmatter-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-bootstrap-doctor-gate.ps1
scripts/verify/vibe-browserops-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-browserops-scorecard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-browserops-softrollout-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-built-in-skill-governance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-candidate-quality-board-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-canonical-entry-truth-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-capability-catalog-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-capability-dedup-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-capability-lifecycle-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-child-specialist-escalation-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-code-quality-pack-consolidation-audit-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-config-parity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-connector-action-ledger-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-connector-admission-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-connector-sandbox-simulation-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-connector-scorecard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-context-retro-smoke.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-host-degrade-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-host-install-isolation-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-host-route-parity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-plane-conflict-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-plane-replay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cross-plane-task-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-cuda-kernel-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-current-routing-contract-scan.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-current-routing-debt-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-data-scale-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-deep-discovery-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-deep-discovery-scenarios.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-deep-extraction-pilot-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-desktopops-replay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-desktopops-shadow-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-desktopops-softrollout-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-developer-entry-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-discovery-intake-scorecard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-dist-manifest-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-docling-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-docling-contract-v2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-document-asset-safety-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-document-failure-taxonomy-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ecosystem-absorption-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-exploration-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-external-corpus-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-framework-interop-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-gate-reliability-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-generate-skills-lock.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-global-pack-consolidation-audit-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-governance-entry-compression-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-governed-runtime-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-gsd-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-heartbeat-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-host-adapter-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-host-capability-schema-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-installed-runtime-freshness-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-keyword-precision-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-letta-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-letta-policy-conformance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-linux-pwsh-proof-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-linux-router-no-pwsh-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-llm-acceleration-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-manual-apply-policy-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-mem0-backend-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-mem0-softrollout-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-memory-governance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-memory-quality-eval-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-memory-runtime-v3-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-memory-tier-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-mirror-edit-hygiene-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ml-lifecycle-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ml-skills-pruning-audit-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-module-dispatch-closure-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-nested-bundled-parity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-no-duplicate-canonical-surface-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-no-self-introduced-fallback-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-no-silent-fallback-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-node-zombie-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-observability-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-offline-hash-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-offline-lock-parity-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-offline-required-skills-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-offline-skills-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-openspec-governance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-openworld-runtime-eval-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-operator-preview-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ops-cockpit-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-ops-dashboard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-orchestration-core-consolidation-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-orchestration-core-hard-removal-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-origin-provenance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-output-artifact-boundary-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-output-fixture-migration-stage2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-pack-regression-matrix.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-pack-routing-smoke.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-pilot-scenarios.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-platform-doctor-parity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-platform-promotion-bundle.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-platform-support-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-promotion-board-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-promotion-scorecard-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-prompt-asset-boost-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-prompt-intelligence-assets-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-prompt-intelligence-eval-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-prompt-intelligence-productization-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-prompt-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-proof-bundle-tracked-files-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-python-clean-code-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-quality-debt-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-evidence-bundle-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-install-runtime-coherence-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-notes-quality-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-train-v2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-truth-consistency-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-release-truth-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-remediation-foundation-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-repo-cleanliness-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-retrieval-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-retro-context-regression-matrix.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-role-pack-governance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-role-pack-v2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-rollback-drill-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-rollout-proposal-boundedness-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-root-child-hierarchy-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-router-ai-connectivity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-router-offline-degrade-contract-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-router-provider-neutrality-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-local-owner-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-no-local-candidate-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-probe-research.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-requested-skill-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-smoke.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-stability-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-routing-terminology-hard-cleanup-scan.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-runtime-boundary-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-runtime-execution-proof-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-skill-contract-parity-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-skill-contract-schema-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-skill-harvest-v2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-skill-index-routing-audit.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-soft-migration-practice.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-subagent-handoff-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-system-design-overlay-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-third-party-disclosure-parity-gate.ps1
- Executable scriptline 1
Executable file - Network accessline 65
foreach ($entry in @($manifest.entries)) { $repoUrl = [string]$entry.repo_url if ($repoUrl -match '^https://github\.com/([^/]+)/([^/]+)$') { - Network accessline 66
$repoUrl = [string]$entry.repo_url if ($repoUrl -match '^https://github\.com/([^/]+)/([^/]+)$') { [void]$canonicalRepos.Add(('{0}/{1}' -f $Matches[1], $Matches[2])) - Network accessline 67
if ($repoUrl -match '^https://github\.com/([^/]+)/([^/]+)$') {
scripts/verify/vibe-uninstall-coherence-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-universalization-no-regression-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-upstream-corpus-manifest-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-upstream-lock-coverage-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-upstream-mirror-freshness-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-upstream-reaudit-matrix-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-upstream-value-ops-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-version-consistency-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-version-packaging-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave121-upstream-mapping-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave124-ops-cockpit-v2-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave125-gate-family-convergence-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave40-63-board-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave64-82-closure-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-wave83-100-closure-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/vibe-workflow-acceptance-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/watch-portfolio-gate.ps1
- Executable scriptline 1
Executable file
scripts/verify/wave15-18-consistency-gate.ps1
- Executable scriptline 1
Executable file
templates/ORIGIN.md.tmpl
templates/cer-report.schema.json
tests/__init__.py
- Executable scriptline 1
Executable file
tests/_python_source_roots.py
- Executable scriptline 1
Executable file
tests/bash_test_support.py
tests/conftest.py
tests/contract/test_adapter_descriptor_contract.py
- Executable scriptline 1
Executable file
tests/contract/test_install_ledger_contract.py
- Executable scriptline 1
Executable file
tests/contract/test_repo_layout_contract.py
- Executable scriptline 1
Executable file
tests/contract/test_runtime_packet_contract.py
- Executable scriptline 1
Executable file
tests/contract/test_vibe_discoverable_entry_contract.py
- Executable scriptline 1
Executable file
tests/e2e/test_distribution_build.py
- Executable scriptline 1
Executable file
tests/integration/test_adapter_closure_gate_registry_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_adapter_registry_query_delegation.py
- Executable scriptline 1
Executable file
tests/integration/test_adapter_registry_single_source.py
- Executable scriptline 1
Executable file
tests/integration/test_adapter_sdk_registry_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_bootstrap_entrypoint_registry_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_bootstrap_host_catalog_shared_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_canonical_vibe_truth_gate.py
- Executable scriptline 1
Executable file
tests/integration/test_catalog_contract_consumption.py
- Executable scriptline 1
Executable file
tests/integration/test_check_entrypoint_registry_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_check_shell_bootstrap_doctor_counting.py
- Executable scriptline 1
Executable file
tests/integration/test_cli_installer_core_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_cli_main_infra_separation.py
- Executable scriptline 1
Executable file
tests/integration/test_cli_runtime_entrypoint_contract_cutover.py
- Executable scriptline 1
Executable file - Access to secretsline 79
[Credential-related source omitted] - Access to secretsline 131
[Credential-related source omitted] - Access to secretsline 156
[Credential-related source omitted] - Access to secretsline 301
[Credential-related source omitted] - Access to secretsline 448
[Credential-related source omitted]
tests/integration/test_cli_verify_runtime_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_codex_install_prompt_discoverability.py
- Executable scriptline 1
Executable file
tests/integration/test_dist_manifest_generation.py
- Executable scriptline 1
Executable file
tests/integration/test_frontmatter_gate_runtime_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_host_capability_matrix_single_source.py
- Executable scriptline 1
Executable file
tests/integration/test_host_global_bootstrap_shell_lifecycle.py
tests/integration/test_install_rerun_matrix.py
- Executable scriptline 1
Executable file
tests/integration/test_installed_runtime_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_mirror_topology_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_multi_host_real_host_root_docs.py
- Executable scriptline 1
Executable file
tests/integration/test_new_origin_record_vendor_guard.py
tests/integration/test_platform_doctor_parity_gate_single_source.py
- Executable scriptline 1
Executable file
tests/integration/test_powershell_compat_shim_cutover.py
tests/integration/test_powershell_installed_runtime_contract_bridge.py
- Executable scriptline 1
Executable file
tests/integration/test_powershell_wrapper_host_validation_dedupe.py
- Executable scriptline 1
Executable file
tests/integration/test_proof_bundle_manifest_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_public_install_uninstall_guidance.py
tests/integration/test_pwsh_wrapper_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_real_canonical_entry_bounded_stop.py
tests/integration/test_release_cut_gate_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_resolver_shim_delegation.py
- Executable scriptline 1
Executable file
tests/integration/test_router_core_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_router_keyword_inference.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_common_registry_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_config_manifest_roles.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_core_packaging_roles.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_payload_dependency_coverage.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_script_manifest_roles.py
- Executable scriptline 1
Executable file
tests/integration/test_runtime_surface_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_shared_run_artifact_contract.py
- Executable scriptline 1
Executable file - Access to secretsline 774
[Credential-related source omitted] - Access to secretsline 1050
[Credential-related source omitted] - Access to secretsline 1478
[Credential-related source omitted] - Access to secretsline 1524
[Credential-related source omitted] - Access to secretsline 1542
[Credential-related source omitted] - Access to secretsline 1566
[Credential-related source omitted] - Access to secretsline 1602
[Credential-related source omitted]
tests/integration/test_shell_frontend_windows_handoff_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_shell_wrapper_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_target_root_guard_single_source.py
- Executable scriptline 1
Executable file
tests/integration/test_verification_core_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_verification_runtime_entrypoint_contract_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_verification_scenario_runner.py
- Executable scriptline 1
Executable file
tests/integration/test_verify_gate_single_source_cutover.py
- Executable scriptline 1
Executable file
tests/integration/test_vibe_skill_bootstrap_contract.py
- Executable scriptline 1
Executable file
tests/integration/test_vibe_wrapper_shim_contract.py
- Executable scriptline 1
Executable file
tests/issue_167_runtime_surfaces.py
- Executable scriptline 1
Executable file
tests/replay/fixtures/provider-state-matrix.json
tests/runtime_neutral/live_contract_fixtures.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_active_consultation_simplification.py
tests/runtime_neutral/test_agent_led_skill_execution_language.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_agent_skill_organization_contract.py
- Executable scriptline 1
Executable file - Access to secretsline 46
[Credential-related source omitted] - Access to secretsline 927
[Credential-related source omitted] - Access to secretsline 983
[Credential-related source omitted] - Access to secretsline 1036
[Credential-related source omitted] - Access to secretsline 1059
[Credential-related source omitted]
tests/runtime_neutral/test_apps_surface_hygiene.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bash_test_support.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bio_science_boundary_hardening.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bio_science_direct_owner_routing.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bootstrap_doctor.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bootstrap_shell_target_root_guard.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bundled_runtime_mirror.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_bundled_skill_governance_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_check_installed_runtime_root.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_check_shell_target_root_guard.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_claude_preview_scaffold.py
- Executable scriptline 1
Executable file - Access to secretsline 35
[Credential-related source omitted] - Network accessline 67
self.existing_settings = { 'env': { 'ANTHROPIC_BASE_URL': 'https://api.example.com/v1', - Network accessline 68
[Credential-related source omitted] - Network accessline 69
'ANTHROPIC_BASE_URL': 'https://api.example.com/v1', - Access to secretsline 70
[Credential-related source omitted]
tests/runtime_neutral/test_codex_memory_user_simulation.py
- Executable scriptline 1
Executable file - Access to secretsline 73
[Credential-related source omitted] - Access to secretsline 110
[Credential-related source omitted] - Access to secretsline 409
[Credential-related source omitted] - Access to secretsline 509
[Credential-related source omitted] - Access to secretsline 586
[Credential-related source omitted] - Access to secretsline 600
[Credential-related source omitted]
tests/runtime_neutral/test_coherence_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_conftest_subprocess_run.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_cross_host_memory_identity.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_current_routing_contract_scan.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_current_routing_docs_entrypoint.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_cursor_managed_preview.py
tests/runtime_neutral/test_custom_admission_bridge.py
tests/runtime_neutral/test_discoverable_wrapper_host_visibility.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_docs_readme_encoding.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_docs_research_publishing_boundary_routing.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_docs_source_neutral_links.py
- Executable scriptline 1
Executable file - Network accessline 7
REPO_ROOT = Path(__file__).resolve().parents[2] SELF_REPO_GITHUB = "https://github.com/foryourhealth111-pixel/Vibe-Skills" - Network accessline 8
SELF_REPO_GITHUB = "https://github.com/foryourhealth111-pixel/Vibe-Skills" - Network accessline 9
SELF_REPO_RAW = "https://raw.githubusercontent.com/foryourhealth111-pixel/Vibe-Skills"
tests/runtime_neutral/test_document_chain_layering_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_forbidden_mcp_installation_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_freshness_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_frontmatter_gate_scope_activation.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_generated_nested_bundled.py
tests/runtime_neutral/test_global_instruction_bootstrap_runtime.py
- Executable scriptline 1
Executable file - Access to secretsline 18
[Credential-related source omitted] - Network accessline 111
agents_path.write_text("# Existing OpenCode rules\n", encoding="utf-8") real_config = target_root / "opencode.json" original = {"$schema": "https://opencode.ai/config.json", "mcp": {"playwright": {"enabled": True}}} - Network accessline 112
real_config = target_root / "opencode.json" original = {"$schema": "https://opencode.ai/config.json", "mcp": {"playwright": {"enabled": True}}} real_config.write_text(json.dumps(original, indent=2) + "\n", encoding=" - Network accessline 113
original = {"$schema": "https://opencode.ai/config.json", "mcp": {"playwright": {"enabled": True}}}
tests/runtime_neutral/test_governed_runtime_bridge.py
- Executable scriptline 1
Executable file - Access to secretsline 286
[Credential-related source omitted] - Access to secretsline 484
[Credential-related source omitted] - Access to secretsline 601
[Credential-related source omitted] - Access to secretsline 677
[Credential-related source omitted] - Access to secretsline 761
[Credential-related source omitted] - Access to secretsline 835
[Credential-related source omitted] - Access to secretsline 909
[Credential-related source omitted] - Access to secretsline 965
[Credential-related source omitted]
tests/runtime_neutral/test_governed_runtime_lineage.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_governed_templates.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_install_generated_nested_bundled.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_install_profile_differentiation.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_installed_host_runtime_simulation.py
tests/runtime_neutral/test_installed_runtime_policy_remap.py
tests/runtime_neutral/test_installed_runtime_scripts.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_installed_runtime_uninstall.py
tests/runtime_neutral/test_intent_contract_host_fidelity.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_l_xl_agent_execution_handoff.py
tests/runtime_neutral/test_live_document_contract_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_llm_acceleration_overlay_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_llm_acceleration_overlay_provider_paths.py
- Executable scriptline 1
Executable file - Access to secretsline 72
[Credential-related source omitted] - Network accessline 85
+ [ "$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 86
"$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", "function Invoke-OpenAiResponsesCreate { throw 'responses should not be called for anthropi - Network accessline 87
"$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 136
+ [ "$policy.provider.type = 'openai'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 137
"$policy.provider.type = 'openai'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", "$script:attempts = @()", - Network accessline 138
"$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 181
+ [ "$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 182
"$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", "function Invoke-OpenAiResponsesCreate { throw 'responses should not be called for anthropi - Network accessline 183
"$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 218
+ [ "$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", - Network accessline 219
"$policy.provider.type = 'anthropic-compatible'", "$policy.provider.base_url = 'https://anthropic-gateway.example'", "function Invoke-OpenAiResponsesCreate { throw 'responses should not be called for anthropi - Network accessline 220
"$policy.provider.base_url = 'https://anthropic-gateway.example'",
tests/runtime_neutral/test_memory_ingest_noise_filters.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_memory_progressive_disclosure.py
tests/runtime_neutral/test_memory_runtime_activation.py
tests/runtime_neutral/test_module_skill_dispatch_safety.py
tests/runtime_neutral/test_non_code_task_classification.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_offline_skills_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_openclaw_runtime_core.py
tests/runtime_neutral/test_opencode_managed_preview.py
- Executable scriptline 1
Executable file - Access to secretsline 18
[Credential-related source omitted] - Network accessline 95
json.dumps( { "$schema": "https://opencode.ai/config.json", - Network accessline 96
{ "$schema": "https://opencode.ai/config.json", "theme": "system", - Network accessline 97
"$schema": "https://opencode.ai/config.json", - Network accessline 127
settings_path = target_root / "opencode.json" original = { "$schema": "https://opencode.ai/config.json", - Network accessline 128
original = { "$schema": "https://opencode.ai/config.json", "theme": "system", - Network accessline 129
"$schema": "https://opencode.ai/config.json",
tests/runtime_neutral/test_opencode_preview_parity.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_outputs_boundary_migration.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_pack_manifest_role_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_powershell_entrypoint_help.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_python_validation_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_readme_benchmark_results.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_readme_install_cta_assets.py
- Executable scriptline 1
Executable file - Network accessline 5
ROOT = Path(__file__).resolve().parents[2] SVG_NS = "{http://www.w3.org/2000/svg}" - Network accessline 6
SVG_NS = "{http://www.w3.org/2000/svg}" - Network accessline 46
assert f"<strong>{labels[language]}</strong>" in readme assert "https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest" in readme - Network accessline 47
assert "https://github.com/foryourhealth111-pixel/Vibe-Skills/releases/latest" in readme
tests/runtime_neutral/test_readme_preface_assets.py
tests/runtime_neutral/test_readme_star_history_assets.py
- Executable scriptline 1
Executable file - Network accessline 11
) PUBLIC_PAGE_URL = ( "https://www.star-history.com/" - Network accessline 12
PUBLIC_PAGE_URL = ( "https://www.star-history.com/" "?repos=foryourhealth111-pixel%2FVibe-Skills&type=date&legend=top-left" - Network accessline 13
"https://www.star-history.com/" - Network accessline 15
) CHART_URL_PATTERN = re.compile( r'https://api\.star-history\.com/chart\?[^"\s<>]+' - Network accessline 16
CHART_URL_PATTERN = re.compile( r'https://api\.star-history\.com/chart\?[^"\s<>]+' ) - Network accessline 17
r'https://api\.star-history\.com/chart\?[^"\s<>]+' - Network accessline 26
assert len(chart_urls) == 3 assert readme.count("https://api.star-history.com") == 3 - Network accessline 27
assert readme.count("https://api.star-history.com") == 3
tests/runtime_neutral/test_release_cut_operator.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_release_notes_quality.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_release_surface.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_release_truth_gate.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_repo_cleanliness_policy.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_repo_config_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_retired_agent_execution_surfaces.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_root_child_hierarchy_bridge.py
tests/runtime_neutral/test_router_ai_connectivity_probe.py
- Executable scriptline 1
Executable file - Network accessline 50
"model": "gpt-4.1-mini", "model_env": "VCO_INTENT_ADVICE_MODEL", "base_url": "https://api.openai.com/v1", - Network accessline 51
"model_env": "VCO_INTENT_ADVICE_MODEL", "base_url": "https://api.openai.com/v1", "base_url_env_candidates": ["VCO_INTENT_ADVICE_BASE_URL"], - Network accessline 52
"base_url": "https://api.openai.com/v1", - Access to secretsline 54
[Credential-related source omitted] - Network accessline 62
"embedding_provider": { "type": "openai", "base_url": "https://api.openai.com/v1", - Network accessline 63
"type": "openai", "base_url": "https://api.openai.com/v1", "base_url_env_candidates": ["VCO_VECTOR_DIFF_BASE_URL"], - Network accessline 64
"base_url": "https://api.openai.com/v1", - Access to secretsline 67
[Credential-related source omitted] - Access to secretsline 85
[Credential-related source omitted] - Access to secretsline 86
[Credential-related source omitted] - Access to secretsline 115
[Credential-related source omitted] - Access to secretsline 122
[Credential-related source omitted] - Access to secretsline 136
[Credential-related source omitted] - Access to secretsline 147
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Access to secretsline 166
[Credential-related source omitted] - Access to secretsline 179
[Credential-related source omitted] - Access to secretsline 190
[Credential-related source omitted] - Access to secretsline 225
[Credential-related source omitted] - Network accessline 241
policy = self._policy() policy["provider"]["type"] = "anthropic-compatible" policy["provider"]["base_url"] = "https://anthropic-gateway.example" - Network accessline 242
policy["provider"]["type"] = "anthropic-compatible" policy["provider"]["base_url"] = "https://anthropic-gateway.example" self._write_policy(policy) - Network accessline 243
policy["provider"]["base_url"] = "https://anthropic-gateway.example" - Access to secretsline 245
[Credential-related source omitted] - Access to secretsline 264
[Credential-related source omitted] - Network accessline 278
policy = self._policy() policy["provider"]["type"] = "openai" policy["provider"]["base_url"] = "https://anthropic-gateway.example" - Network accessline 279
policy["provider"]["type"] = "openai" policy["provider"]["base_url"] = "https://anthropic-gateway.example" self._write_policy(policy) - Network accessline 280
policy["provider"]["base_url"] = "https://anthropic-gateway.example" - Access to secretsline 282
[Credential-related source omitted] - Access to secretsline 307
[Credential-related source omitted] - Access to secretsline 323
[Credential-related source omitted] - Access to secretsline 336
[Credential-related source omitted] - Access to secretsline 347
[Credential-related source omitted] - Access to secretsline 370
[Credential-related source omitted] - Access to secretsline 387
[Credential-related source omitted] - Access to secretsline 410
[Credential-related source omitted] - Access to secretsline 427
[Credential-related source omitted] - Access to secretsline 450
[Credential-related source omitted] - Access to secretsline 463
[Credential-related source omitted] - Access to secretsline 465
[Credential-related source omitted] - Access to secretsline 479
[Credential-related source omitted] - Access to secretsline 492
[Credential-related source omitted] - Access to secretsline 494
[Credential-related source omitted] - Access to secretsline 510
[Credential-related source omitted]
tests/runtime_neutral/test_router_authority_safe_fallback.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_router_authority_safe_fallback_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_router_bridge.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_router_ownership_docs_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_runtime_authority_docs_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_runtime_contract_schema.py
tests/runtime_neutral/test_runtime_contracts.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_runtime_delivery_acceptance.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_runtime_entrypoint_helper.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_runtime_route_output_shape.py
tests/runtime_neutral/test_runtime_summary_acceptance_refresh.py
tests/runtime_neutral/test_scientific_visualization_latex_routing.py
tests/runtime_neutral/test_shell_entrypoint_compatibility.py
tests/runtime_neutral/test_simple_install_docs_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_simple_powershell_installer_wrappers.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_simplified_skill_routing_contract.py
tests/runtime_neutral/test_skill_authority_parity.py
tests/runtime_neutral/test_skill_candidate_execution_safety.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_structured_bounded_reentry_continuation.py
- Executable scriptline 1
Executable file - Access to secretsline 55
[Credential-related source omitted] - Access to secretsline 251
[Credential-related source omitted] - Access to secretsline 283
[Credential-related source omitted] - Access to secretsline 301
[Credential-related source omitted] - Access to secretsline 467
[Credential-related source omitted] - Access to secretsline 541
[Credential-related source omitted]
tests/runtime_neutral/test_test_baseline_audit.py
- Executable scriptline 1
Executable file - Network accessline 169
path = Path(tempdir) / "tests" / "runtime_neutral" / "test_release.py" path.parent.mkdir(parents=True) path.write_text("def test_release():\n assert 'https://example.invalid'\n", encoding="utf-8") - Network accessline 171
path.write_text("def test_release():\n assert 'https://example.invalid'\n", encoding="utf-8")
tests/runtime_neutral/test_uninstall_vgo_adapter.py
tests/runtime_neutral/test_verify_docs_contract.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_vibe_routing_chaos_audit_fixture.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_vibe_upgrade_reminder.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_windows_setup_helpers.py
tests/runtime_neutral/test_windsurf_runtime_core.py
tests/runtime_neutral/test_workflow_acceptance_runner.py
- Executable scriptline 1
Executable file
tests/runtime_neutral/test_workspace_shared_memory_plane.py
tests/unit/test_adapter_registry_support.py
- Executable scriptline 1
Executable file
tests/unit/test_adapter_sdk.py
- Executable scriptline 1
Executable file
tests/unit/test_artifact_receipt_sync.py
- Executable scriptline 1
Executable file
tests/unit/test_canonical_entry_boundary.py
- Executable scriptline 1
Executable file
tests/unit/test_canonical_vibe_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_canonical_vibe_entry_launcher.py
- Executable scriptline 1
Executable file
tests/unit/test_codex_plugin_inventory.py
- Executable scriptline 1
Executable file - Network accessline 180
payload = {"name": "documents", "skills": f"./{export}/"} if manifest_path == "plugin.json": payload = {"name": "documents", "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json"} - Network accessline 181
if manifest_path == "plugin.json": payload = {"name": "documents", "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json"} overlay = plugin / ".codex-plugin/plugin.json" - Network accessline 182
payload = {"name": "documents", "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json"}
tests/unit/test_delegated_lane_contract.py
tests/unit/test_discoverable_entry_surface.py
- Executable scriptline 1
Executable file
tests/unit/test_discoverable_wrapper_task_fidelity.py
- Executable scriptline 1
Executable file
tests/unit/test_discoverable_wrappers.py
- Executable scriptline 1
Executable file
tests/unit/test_entry_root_guard.py
- Executable scriptline 1
Executable file
tests/unit/test_external_skill_catalog.py
- Executable scriptline 1
Executable file
tests/unit/test_external_skill_selection.py
- Executable scriptline 1
Executable file
tests/unit/test_gate_engine.py
- Executable scriptline 1
Executable file
tests/unit/test_global_instruction_merge.py
- Executable scriptline 1
Executable file
tests/unit/test_host_closure.py
- Executable scriptline 1
Executable file
tests/unit/test_host_launch_receipt.py
- Executable scriptline 1
Executable file
tests/unit/test_host_skill_roots.py
- Executable scriptline 1
Executable file
tests/unit/test_install_runtime_cleanup.py
- Executable scriptline 1
Executable file
tests/unit/test_installed_runtime_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_installer_adapter_registry_target_roots.py
- Executable scriptline 1
Executable file
tests/unit/test_installer_ledger_service.py
- Executable scriptline 1
Executable file
tests/unit/test_installer_opencode_guidance_payload.py
- Executable scriptline 1
Executable file
tests/unit/test_installer_profile_inventory.py
- Executable scriptline 1
Executable file
tests/unit/test_kernel_boundary_demotion_matrix.py
- Executable scriptline 1
Executable file
tests/unit/test_kernel_text_tokens.py
- Executable scriptline 1
Executable file
tests/unit/test_live_document_gate.py
- Executable scriptline 1
Executable file
tests/unit/test_live_governance_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_local_installed_skill_routing.py
- Executable scriptline 1
Executable file
tests/unit/test_local_kernel_execution.py
- Executable scriptline 1
Executable file
tests/unit/test_local_kernel_planning.py
- Executable scriptline 1
Executable file
tests/unit/test_local_kernel_resume.py
- Executable scriptline 1
Executable file
tests/unit/test_local_skill_index.py
- Executable scriptline 1
Executable file
tests/unit/test_materializer_path_safety.py
- Executable scriptline 1
Executable file
tests/unit/test_materializer_runtime_noise.py
- Executable scriptline 1
Executable file
tests/unit/test_mirror_topology_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_module_execution_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_powershell_process_tree.py
tests/unit/test_proof_publication.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_compatibility_exit.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_contracts_helper.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_entry_locator.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_entry_policy.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_grade_intent.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_packaging_resolver.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_planning.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_router.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_stage_machine.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_stage_stop.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_summary.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_support.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_surface_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_task_intent.py
- Executable scriptline 1
Executable file
tests/unit/test_runtime_truth.py
- Executable scriptline 1
Executable file
tests/unit/test_simple_skill_installer.py
tests/unit/test_skill_authority.py
- Executable scriptline 1
Executable file
tests/unit/test_skill_cache_routing.py
- Executable scriptline 1
Executable file
tests/unit/test_skill_resources.py
tests/unit/test_uninstall_service.py
- Executable scriptline 1
Executable file
tests/unit/test_verification_repo_root.py
- Executable scriptline 1
Executable file
tests/unit/test_verify_surface_default.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_commands.py
tests/unit/test_vgo_cli_core_bridge.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_external.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_infra_split.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_install_gates.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_install_support.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_installer_bridge.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_process.py
- Executable scriptline 1
Executable file
tests/unit/test_vgo_cli_repo.py
- Executable scriptline 1
Executable file - Network accessline 58
( '{"source_of_truth": {"canonical_root": ".", "official_self_repo": ' '{"repo_url": "https://example.com/Vibe-Skills.git", "default_branch": "main"}}}' - Network accessline 59
'{"source_of_truth": {"canonical_root": ".", "official_self_repo": ' '{"repo_url": "https://example.com/Vibe-Skills.git", "default_branch": "main"}}}' ), - Network accessline 60
'{"repo_url": "https://example.com/Vibe-Skills.git", "default_branch": "main"}}}' - Network accessline 67
assert payload == { 'repo_url': 'https://example.com/Vibe-Skills.git', - Network accessline 68
'repo_url': 'https://example.com/Vibe-Skills.git', - Network accessline 111
) -> subprocess.CompletedProcess[str]: if command == ['git', '-C', str(repo_root), 'config', '--get', 'remote.origin.url']: return subprocess.CompletedProcess(command, 0, stdout='https://github.com/foryourhealth111-pixel - Network accessline 112
if command == ['git', '-C', str(repo_root), 'config', '--get', 'remote.origin.url']: return subprocess.CompletedProcess(command, 0, stdout='https://github.com/foryourhealth111-pixel/Vibe-Skills.git\n', stderr='') if comm - Network accessline 113
return subprocess.CompletedProcess(command, 0, stdout='https://github.com/foryourhealth111-pixel/Vibe-Skills.git\n', stderr='') - Network accessline 122
assert payload == { 'repo_url': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', - Network accessline 123
'repo_url': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git',
tests/unit/test_vgo_cli_upgrade_service.py
- Executable scriptline 1
Executable file - Network accessline 88
"installed_version": "3.0.1", "installed_commit": "same", "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 89
"installed_commit": "same", "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 90
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 147
"host_id": "codex", "target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 148
"target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 149
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 160
"get_official_self_repo_metadata", lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 161
lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main", - Network accessline 162
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 241
"get_official_self_repo_metadata", lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 242
lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main", - Network accessline 243
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 315
"host_id": "codex", "target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 316
"target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 317
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 328
"get_official_self_repo_metadata", lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 329
lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main", - Network accessline 330
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 412
(installed_runtime / "config").mkdir(parents=True) (installed_runtime / "config" / "version-governance.json").write_text( '{"source_of_truth":{"official_self_repo":{"repo_url":"https://example.test/Vibe-Skills.git","default_bran - Network accessline 413
(installed_runtime / "config" / "version-governance.json").write_text( '{"source_of_truth":{"official_self_repo":{"repo_url":"https://example.test/Vibe-Skills.git","default_branch":"main"}}}\n', encoding="utf-8", - Network accessline 414
'{"source_of_truth":{"official_self_repo":{"repo_url":"https://example.test/Vibe-Skills.git","default_branch":"main"}}}\n', - Network accessline 441
"main", "--single-branch", "https://example.test/Vibe-Skills.git", - Network accessline 442
"--single-branch", "https://example.test/Vibe-Skills.git", str(target_root / ".vibeskills" / "upgrade-source"), - Network accessline 443
"https://example.test/Vibe-Skills.git", - Network accessline 472
"installed_version": "3.0.4", "installed_commit": "old-install", "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 473
"installed_commit": "old-install", "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 474
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 744
target_root, { "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 745
{ "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 746
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 755
assert status["remote_latest_version"] == "3.0.1" assert commands == [ ["git", "fetch", "--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "main"], - Network accessline 756
assert commands == [ ["git", "fetch", "--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "main"], ["git", "rev-parse", "FETCH_HEAD"], - Network accessline 757
["git", "fetch", "--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "main"], - Network accessline 776
"get_official_self_repo_metadata", lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 777
lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main", - Network accessline 778
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 790
"fetch", "--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 791
"--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "main", - Network accessline 792
"https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 825
"fetch", "--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 826
"--quiet", "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "main", - Network accessline 827
"https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 842
"host_id": "codex", "target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 843
"target_root": str(target_root.resolve()), "repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "repo_default_branch": "main", - Network accessline 844
"repo_remote": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 859
"get_official_self_repo_metadata", lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", - Network accessline 860
lambda repo_root_arg: { "repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git", "default_branch": "main", - Network accessline 861
"repo_url": "https://github.com/foryourhealth111-pixel/Vibe-Skills.git",
tests/unit/test_vgo_cli_upgrade_state.py
- Executable scriptline 1
Executable file - Network accessline 45
'host_id': 'codex', 'target_root': str(target_root.resolve()), 'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', - Network accessline 46
'target_root': str(target_root.resolve()), 'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', 'repo_default_branch': 'main', - Network accessline 47
'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', - Network accessline 61
'host_id': 'codex', 'target_root': target_root, 'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', - Network accessline 62
'target_root': target_root, 'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git', 'repo_default_branch': 'main', - Network accessline 63
'repo_remote': 'https://github.com/foryourhealth111-pixel/Vibe-Skills.git',
tests/unit/test_vgo_verify_repo.py
- Executable scriptline 1
Executable file
tests/unit/test_vibe_skill_entry_contract.py
- Executable scriptline 1
Executable file
tests/unit/test_vibe_task_prompt_fidelity_contract.py
- Executable scriptline 1
Executable file
uninstall.ps1
- Executable scriptline 1
Executable file
uninstall.sh
- Executable scriptline 1
#!/usr/bin/env bash
update.ps1
- Executable scriptline 1
Executable file
update.sh
- Executable scriptline 1
#!/usr/bin/env bash
vgo_cli/__init__.py
- Executable scriptline 1
Executable file
vgo_python_source_roots.py
- Executable scriptline 1
Executable file
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Declared and executed: 2 facts
- Allows Bash without restrictions, though it has no scripts or shell blocksLQF_Machine_Learning_Expert_Guide/SKILL.md:7High confidence
- Contacts www.w3.org, which SKILL.md, the README and the plugin manifest do not mentioncitation-management/scripts/extract_metadata.py:235High confidence
Signal confidence: 498 facts
- Network access in prose of documentationREADME.md:23Low confidence
- Network access in prose of documentationREADME.md:56Low confidence
- Network access in prose of documentationREADME.md:61Low confidence
- Network access in prose of documentationREADME.md:62Low confidence
- Network access in prose of documentationREADME.md:69Low confidence
- Network access in prose of documentationREADME.md:70Low confidence
- Network access in prose of documentationREADME.md:84Low confidence
- Network access in prose of documentationREADME.md:85Low confidence
- Network access in prose of documentationREADME.md:450Low confidence
- Network access in prose of documentationREADME.md:451Low confidence
- Network access in prose of documentationREADME.md:492Low confidence
- Network access in prose of documentationREADME.md:493Low confidence
- Network access in prose of documentationREADME.md:494Low confidence
- Network access in prose of documentationREADME.md:511Low confidence
- Network access in prose of documentationREADME.md:512Low confidence
- Network access in prose of documentationREADME.md:515Low confidence
- Network access in prose of documentationREADME.md:516Low confidence
- Network access in prose of documentationREADME.md:520Low confidence
- Network access in prose of documentationREADME.md:523Low confidence
- Network access in prose of documentationREADME.md:524Low confidence
- Network access in prose of documentationREADME.md:525Low confidence
- Network access in prose of documentationREADME.zh.md:23Low confidence
- Network access in prose of documentationREADME.zh.md:57Low confidence
- Network access in prose of documentationREADME.zh.md:61Low confidence
- Network access in prose of documentationREADME.zh.md:62Low confidence
- Network access in prose of documentationREADME.zh.md:69Low confidence
- Network access in prose of documentationREADME.zh.md:70Low confidence
- Network access in prose of documentationREADME.zh.md:79Low confidence
- Network access in prose of documentationREADME.zh.md:80Low confidence
- Network access in prose of documentationREADME.zh.md:427Low confidence
- Network access in prose of documentationREADME.zh.md:468Low confidence
- Network access in prose of documentationREADME.zh.md:469Low confidence
- Network access in prose of documentationREADME.zh.md:470Low confidence
- Network access in prose of documentationREADME.zh.md:487Low confidence
- Network access in prose of documentationREADME.zh.md:488Low confidence
- Network access in prose of documentationREADME.zh.md:491Low confidence
- Network access in prose of documentationREADME.zh.md:495Low confidence
- Network access in prose of documentationREADME.zh.md:496Low confidence
- Network access in prose of documentationREADME.zh.md:498Low confidence
- Network access in prose of documentationREADME.zh.md:499Low confidence
- Network access in prose of documentationREADME.zh.md:500Low confidence
- Executable script in code of a file that runs_python_source_roots.py:1High confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/__init__.py:1High confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/commands.py:1High confidence
- Network access in code of a file that runsapps/vgo-cli/src/vgo_cli/commands.py:25High confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/core_bridge.py:1High confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/errors.py:1High confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/external.py:1High confidence
- Access to secrets in code of a file that runs: a variable, placeholder or call, not a stored valueapps/vgo-cli/src/vgo_cli/external.py:12Low confidence
- Executable script in code of a file that runsapps/vgo-cli/src/vgo_cli/hosts.py:1High confidence
and 448 more
Only the first 500 facts are listed.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Frontmatter field user-invocable in bundled/skills/autonomous-builder/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Native | Manifest bundled/skills/claude-skills/AGENTS.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.
Explore alternatives and comparisons
Add this badge to your README
It updates every night and links to this page.
[](https://hotskills.dev/skill/foryourhealth111-pixel-vibe-skills/)