#842 by GitHub stars
NeuroAIHub/BrainPilot
BrainPilot: Automating Brain Discovery with Agentic Research
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
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/dispatching-parallel-agents/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/executing-plans/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/receiving-code-review/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/requesting-code-review/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/using-superpowers/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/verification-before-completion/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/writing-plans/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.0/skills/writing-skills/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/dispatching-parallel-agents/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/executing-plans/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/finishing-a-development-branch/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/receiving-code-review/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/requesting-code-review/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/systematic-debugging/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/test-driven-development/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/using-git-worktrees/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/using-superpowers/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/verification-before-completion/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-plans/SKILL.md
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packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-skills/SKILL.md
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packages/plugin-auditor/skills/audit-code-artifact/SKILL.md
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packages/plugin-auditor/skills/audit-data-integrity/SKILL.md
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packages/plugin-auditor/skills/audit-evidence/SKILL.md
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packages/plugin-auditor/skills/audit-feedback-loop/SKILL.md
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packages/plugin-auditor/skills/audit-model-validation/SKILL.md
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packages/plugin-got/skills/curate-research-trace/SKILL.md
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packages/plugin-research/skills/create-data-inventory/SKILL.md
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packages/plugin-research/skills/source-grounded-research-report/SKILL.md
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packages/skills/skills/01_Meta-Skills/contribute-skill/SKILL.md
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packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr/SKILL.md
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packages/skills/skills/01_Meta-Skills/paper-to-skill/SKILL.md
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packages/skills/skills/01_Meta-Skills/repo-to-skill/SKILL.md
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packages/skills/skills/01_Meta-Skills/share-case/SKILL.md
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packages/skills/skills/01_Meta-Skills/share-usage/SKILL.md
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packages/skills/skills/01_Meta-Skills/verify-skill/SKILL.md
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packages/skills/skills/01_Meta-Skills/workflow-skill-creator/SKILL.md
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packages/skills/skills/02_Cross-Domain_Foundation/cogsci-power-analysis/SKILL.md
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packages/skills/skills/02_Cross-Domain_Foundation/cogsci-statistics/SKILL.md
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packages/skills/skills/02_Cross-Domain_Foundation/cogsci-visualization/SKILL.md
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packages/skills/skills/02_Cross-Domain_Foundation/research-literacy/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/alternative-uses-task-designer/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/creativity-self-efficacy-mediation/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/divergent-thinking-scoring/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/drift-diffusion-model/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/evidence-accumulation-selector/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/signal-detection-analysis/SKILL.md
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packages/skills/skills/03_Cognitive_Psychology/visual-search-array-generator/SKILL.md
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packages/skills/skills/04_Psycholinguistics/reading-time-analysis/SKILL.md
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packages/skills/skills/04_Psycholinguistics/self-paced-reading-designer/SKILL.md
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packages/skills/skills/04_Psycholinguistics/sentence-stimulus-norming/SKILL.md
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packages/skills/skills/05_EEG_ERP/eeg-paradigm-designer/SKILL.md
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packages/skills/skills/05_EEG_ERP/eeg-preprocessing-pipeline-guide/SKILL.md
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packages/skills/skills/05_EEG_ERP/erp-analysis/SKILL.md
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packages/skills/skills/05_EEG_ERP/mne-python-guide/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/brain-connectivity-modeler/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/fmri-glm-analysis-guide/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/fmri-preprocessing-pipeline-guide/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/fmri-task-design-guide/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/netneurotools-guide/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/neural-decoding-analysis/SKILL.md
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packages/skills/skills/06_fMRI_Neuroimaging/pycortex-guide/SKILL.md
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packages/skills/skills/07_Computational_Modeling/act-r-model-builder/SKILL.md
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packages/skills/skills/07_Computational_Modeling/bayesian-cognitive-model-builder/SKILL.md
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packages/skills/skills/07_Computational_Modeling/parameter-recovery-checker/SKILL.md
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packages/skills/skills/08_Computational_Neuroscience/brain-connectivity-modeler/SKILL.md
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packages/skills/skills/08_Computational_Neuroscience/neural-decoding-analysis/SKILL.md
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packages/skills/skills/08_Computational_Neuroscience/neural-population-analysis-guide/SKILL.md
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packages/skills/skills/08_Computational_Neuroscience/spiking-network-model-builder/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/calcium-imaging-analysis-guide/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/gtex-database/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/human-protein-atlas-database/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/optogenetics-protocol-designer/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/SKILL.md
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packages/skills/skills/09_Cellular_Molecular_Neuroscience/pymol/SKILL.md
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packages/skills/skills/10_Clinical_Neuropsychology/lesion-symptom-mapping-guide/SKILL.md
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packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector/SKILL.md
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packages/skills/skills/11_Developmental_Cognition/infant-looking-time-designer/SKILL.md
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packages/skills/skills/12_Social_Cognition/tom-task-selector/SKILL.md
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packages/skills/skills/13_Visualization/nature-figure/SKILL.md
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packages/skills/skills/14_Writing/markdown-report-writing/SKILL.md
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packages/skills/skills/15_Others/neuroimaging-power-guide/SKILL.md
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packages/skills/skills/15_Others/neuroimaging-sample-size-calculator/SKILL.md
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packages/skills/skills/16_Animal_Behavior/deeplabcut/SKILL.md
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packages/skills/skills/17_Literature_Databases/literature-search-arxiv/SKILL.md
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packages/skills/skills/17_Literature_Databases/literature-search-biorxiv/SKILL.md
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packages/skills/skills/17_Literature_Databases/literature-search-europepmc/SKILL.md
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packages/skills/skills/17_Literature_Databases/literature-search-openalex/SKILL.md
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packages/skills/skills/17_Literature_Databases/pubmed-database/SKILL.md
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packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/SKILL.md
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packages/skills/skills/18_Genetics_Genomics/clinvar-database/SKILL.md
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packages/skills/skills/18_Genetics_Genomics/dbsnp-database/SKILL.md
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packages/skills/skills/18_Genetics_Genomics/gnomad-database/SKILL.md
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packages/skills/skills/19_Pharmacology/chembl-database/SKILL.md
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packages/skills/skills/19_Pharmacology/clinical-trials-database/SKILL.md
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packages/skills/skills/19_Pharmacology/openfda-database/SKILL.md
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packages/skills/skills/19_Pharmacology/opentargets-database/SKILL.md
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packages/skills/skills/19_Pharmacology/pubchem-database/SKILL.md
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packages/skills/skills/20_Infrastructure/uv/SKILL.md
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packages/skills/skills/21_Electrophysiology/spikeinterface-skill/SKILL.md
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1.1kGitHub stars
3stars in 7 days
110skills in this repository
0commits in 30 days
Heat
3.9- Star growth, last 7 daysAhead of 61% of tracked repositories
- Star growth, last 24 hoursAhead of 71% of tracked repositories
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Individual skills in this repository
- brainstorming
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming - dispatching-parallel-agents
packages/backend-core/plugins/superpowers/6.2.0/skills/dispatching-parallel-agents - executing-plans
packages/backend-core/plugins/superpowers/6.2.0/skills/executing-plans - finishing-a-development-branch
packages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch - receiving-code-review
packages/backend-core/plugins/superpowers/6.2.0/skills/receiving-code-review - requesting-code-review
packages/backend-core/plugins/superpowers/6.2.0/skills/requesting-code-review - subagent-driven-development
packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development - systematic-debugging
packages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging - test-driven-development
packages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development - using-git-worktrees
packages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees - using-superpowers
packages/backend-core/plugins/superpowers/6.2.0/skills/using-superpowers - verification-before-completion
packages/backend-core/plugins/superpowers/6.2.0/skills/verification-before-completion - writing-plans
packages/backend-core/plugins/superpowers/6.2.0/skills/writing-plans - writing-skills
packages/backend-core/plugins/superpowers/6.2.0/skills/writing-skills - brainstorming
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming - dispatching-parallel-agents
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/dispatching-parallel-agents - executing-plans
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/executing-plans - finishing-a-development-branch
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/finishing-a-development-branch - receiving-code-review
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/receiving-code-review - requesting-code-review
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/requesting-code-review - subagent-driven-development
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development - systematic-debugging
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/systematic-debugging - test-driven-development
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/test-driven-development - using-git-worktrees
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/using-git-worktrees - using-superpowers
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/using-superpowers - verification-before-completion
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/verification-before-completion - writing-plans
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-plans - writing-skills
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-skills - audit-code-artifact
packages/plugin-auditor/skills/audit-code-artifact - audit-data-integrity
packages/plugin-auditor/skills/audit-data-integrity - audit-evidence
packages/plugin-auditor/skills/audit-evidence - audit-feedback-loop
packages/plugin-auditor/skills/audit-feedback-loop - audit-model-validation
packages/plugin-auditor/skills/audit-model-validation - curate-research-trace
packages/plugin-got/skills/curate-research-trace - create-data-inventory
packages/plugin-research/skills/create-data-inventory - source-grounded-research-report
packages/plugin-research/skills/source-grounded-research-report - contribute-skill
packages/skills/skills/01_Meta-Skills/contribute-skill - contribute-skills-via-pr
packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr - paper-to-skill
packages/skills/skills/01_Meta-Skills/paper-to-skill - repo-to-skill
packages/skills/skills/01_Meta-Skills/repo-to-skill - share-case
packages/skills/skills/01_Meta-Skills/share-case - share-usage
packages/skills/skills/01_Meta-Skills/share-usage - verify-skill
packages/skills/skills/01_Meta-Skills/verify-skill - workflow-skill-creator
packages/skills/skills/01_Meta-Skills/workflow-skill-creator - cogsci-power-analysis
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-power-analysis - cogsci-statistics
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-statistics - cogsci-visualization
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-visualization - research-literacy
packages/skills/skills/02_Cross-Domain_Foundation/research-literacy - alternative-uses-task-designer
packages/skills/skills/03_Cognitive_Psychology/alternative-uses-task-designer - cognitive-paradigm-design
packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design - creativity-self-efficacy-mediation
packages/skills/skills/03_Cognitive_Psychology/creativity-self-efficacy-mediation - divergent-thinking-scoring
packages/skills/skills/03_Cognitive_Psychology/divergent-thinking-scoring - drift-diffusion-model
packages/skills/skills/03_Cognitive_Psychology/drift-diffusion-model - evidence-accumulation-selector
packages/skills/skills/03_Cognitive_Psychology/evidence-accumulation-selector - signal-detection-analysis
packages/skills/skills/03_Cognitive_Psychology/signal-detection-analysis - visual-search-array-generator
packages/skills/skills/03_Cognitive_Psychology/visual-search-array-generator - reading-time-analysis
packages/skills/skills/04_Psycholinguistics/reading-time-analysis - self-paced-reading-designer
packages/skills/skills/04_Psycholinguistics/self-paced-reading-designer - sentence-stimulus-norming
packages/skills/skills/04_Psycholinguistics/sentence-stimulus-norming - eeg-paradigm-designer
packages/skills/skills/05_EEG_ERP/eeg-paradigm-designer - eeg-preprocessing-pipeline-guide
packages/skills/skills/05_EEG_ERP/eeg-preprocessing-pipeline-guide - erp-analysis
packages/skills/skills/05_EEG_ERP/erp-analysis - mne-python-guide
packages/skills/skills/05_EEG_ERP/mne-python-guide - brain-connectivity-modeler
packages/skills/skills/06_fMRI_Neuroimaging/brain-connectivity-modeler - fmri-glm-analysis-guide
packages/skills/skills/06_fMRI_Neuroimaging/fmri-glm-analysis-guide - fmri-preprocessing-pipeline-guide
packages/skills/skills/06_fMRI_Neuroimaging/fmri-preprocessing-pipeline-guide - fmri-task-design-guide
packages/skills/skills/06_fMRI_Neuroimaging/fmri-task-design-guide - fmriprep
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep - netneurotools-guide
packages/skills/skills/06_fMRI_Neuroimaging/netneurotools-guide - neural-decoding-analysis
packages/skills/skills/06_fMRI_Neuroimaging/neural-decoding-analysis - pycortex-guide
packages/skills/skills/06_fMRI_Neuroimaging/pycortex-guide - act-r-model-builder
packages/skills/skills/07_Computational_Modeling/act-r-model-builder - bayesian-cognitive-model-builder
packages/skills/skills/07_Computational_Modeling/bayesian-cognitive-model-builder - parameter-recovery-checker
packages/skills/skills/07_Computational_Modeling/parameter-recovery-checker - brain-connectivity-modeler
packages/skills/skills/08_Computational_Neuroscience/brain-connectivity-modeler - neural-decoding-analysis
packages/skills/skills/08_Computational_Neuroscience/neural-decoding-analysis - neural-population-analysis-guide
packages/skills/skills/08_Computational_Neuroscience/neural-population-analysis-guide - spiking-network-model-builder
packages/skills/skills/08_Computational_Neuroscience/spiking-network-model-builder - alphafold-database-fetch-and-analyze
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze - calcium-imaging-analysis-guide
packages/skills/skills/09_Cellular_Molecular_Neuroscience/calcium-imaging-analysis-guide - gtex-database
packages/skills/skills/09_Cellular_Molecular_Neuroscience/gtex-database - human-protein-atlas-database
packages/skills/skills/09_Cellular_Molecular_Neuroscience/human-protein-atlas-database - optogenetics-protocol-designer
packages/skills/skills/09_Cellular_Molecular_Neuroscience/optogenetics-protocol-designer - pdb-database
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database - pymol
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pymol - lesion-symptom-mapping-guide
packages/skills/skills/10_Clinical_Neuropsychology/lesion-symptom-mapping-guide - neuropsych-battery-selector
packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector - infant-looking-time-designer
packages/skills/skills/11_Developmental_Cognition/infant-looking-time-designer - tom-task-selector
packages/skills/skills/12_Social_Cognition/tom-task-selector - nature-figure
packages/skills/skills/13_Visualization/nature-figure - markdown-report-writing
packages/skills/skills/14_Writing/markdown-report-writing - neuroimaging-power-guide
packages/skills/skills/15_Others/neuroimaging-power-guide - neuroimaging-sample-size-calculator
packages/skills/skills/15_Others/neuroimaging-sample-size-calculator - deeplabcut
packages/skills/skills/16_Animal_Behavior/deeplabcut - literature-search-arxiv
packages/skills/skills/17_Literature_Databases/literature-search-arxiv - literature-search-biorxiv
packages/skills/skills/17_Literature_Databases/literature-search-biorxiv - literature-search-europepmc
packages/skills/skills/17_Literature_Databases/literature-search-europepmc - literature-search-openalex
packages/skills/skills/17_Literature_Databases/literature-search-openalex - pubmed-database
packages/skills/skills/17_Literature_Databases/pubmed-database - alphagenome-single-variant-analysis
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis - clinvar-database
packages/skills/skills/18_Genetics_Genomics/clinvar-database - dbsnp-database
packages/skills/skills/18_Genetics_Genomics/dbsnp-database - gnomad-database
packages/skills/skills/18_Genetics_Genomics/gnomad-database - chembl-database
packages/skills/skills/19_Pharmacology/chembl-database - clinical-trials-database
packages/skills/skills/19_Pharmacology/clinical-trials-database - openfda-database
packages/skills/skills/19_Pharmacology/openfda-database - opentargets-database
packages/skills/skills/19_Pharmacology/opentargets-database - pubchem-database
packages/skills/skills/19_Pharmacology/pubchem-database - uv
packages/skills/skills/20_Infrastructure/uv - spikeinterface-skill
packages/skills/skills/21_Electrophysiology/spikeinterface-skill
How it works
brainstorming
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
2,136 tokensWhen the skill is activated
Reference documents
3,527 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Anti-Pattern: "This Is Too Simple To Need A Design"
- Checklist
- Process Flow
- The Process
- After the Design
- Visual Companion
Scripts executed separately
scripts/helper.jsscripts/server.cjsscripts/start-server.shscripts/stop-server.sh
Files
SKILL.mdcore10,047 bytesscripts/frame-template.htmlasset8,094 bytesscripts/helper.jsruns5,615 bytesscripts/server.cjsruns25,693 bytesscripts/start-server.shruns6,908 bytesscripts/stop-server.shruns3,263 bytesspec-document-reviewer-prompt.mddoc1,747 bytesvisual-companion.mddoc13,298 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdispatching-parallel-agents
When your agent uses it
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
1,363 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
- The Pattern
- Agent Prompt Structure
- Common Mistakes
- When NOT to Use
- Real Example from Session
- Verification
Files
SKILL.mdcore6,078 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubexecuting-plans
When your agent uses it
Use when you have a written implementation plan to execute in a separate session with review checkpoints
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
503 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
- The Process
- When to Stop and Ask for Help
- When to Revisit Earlier Steps
- Remember
Files
SKILL.mdcore2,305 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfinishing-a-development-branch
When your agent uses it
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
1,741 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
- Step 1: Verify Tests
- Step 2: Detect Environment
- Step 3: Determine Base Branch
- Step 4: Present Options
- Step 5: Execute Choice
- Step 6: Cleanup Workspace
- Quick Reference
- Common Rationalizations
Files
SKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubreceiving-code-review
When your agent uses it
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,459 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
- Overview
- 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
Files
SKILL.mdcore6,203 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubrequesting-code-review
When your agent uses it
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
680 tokensWhen the skill is activated
Reference documents
1,177 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Request Review
- How to Request
- Example
- Common Rationalizations
- Red Flags
Files
SKILL.mdcore2,956 bytesSKILL.mdcore2,956 bytescode-reviewer.mddoc5,213 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsubagent-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
6,513 tokensWhen the skill is activated
Reference documents
5,190 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- The Process
- Setup
- Model Selection
- The Task Loop
- Final Review
- Finish
- Common Rationalizations
- Example Workflow
Scripts executed separately
scripts/review-packagescripts/sdd-workspacescripts/task-brief
Files
../requesting-code-review/code-reviewer.mddoc5,213 bytesSKILL.mdcore28,077 bytesSKILL.mdcore28,077 bytesimplementer-prompt.mddoc5,717 bytesre-review-prompt.mddoc4,300 bytesscripts/review-packageruns1,469 bytesscripts/sdd-workspaceruns1,586 bytesscripts/task-briefruns1,158 bytestask-reviewer-prompt.mddoc7,816 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsystematic-debugging
When your agent uses it
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
What it loads into context
Frontmatter
24 tokensAlways available to the agent
SKILL.md
2,183 tokensWhen the skill is activated
Reference documents
5,727 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
- 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
Scripts executed separately
condition-based-waiting-example.tsfind-polluter.sh
Files
CREATION-LOG.mddoc4,257 bytesSKILL.mdcore9,465 bytesSKILL.mdcore9,465 bytescondition-based-waiting-example.tsruns5,054 bytescondition-based-waiting.mddoc3,516 bytesdefense-in-depth.mddoc3,650 bytesfind-polluter.shruns1,986 bytesroot-cause-tracing.mddoc5,316 bytestest-academic.mddoc653 bytestest-pressure-1.mddoc1,900 bytestest-pressure-2.mddoc2,283 bytestest-pressure-3.mddoc2,692 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubtest-driven-development
When your agent uses it
Use when implementing any feature or bugfix, before writing implementation code
What it loads into context
Frontmatter
21 tokensAlways available to the agent
SKILL.md
2,211 tokensWhen the skill is activated
Reference documents
1,779 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use
- The Iron Law
- Red-Green-Refactor
- Good Tests
- Common Rationalizations
- Red Flags - STOP and Start Over
- Example: Bug Fix
- Verification Checklist
- When Stuck
- Debugging Integration
- Final Rule
Files
SKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 byteswriting-good-tests.mddoc8,268 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubusing-git-worktrees
When your agent uses it
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
1,623 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
- Step 0: Detect Existing Isolation
- Step 1: Create Isolated Workspace
- Step 2: Project Setup
- Step 3: Verify Clean Baseline
- Quick Reference
- Common Rationalizations
Files
SKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubusing-superpowers
When your agent uses it
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
701 tokensWhen the skill is activated
Reference documents
2,135 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The Rule
- Skill Priority
- Red Flags
- Platform Adaptation
- User Instructions
Files
SKILL.mdcore3,063 bytesreferences/antigravity-tools.mddoc1,495 bytesreferences/codex-tools.mddoc1,774 bytesreferences/gemini-tools.mddoc4,598 bytesreferences/pi-tools.mddoc1,242 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubverification-before-completion
When your agent uses it
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
854 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
- The Iron Law
- The Gate Function
- Common Failures
- Red Flags - STOP
- Rationalization Prevention
- Key Patterns
- When To Apply
Files
SKILL.mdcore3,646 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubwriting-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
1,560 tokensWhen the skill is activated
Reference documents
361 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Scope Check
- File Structure
- Task Right-Sizing
- Bite-Sized Task Granularity
- Plan Document Header
- Task Structure
- No Placeholders
- Self-Review
- Execution Handoff
Files
SKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesplan-document-reviewer-prompt.mddoc1,713 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubwriting-skills
When your agent uses it
Use when creating new skills, editing existing skills, or verifying skills work before deployment
What it loads into context
Frontmatter
24 tokensAlways available to the agent
SKILL.md
5,841 tokensWhen the skill is activated
Reference documents
18,009 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- What is a Skill?
- TDD Mapping for Skills
- When to Create a Skill
- Skill Types
- Directory Structure
- SKILL.md Structure
- Skill Discovery Optimization (SDO)
- Flowchart Usage
- Code Examples
- File Organization
- The Iron Law (Same as TDD)
- Testing All Skill Types
- Common Rationalizations for Skipping Testing
- Match the Form to the Failure
- Bulletproofing Skills Against Rationalization
- RED-GREEN-REFACTOR for Skills
- Anti-Patterns
- STOP: Before Moving to Next Skill
- Skill Creation Checklist (TDD Adapted)
- Discovery Workflow
Scripts executed separately
render-graphs.js
Files
../using-superpowers/references/codex-tools.mddoc1,774 bytes../using-superpowers/references/gemini-tools.mddoc4,598 bytesSKILL.mdcore26,360 bytesSKILL.mdcore26,360 bytesSKILL.mdcore26,360 bytesanthropic-best-practices.mddoc46,197 bytesexamples/CLAUDE_MD_TESTING.mddoc5,423 bytesgraphviz-conventions.dotasset5,970 bytespersuasion-principles.mddoc5,901 bytesrender-graphs.jsruns4,857 bytestesting-skills-with-subagents.mddoc12,558 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubbrainstorming
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
2,136 tokensWhen the skill is activated
Reference documents
3,527 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Anti-Pattern: "This Is Too Simple To Need A Design"
- Checklist
- Process Flow
- The Process
- After the Design
- Visual Companion
Scripts executed separately
scripts/helper.jsscripts/server.cjsscripts/start-server.shscripts/stop-server.sh
Files
SKILL.mdcore10,047 bytesscripts/frame-template.htmlasset8,094 bytesscripts/helper.jsruns5,615 bytesscripts/server.cjsruns25,693 bytesscripts/start-server.shruns6,908 bytesscripts/stop-server.shruns3,263 bytesspec-document-reviewer-prompt.mddoc1,747 bytesvisual-companion.mddoc13,298 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdispatching-parallel-agents
When your agent uses it
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
1,363 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
- The Pattern
- Agent Prompt Structure
- Common Mistakes
- When NOT to Use
- Real Example from Session
- Verification
Files
SKILL.mdcore6,078 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubexecuting-plans
When your agent uses it
Use when you have a written implementation plan to execute in a separate session with review checkpoints
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
503 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
- The Process
- When to Stop and Ask for Help
- When to Revisit Earlier Steps
- Remember
Files
SKILL.mdcore2,305 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfinishing-a-development-branch
When your agent uses it
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
1,741 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
- Step 1: Verify Tests
- Step 2: Detect Environment
- Step 3: Determine Base Branch
- Step 4: Present Options
- Step 5: Execute Choice
- Step 6: Cleanup Workspace
- Quick Reference
- Common Rationalizations
Files
SKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytesSKILL.mdcore7,022 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubreceiving-code-review
When your agent uses it
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,459 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
- Overview
- 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
Files
SKILL.mdcore6,203 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubrequesting-code-review
When your agent uses it
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
680 tokensWhen the skill is activated
Reference documents
1,177 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Request Review
- How to Request
- Example
- Common Rationalizations
- Red Flags
Files
SKILL.mdcore2,956 bytesSKILL.mdcore2,956 bytescode-reviewer.mddoc5,213 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsubagent-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
6,513 tokensWhen the skill is activated
Reference documents
5,190 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- The Process
- Setup
- Model Selection
- The Task Loop
- Final Review
- Finish
- Common Rationalizations
- Example Workflow
Scripts executed separately
scripts/review-packagescripts/sdd-workspacescripts/task-brief
Files
../requesting-code-review/code-reviewer.mddoc5,213 bytesSKILL.mdcore28,077 bytesSKILL.mdcore28,077 bytesimplementer-prompt.mddoc5,717 bytesre-review-prompt.mddoc4,300 bytesscripts/review-packageruns1,469 bytesscripts/sdd-workspaceruns1,586 bytesscripts/task-briefruns1,158 bytestask-reviewer-prompt.mddoc7,816 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsystematic-debugging
When your agent uses it
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
What it loads into context
Frontmatter
24 tokensAlways available to the agent
SKILL.md
2,183 tokensWhen the skill is activated
Reference documents
5,727 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
- 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
Scripts executed separately
condition-based-waiting-example.tsfind-polluter.sh
Files
CREATION-LOG.mddoc4,257 bytesSKILL.mdcore9,465 bytesSKILL.mdcore9,465 bytescondition-based-waiting-example.tsruns5,054 bytescondition-based-waiting.mddoc3,516 bytesdefense-in-depth.mddoc3,650 bytesfind-polluter.shruns1,986 bytesroot-cause-tracing.mddoc5,316 bytestest-academic.mddoc653 bytestest-pressure-1.mddoc1,900 bytestest-pressure-2.mddoc2,283 bytestest-pressure-3.mddoc2,692 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubtest-driven-development
When your agent uses it
Use when implementing any feature or bugfix, before writing implementation code
What it loads into context
Frontmatter
21 tokensAlways available to the agent
SKILL.md
2,211 tokensWhen the skill is activated
Reference documents
1,779 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use
- The Iron Law
- Red-Green-Refactor
- Good Tests
- Common Rationalizations
- Red Flags - STOP and Start Over
- Example: Bug Fix
- Verification Checklist
- When Stuck
- Debugging Integration
- Final Rule
Files
SKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 bytesSKILL.mdcore9,015 byteswriting-good-tests.mddoc8,268 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubusing-git-worktrees
When your agent uses it
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
1,623 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
- Step 0: Detect Existing Isolation
- Step 1: Create Isolated Workspace
- Step 2: Project Setup
- Step 3: Verify Clean Baseline
- Quick Reference
- Common Rationalizations
Files
SKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytesSKILL.mdcore6,813 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubusing-superpowers
When your agent uses it
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
701 tokensWhen the skill is activated
Reference documents
2,135 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The Rule
- Skill Priority
- Red Flags
- Platform Adaptation
- User Instructions
Files
SKILL.mdcore3,063 bytesreferences/antigravity-tools.mddoc1,495 bytesreferences/codex-tools.mddoc1,774 bytesreferences/gemini-tools.mddoc4,598 bytesreferences/pi-tools.mddoc1,242 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubverification-before-completion
When your agent uses it
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
854 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
- The Iron Law
- The Gate Function
- Common Failures
- Red Flags - STOP
- Rationalization Prevention
- Key Patterns
- When To Apply
Files
SKILL.mdcore3,646 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubwriting-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
1,560 tokensWhen the skill is activated
Reference documents
361 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Scope Check
- File Structure
- Task Right-Sizing
- Bite-Sized Task Granularity
- Plan Document Header
- Task Structure
- No Placeholders
- Self-Review
- Execution Handoff
Files
SKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesSKILL.mdcore6,907 bytesplan-document-reviewer-prompt.mddoc1,713 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubwriting-skills
When your agent uses it
Use when creating new skills, editing existing skills, or verifying skills work before deployment
What it loads into context
Frontmatter
24 tokensAlways available to the agent
SKILL.md
5,841 tokensWhen the skill is activated
Reference documents
18,009 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- What is a Skill?
- TDD Mapping for Skills
- When to Create a Skill
- Skill Types
- Directory Structure
- SKILL.md Structure
- Skill Discovery Optimization (SDO)
- Flowchart Usage
- Code Examples
- File Organization
- The Iron Law (Same as TDD)
- Testing All Skill Types
- Common Rationalizations for Skipping Testing
- Match the Form to the Failure
- Bulletproofing Skills Against Rationalization
- RED-GREEN-REFACTOR for Skills
- Anti-Patterns
- STOP: Before Moving to Next Skill
- Skill Creation Checklist (TDD Adapted)
- Discovery Workflow
Scripts executed separately
render-graphs.js
Files
../using-superpowers/references/codex-tools.mddoc1,774 bytes../using-superpowers/references/gemini-tools.mddoc4,598 bytesSKILL.mdcore26,360 bytesSKILL.mdcore26,360 bytesSKILL.mdcore26,360 bytesanthropic-best-practices.mddoc46,197 bytesexamples/CLAUDE_MD_TESTING.mddoc5,423 bytesgraphviz-conventions.dotasset5,970 bytespersuasion-principles.mddoc5,901 bytesrender-graphs.jsruns4,857 bytestesting-skills-with-subagents.mddoc12,558 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubaudit-code-artifact
When your agent uses it
Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference. Use when claims depend on code, trained artifacts, evaluators, or deployable entry points.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
354 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
- Checks
Files
SKILL.mdcore1,906 bytesagents/openai.yamlasset226 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubaudit-data-integrity
When your agent uses it
Audit scientific data semantics, sample and label alignment, leakage, group splits, preprocessing boundaries, and train-to-inference transforms. Use for any result based on datasets, feature matrices, tensors, repeated observations, or learned preprocessing.
What it loads into context
Frontmatter
54 tokensAlways available to the agent
SKILL.md
348 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
- Checks
Files
SKILL.mdcore1,730 bytesSKILL.mdcore1,730 bytesagents/openai.yamlasset235 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubaudit-evidence
When your agent uses it
Audit numeric, artifact, log, citation, and cross-report claims against inspectable evidence. Use for reports, syntheses, benchmark claims, external citations, or conflicting Expert outputs.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
377 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
- Checks
Files
SKILL.mdcore1,893 bytesagents/openai.yamlasset232 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubaudit-feedback-loop
When your agent uses it
Coordinate iterative evidence and reliability reviews between BrainPilot's Principal Investigator and Auditor. Use when PI needs to audit its own draft, an Expert result, or a multi-agent synthesis; when Auditor receives such a review task; or when a previous audit requires correction and incremental re-review.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
395 tokensWhen the skill is activated
Reference documents
5,423 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Select the role procedure
- Load only the needed templates
- Specialist audit skills
Files
../audit-code-artifact/SKILL.mddoc1,906 bytes../audit-data-integrity/SKILL.mddoc1,730 bytes../audit-evidence/SKILL.mddoc1,893 bytesSKILL.mdcore1,865 bytesagents/openai.yamlasset220 bytesreferences/audit-request-template.mddoc1,839 bytesreferences/audit-response-template.mddoc2,139 bytesreferences/auditor-review.mddoc6,126 bytesreferences/pi-orchestration.mddoc2,477 bytesreferences/revision-loop.mddoc2,056 bytes../audit-model-validation/SKILL.mddoc6,843 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubaudit-model-validation
When your agent uses it
Audit whether method discovery, comparison, representative real-data validation, collapse diagnostics, pruning, and selection evidence support claims of suitability or superiority. Use for research-method selection, empirical evaluation, benchmarking, modelling, prediction, or other conclusions that depend on choosing among alternatives.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
1,288 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
- Separate operational and empirical evidence
- Checks
- Audit techniques
Files
SKILL.mdcore6,843 bytesagents/openai.yamlasset239 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcurate-research-trace
When your agent uses it
Curate BrainPilot Trace Events into human-readable research Episodes, appropriately granular nodes, and direct depends_on relationships. Use when a report contains multiple settings, results, analyses, visualizations, findings, or conclusions; when Episode placement is unclear; or when deciding whether new evidence should create parallel/sequential nodes or update an existing node.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
845 tokensWhen the skill is activated
Reference documents
715 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Curate one Trace Event
- Select an Episode
- Decide node boundaries
- Select direct parents
Files
SKILL.mdcore4,352 bytesSKILL.mdcore4,352 bytesSKILL.mdcore4,352 bytesSKILL.mdcore4,352 bytesSKILL.mdcore4,352 bytesSKILL.mdcore4,352 bytesagents/openai.yamlasset256 bytesreferences/examples.mddoc3,701 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcreate-data-inventory
When your agent uses it
Create or update the canonical Markdown inventory of task-relevant research data. Engineer must invoke this skill before creating or updating any data inventory, data contract, or dataset-coverage summary that downstream agents will use.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
441 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
Files
SKILL.mdcore2,315 bytesSKILL.mdcore2,315 bytesagents/openai.yamlasset241 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsource-grounded-research-report
When your agent uses it
Research a bounded factual, documentation, API, or literature question from authoritative sources and save a self-contained Markdown report with claim-level citations. Use for reading-heavy evidence gathering, not experiment execution or data analysis.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
383 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
Files
SKILL.mdcore2,010 bytesSKILL.mdcore2,010 bytesSKILL.mdcore2,010 bytesSKILL.mdcore2,010 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcontribute-skill
When your agent uses it
One-command skill contribution — generate a SKILL.md from your domain expertise and submit to GitHub Issues for maintainer review
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
2,182 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Prerequisites
- Interactive Flow
- Litmus Test Enforcement
Files
SKILL.mdcore9,288 bytesSKILL.mdcore9,288 bytesSKILL.mdcore9,288 bytesSKILL.mdcore9,288 bytesSKILL.mdcore9,288 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcontribute-skills-via-pr
When your agent uses it
Step-by-step guidance for contributing a new skill to the NeuroAIHub/awesome_cognitive_and_neuroscience_skills repository via GitHub Pull Request, including SKILL.md format requirements, quality rules, and PR checklist
What it loads into context
Frontmatter
92 tokensAlways available to the agent
SKILL.md
1,775 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- Verification Notice
- Step 1: Check for Overlap
- Step 2: Write the SKILL.md
- Step 3: Submit via Git PR
- Alternative: No-Git Contribution
- After Submission
Files
SKILL.mdcore7,413 bytesSKILL.mdcore7,413 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpaper-to-skill
When your agent uses it
Interactive skill that guides extraction of research paradigms and methodological techniques from cognitive science papers into structured, reusable skills
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
5,077 tokensWhen the skill is activated
Reference documents
5,154 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Trigger Conditions
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Interactive Workflow
- Extraction Depth Requirements
- Quality Checks Before Output
- Handling Ambiguity
- Multi-Skill Extraction
- Batch Extraction Mode
- Output Structure
- Example Interaction Summary
Files
SKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesSKILL.mdcore23,976 bytesreferences/extraction-guide.mddoc13,850 bytesreferences/skill-template.mddoc9,294 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubrepo-to-skill
When your agent uses it
Convert a GitHub repository or local codebase into a well-structured Claude Code skill with progressive disclosure. Use this skill whenever the user provides a GitHub URL or local repo path and asks to turn it into a skill, create a skill from a repo, or convert a library/tool/framework into reusable skill documentation. Also trigger when users say things like 'make a skill from this repo', 'turn this codebase into a skill', or 'I want a skill for [library name]'.
What it loads into context
Frontmatter
137 tokensAlways available to the agent
SKILL.md
2,327 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
- Purpose
- When to Use
- Workflow Overview
- Phase 1: Acquire the Repository
- Phase 2: Explore the Repository
- Phase 3: Design the Skill Structure
- Phase 4: Write the SKILL.md
- Phase 5: Write Reference Files
- Quality Checklist
- Example: Converting a Python Library
Files
SKILL.mdcore10,141 bytesSKILL.mdcore10,141 bytesSKILL.mdcore10,141 bytesSKILL.mdcore10,141 bytesSKILL.mdcore10,141 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubshare-case
When your agent uses it
One-command community case sharing — capture research context from your session and submit to GitHub Discussions
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,785 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Prerequisites
- Interactive Flow
- Case Format Template
- Privacy Principles
Files
SKILL.mdcore7,724 bytesSKILL.mdcore7,724 bytesSKILL.mdcore7,724 bytesSKILL.mdcore7,724 bytesSKILL.mdcore7,724 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubshare-usage
When your agent uses it
Generate and share anonymized skill usage statistics to help the community understand which skills are most valuable
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
3,005 tokensWhen the skill is activated
Reference documents
323 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- What Information Will Be Shared
- Privacy Notice
- How to Use
- Implementation Steps
- Example Report
- Important Notes
Files
README.mddoc1,328 bytesSKILL.mdcore12,668 bytesSKILL.mdcore12,668 bytesSKILL.mdcore12,668 bytesSKILL.mdcore12,668 bytesSKILL.mdcore12,668 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubverify-skill
When your agent uses it
Interactive skill verification — assess accuracy of parameters, citations, and methodology through structured expert review
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
2,898 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Prerequisites
- Interactive Flow (6 Phases)
- Verification Report Format
- Verification Depth Guidance
- Completion Checklist
Files
SKILL.mdcore12,939 bytesSKILL.mdcore12,939 bytesSKILL.mdcore12,939 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubworkflow-skill-creator
When your agent uses it
Distills a completed user workflow or interaction into a reusable agent skill. Use when the user asks to turn their workflow, interaction, or multi-step process into a skill, or when they say "make this a skill", "create a skill from what we just did", "package this workflow" or similar. Do not use for creating skills from scratch without an existing workflow (use a generic skill-creator for that).
What it loads into context
Frontmatter
104 tokensAlways available to the agent
SKILL.md
2,883 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
- Phase 1: Brainstorming (MANDATORY)
- Phase 2: Skill Design
- Phase 3: Implementation
- Phase 4: Validation
Scripts executed separately
references/cli_script_template.py
Files
SKILL.mdcore12,390 bytesreferences/cli_script_template.pyruns6,940 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcogsci-power-analysis
When your agent uses it
Domain-specific statistical power analysis guidance for cognitive and neuroscience research, encoding effect size priors and sample size recommendations by modality
What it loads into context
Frontmatter
123 tokensAlways available to the agent
SKILL.md
3,506 tokensWhen the skill is activated
Reference documents
18,419 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Workflow
- Common Pitfalls
- Quick Reference Decision Table
- References
Files
SKILL.mdcore13,444 bytesreferences/effect-sizes.mddoc31,185 bytesreferences/sample-size-guide.mddoc27,270 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcogsci-statistics
When your agent uses it
Domain-specific statistical modeling guidance for cognitive science and neuroscience, encoding when and how to apply mixed models, correction methods, Bayesian approaches, and effect size reporting
What it loads into context
Frontmatter
153 tokensAlways available to the agent
SKILL.md
5,547 tokensWhen the skill is activated
Reference documents
16,077 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Repeated-Measures ANOVA vs. Mixed-Effects Models
- Random Effects Structure
- Handling Reaction Time Data
- Multiple Comparison Correction
- Bayesian Alternatives
- Effect Size Reporting
- Common Statistical Mistakes in Cognitive Science
- Minimum Statistical Reporting Checklist
- References
Files
../cogsci-power-analysis/references/effect-sizes.mddoc31,185 bytesSKILL.mdcore21,356 bytesreferences/common-analyses.mddoc20,872 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcogsci-visualization
When your agent uses it
Domain-specific visualization best practices for cognitive and neuroscience data, encoding plot type selection, color standards, and publication formatting
What it loads into context
Frontmatter
125 tokensAlways available to the agent
SKILL.md
4,611 tokensWhen the skill is activated
Reference documents
7,124 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Plot Type Selection by Data Type
- ERP Visualization Conventions
- fMRI Visualization Standards
- Brain Connectivity Visualization
- Color Accessibility
- Publication Formatting Standards
- Common Visualization Mistakes in Cognitive Science
- Quick Reference Decision Table
- References
Files
SKILL.mdcore18,452 bytesSKILL.mdcore18,452 bytesreferences/plot-recipes.mddoc24,958 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubresearch-literacy
When your agent uses it
Core scientific methodology principles: research planning, method justification, assumption checking, and human-in-the-loop decision making for cognitive science and neuroscience
What it loads into context
Frontmatter
127 tokensAlways available to the agent
SKILL.md
4,055 tokensWhen the skill is activated
Reference documents
10,219 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- ⚠<U+FE0F> Verification Notice
- Research Question Formulation
- Method Selection Justification
- Expected Outcomes Declaration
- Assumptions and Limitations Awareness
- Human-in-the-Loop Principles
- Common Research Anti-Patterns
- The Planning Protocol
- Key References
Files
SKILL.mdcore17,977 bytesreferences/common-assumptions.mddoc31,001 bytesreferences/planning-template.mddoc6,603 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubalternative-uses-task-designer
When your agent uses it
Domain-validated guidance for designing Alternative Uses Task (AUT) experiments measuring divergent thinking, with parameters for AI-augmented and traditional conditions
What it loads into context
Frontmatter
123 tokensAlways available to the agent
SKILL.md
2,878 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- AUT Overview
- Condition Design
- Online Implementation
- Additional Measures
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore11,863 bytesreferences/instruction-templates.mddoc3,144 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcognitive-paradigm-design
When your agent uses it
Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions
What it loads into context
Frontmatter
147 tokensAlways available to the agent
SKILL.md
3,909 tokensWhen the skill is activated
Reference documents
14,348 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Workflow
- Quick Reference: Paradigm Selection Matrix
- Domain-Specific Warnings
- References
Files
SKILL.mdcore15,760 bytesreferences/classic-paradigms.mddoc36,133 bytesreferences/design-principles.mddoc16,990 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcreativity-self-efficacy-mediation
When your agent uses it
Domain-validated guidance for SEM-based mediation analysis of creative self-efficacy and moderation by baseline creativity in AI-augmented creativity research
What it loads into context
Frontmatter
118 tokensAlways available to the agent
SKILL.md
3,393 tokensWhen the skill is activated
Reference documents
1,264 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Theoretical Framework
- Measurement Instruments
- SEM Mediation Model Specification
- Moderation Analysis
- Moderated Mediation (Full Model)
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore14,002 bytesreferences/lavaan-templates.mddoc4,267 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdivergent-thinking-scoring
When your agent uses it
Domain-validated multi-dimensional scoring system for divergent thinking tasks, including fluency, flexibility, originality, and automated semantic distance methods
What it loads into context
Frontmatter
133 tokensAlways available to the agent
SKILL.md
3,355 tokensWhen the skill is activated
Reference documents
1,410 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Scoring Dimensions Overview
- Fluency Scoring
- Flexibility Scoring
- Originality Scoring
- Semantic Distance (Automated Scoring)
- Handling the Fluency-Originality Confound
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore13,974 bytesreferences/scoring-rubric.mddoc5,663 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdrift-diffusion-model
When your agent uses it
Expert guidance on selecting, fitting, and evaluating drift-diffusion models for two-choice response time data in cognitive science
What it loads into context
Frontmatter
132 tokensAlways available to the agent
SKILL.md
3,099 tokensWhen the skill is activated
Reference documents
16,235 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- When NOT to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Concepts
- Decision Logic: Choosing a Model Variant
- Fitting Workflow Summary
- Interpreting Parameters
- Common Pitfalls
- Key References
Files
SKILL.mdcore12,335 bytesreferences/fitting-guide.mddoc36,163 bytesreferences/model-variants.mddoc25,093 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubevidence-accumulation-selector
When your agent uses it
Advises on when to use DDM vs. LBA vs. race models for choice-RT data based on experimental design and research goals
What it loads into context
Frontmatter
148 tokensAlways available to the agent
SKILL.md
5,078 tokensWhen the skill is activated
Reference documents
1,597 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Concepts: What EAMs Do
- Decision Tree: Selecting a Model
- Model Descriptions
- Model Comparison Methods
- Parameter Recovery Check
- Software Recommendations
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore19,284 bytesreferences/ez-diffusion-formulas.mddoc4,734 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsignal-detection-analysis
When your agent uses it
Domain-validated decision logic, formulas, and interpretation guidelines for applying Signal Detection Theory to cognitive science data
What it loads into context
Frontmatter
125 tokensAlways available to the agent
SKILL.md
4,187 tokensWhen the skill is activated
Reference documents
8,383 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use SDT (Not Simple Accuracy)
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Concepts
- Decision Logic: Choosing a Sensitivity Measure
- Common Paradigms
- Handling Extreme Hit/False Alarm Rates
- The Unequal-Variance Problem
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore15,949 bytesreferences/application-guide.mddoc16,501 bytesreferences/sdt-formulas.mddoc12,570 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubvisual-search-array-generator
When your agent uses it
Specifies display parameters, set sizes, target-distractor similarity, and randomization constraints for visual search experiments
What it loads into context
Frontmatter
136 tokensAlways available to the agent
SKILL.md
4,517 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
- Purpose
- When to Use
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Search Type Classification
- Display Parameters
- Feature Dimensions and Similarity
- Target-Distractor Similarity and Distractor Heterogeneity
- Array Generation Algorithm
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore18,603 bytesreferences/array-generation-parameters.yamlasset4,148 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubreading-time-analysis
When your agent uses it
Guides analysis of eye-tracking reading measures including first fixation, gaze duration, regression path, and total reading time
What it loads into context
Frontmatter
132 tokensAlways available to the agent
SKILL.md
4,660 tokensWhen the skill is activated
Reference documents
2,781 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Eye-Tracking Reading Measures Hierarchy
- Region of Interest (ROI) Definition
- Data Cleaning
- Statistical Modeling
- Typical Fixation Duration Benchmarks
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore19,271 bytesreferences/measure-computation-guide.mddoc11,202 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubself-paced-reading-designer
When your agent uses it
Expert guidance for designing self-paced reading experiments: region segmentation, timing parameters, comprehension probes, and spillover analysis
What it loads into context
Frontmatter
142 tokensAlways available to the agent
SKILL.md
4,745 tokensWhen the skill is activated
Reference documents
8,023 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Why SPR Design Requires Domain Expertise
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Workflow
- Common Pitfalls
- Quick Reference: SPR Design Checklist
- References
Files
SKILL.mdcore20,681 bytesreferences/analysis-guide.mddoc19,374 bytesreferences/region-segmentation.mddoc13,472 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsentence-stimulus-norming
When your agent uses it
Specifies norming procedures for linguistic stimuli including cloze probability, plausibility ratings, acceptability judgments, and lexical controls
What it loads into context
Frontmatter
140 tokensAlways available to the agent
SKILL.md
5,616 tokensWhen the skill is activated
Reference documents
2,627 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Cloze Probability Norming
- Plausibility and Naturalness Ratings
- Acceptability Judgments
- Lexical Controls
- Latin Square Counterbalancing
- Filler Items
- Practice and Warm-Up Items
- Online Norming Considerations
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore23,406 bytesreferences/lexical-databases-guide.mddoc8,708 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubeeg-paradigm-designer
When your agent uses it
Expert guidance for designing EEG paradigms optimized to isolate specific ERP components, with domain-validated timing, trial count, and control condition parameters
What it loads into context
Frontmatter
168 tokensAlways available to the agent
SKILL.md
5,296 tokensWhen the skill is activated
Reference documents
13,119 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Core Design Workflow
- EEG-Specific Additions to Standard Paradigm Design
- References
Files
SKILL.mdcore19,990 bytesSKILL.mdcore19,990 bytesSKILL.mdcore19,990 bytesSKILL.mdcore19,990 bytesSKILL.mdcore19,990 bytesreferences/component-paradigm-map.mddoc25,265 bytesreferences/timing-parameters.mddoc18,828 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubeeg-preprocessing-pipeline-guide
When your agent uses it
Guides EEG preprocessing: filtering, artifact rejection (ICA/ASR), re-referencing, interpolation
What it loads into context
Frontmatter
190 tokensAlways available to the agent
SKILL.md
6,143 tokensWhen the skill is activated
Reference documents
2,477 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Standard Preprocessing Pipeline Order
- Step 1: Import and Inspect Raw Data
- Step 2: Remove Bad Channels
- Step 3: High-Pass Filtering
- Step 4: Line Noise Removal
- Step 5: Re-Referencing
- Step 6: ICA Decomposition and Artifact Removal
- Alternative: ASR (Artifact Subspace Reconstruction)
- Step 7: Interpolate Bad Channels
- Step 8: Epoch and Baseline Correct
- Step 9: Epoch Rejection by Amplitude Threshold
- Low-Pass Filtering (Optional, Post-Epoching)
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore23,484 bytesreferences/parameter-lookup-tables.mddoc7,911 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHuberp-analysis
When your agent uses it
Domain-validated pipeline and parameter guidance for event-related potential analysis, from preprocessing through statistical testing
What it loads into context
Frontmatter
107 tokensAlways available to the agent
SKILL.md
2,760 tokensWhen the skill is activated
Reference documents
21,823 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Preprocessing Pipeline Overview
- ERP Component Identification
- Statistical Analysis Strategy
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore11,150 bytesreferences/erp-components.mddoc36,148 bytesreferences/preprocessing-pipeline.mddoc19,953 bytesreferences/statistical-approaches.mddoc23,261 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmne-python-guide
When your agent uses it
Domain-validated pipeline guidance for EEG/MEG data analysis using MNE-Python: data loading, preprocessing (filtering, ICA, re-referencing), epoching, ERP/ERF computation, time-frequency decomposition, source localization, decoding/MVPA, statistical testing, simulation, and visualization. Use this skill whenever the user works with EEG/MEG/sEEG/ECoG/NIRS/eye-tracking data in Python, mentions MNE, or needs neurophysiological analysis guidance.
What it loads into context
Frontmatter
285 tokensAlways available to the agent
SKILL.md
2,504 tokensWhen the skill is activated
Reference documents
13,323 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- Verification Notice
- Reference Files (Progressive Disclosure)
- Pipeline Overview
- Core Data Structures
- Quick Start Pipeline
- Common Pitfalls
- References
Files
SKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesSKILL.mdcore9,283 bytesreferences/decoding.mddoc5,559 bytesreferences/io_formats.mddoc4,875 bytesreferences/preprocessing.mddoc7,690 bytesreferences/simulation.mddoc4,684 bytesreferences/source_localization.mddoc7,041 bytesreferences/statistics.mddoc5,977 bytesreferences/time_frequency.mddoc5,561 bytesreferences/visualization.mddoc5,716 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubbrain-connectivity-modeler
When your agent uses it
Advises on functional/effective connectivity methods: PPI, DCM, Granger causality, graph theory
What it loads into context
Frontmatter
185 tokensAlways available to the agent
SKILL.md
6,119 tokensWhen the skill is activated
Reference documents
1,970 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Functional vs. Effective Connectivity
- Method Selection Decision Tree
- Functional Connectivity Methods
- Psychophysiological Interactions (PPI)
- Dynamic Causal Modeling (DCM)
- Granger Causality
- Graph Theory for Brain Networks
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore24,167 bytesSKILL.mdcore24,167 bytesSKILL.mdcore24,167 bytesreferences/method-implementation-guide.mddoc7,647 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfmri-glm-analysis-guide
When your agent uses it
Domain-validated guidance for fMRI General Linear Model specification: HRF modeling, design matrix construction, contrast definition, confound regression, and statistical inference
What it loads into context
Frontmatter
160 tokensAlways available to the agent
SKILL.md
6,007 tokensWhen the skill is activated
Reference documents
8,019 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- First-Level Analysis Decision Tree
- Contrast Specification
- Second-Level Analysis (Group Inference)
- Multiple Comparison Correction
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore23,208 bytesSKILL.mdcore23,208 bytesSKILL.mdcore23,208 bytesreferences/design-matrix-guide.mddoc14,247 bytesreferences/statistical-inference.mddoc17,476 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfmri-preprocessing-pipeline-guide
When your agent uses it
Domain-validated guidance for fMRI preprocessing decisions: motion correction, slice timing, spatial normalization, smoothing, confound regression, and quality control
What it loads into context
Frontmatter
188 tokensAlways available to the agent
SKILL.md
4,800 tokensWhen the skill is activated
Reference documents
10,518 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Pipeline Order Decision Tree
- Core Preprocessing Steps
- Pipeline Variants by Analysis Type
- fMRIPrep as the Recommended Standard
- Common Pitfalls
- Key References
Files
SKILL.mdcore18,920 bytesSKILL.mdcore18,920 bytesreferences/quality-control.mddoc19,287 bytesreferences/step-by-step-pipeline.mddoc19,502 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfmri-task-design-guide
When your agent uses it
Guides fMRI task design: block vs. event-related vs. mixed; jittering; contrasts; power for BOLD detection
What it loads into context
Frontmatter
186 tokensAlways available to the agent
SKILL.md
4,345 tokensWhen the skill is activated
Reference documents
1,677 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Design Type Selection
- Block Design Parameters
- Event-Related Design Parameters
- Design Efficiency
- Mixed Design Specification
- Scanner-Related Timing Constraints
- Rest/Fixation Baseline
- Condition Ordering
- Behavioral Task Constraints
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore16,817 bytesreferences/design-optimization-examples.mddoc6,136 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubfmriprep
When your agent uses it
Preprocess task-based or resting-state fMRI data with fMRIPrep — a robust, BIDS-App preprocessing pipeline built on FSL, ANTs, FreeSurfer, AFNI, and Nilearn. Use this skill whenever the user asks to preprocess fMRI/BOLD data, run fMRIPrep on a BIDS dataset, set up Docker/Singularity/Apptainer containers for fMRIPrep, choose output spaces (MNI152NLin2009cAsym, fsaverage, fsLR/CIFTI), configure susceptibility distortion correction (SDC), extract or interpret the confounds table, resample to surface/grayordinates, cite fMRIPrep and its dependencies, or debug fMRIPrep crashes and hangs.
What it loads into context
Frontmatter
200 tokensAlways available to the agent
SKILL.md
4,682 tokensWhen the skill is activated
Reference documents
42,948 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Reference Files (Progressive Disclosure)
- What fMRIPrep Is
- Command-Line Structure (BIDS-App)
- Pipeline Overview
- Quick Start
- Key Concepts (cheat-sheet)
- Sensible Defaults
- Common Pitfalls
- What This Skill Does Not Cover
- Where to Get Help
- Verify Installation
Files
SKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesSKILL.mdcore17,613 bytesreferences/bids-filter.mddoc8,326 bytesreferences/citation.mddoc10,557 bytesreferences/cli-reference.mddoc14,252 bytesreferences/confounds.mddoc12,302 bytesreferences/installation.mddoc11,613 bytesreferences/outputs.mddoc12,623 bytesreferences/sdc-fieldmaps.mddoc9,484 bytesreferences/spaces.mddoc10,371 bytesreferences/troubleshooting-faq.mddoc14,989 bytesreferences/usage-examples.mddoc13,830 bytesreferences/versions-dependencies.mddoc9,691 bytesreferences/workflows.mddoc18,127 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubnetneurotools-guide
When your agent uses it
Domain-validated guidance for network neuroscience analysis using netneurotools: datasets, brain network metrics, connectivity consensus, modularity, spatial statistics, null models, and cortical surface visualization. Use this skill whenever the user works with brain connectivity matrices, connectomes, graph theory on brain networks, parcellated brain data (Schaefer, Cammoun, Desikan-Killiany), cortical surface templates (fsaverage, fsLR, CIVET, Conte69), network communication metrics, null model generation, spatial autocorrelation on brain maps, community detection in connectomes, or surface-based visualization with PyVista/PySurfer. Also trigger when the user mentions netneurotools, netneurolab, structure-function coupling, network neuroscience, brain graph analysis, or needs to fetch neuroimaging atlases and templates.
What it loads into context
Frontmatter
204 tokensAlways available to the agent
SKILL.md
2,600 tokensWhen the skill is activated
Reference documents
23,512 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Reference Files (Progressive Disclosure)
- Installation
- Overview Pipeline
- Quick Start
- Key Data Structures
- Core Modules Quick Reference
- Common Pitfalls
Files
SKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesSKILL.mdcore10,212 bytesreferences/datasets.mddoc11,876 bytesreferences/interface-plotting.mddoc14,378 bytesreferences/metrics.mddoc16,838 bytesreferences/networks.mddoc15,417 bytesreferences/spatial-modularity.mddoc13,023 bytesreferences/stats.mddoc12,151 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneural-decoding-analysis
When your agent uses it
Domain-validated methods and decision logic for neural decoding, RSA, temporal generalization, and encoding models in systems neuroscience
What it loads into context
Frontmatter
152 tokensAlways available to the agent
SKILL.md
4,631 tokensWhen the skill is activated
Reference documents
6,629 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- When to Use Decoding vs. Univariate Analysis
- Method Selection Decision Tree
- Cross-Validated Classification (MVPA)
- Representational Similarity Analysis (RSA)
- Temporal Generalization (EEG/MEG)
- Encoding Models
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore19,758 bytesreferences/decoding-methods.mddoc11,801 bytesreferences/rsa-guide.mddoc15,139 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpycortex-guide
When your agent uses it
Domain-validated guidance for cortical surface visualization and brain surface rendering of fMRI data using pycortex: data types (Volume, Vertex, Dataset), 2D cortical flatmaps, 3D WebGL brain viewers, volume-to-surface mapping, FreeSurfer/fMRIPrep integration, ROI management, and surface analysis. Use this skill whenever the user mentions pycortex, `import cortex`, cortical surfaces, brain flatmaps, WebGL brain viewers, cortical surface mapping, or wants to visualize neuroimaging data on the cortex, even if they don't explicitly name pycortex.
What it loads into context
Frontmatter
157 tokensAlways available to the agent
SKILL.md
1,663 tokensWhen the skill is activated
Reference documents
11,336 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Reference Files
- Installation
- Overview Pipeline
- Quick Start
- Key Data Types
- Key Visualization Functions
- Common Pitfalls
Files
SKILL.mdcore6,342 bytesSKILL.mdcore6,342 bytesSKILL.mdcore6,342 bytesreferences/database-subjects.mddoc4,625 bytesreferences/dataset-types.mddoc6,794 bytesreferences/freesurfer-fmriprep.mddoc4,718 bytesreferences/mapping-transforms.mddoc5,526 bytesreferences/mni-utils.mddoc4,852 bytesreferences/surface-analysis.mddoc5,538 bytesreferences/visualization.mddoc8,230 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubact-r-model-builder
When your agent uses it
Guides ACT-R cognitive model construction: chunk types, production rules, subsymbolic parameters, and model validation
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
3,746 tokensWhen the skill is activated
Reference documents
1,910 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- ACT-R Architecture Overview
- Building the Symbolic Model
- Subsymbolic Parameters
- Model Fitting Workflow
- Common Model Patterns
- Model Validation Checklist
- Software and Implementation
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore14,662 bytesSKILL.mdcore14,662 bytesreferences/model-patterns.mddoc7,644 bytesreferences/parameter-table.yamlasset6,207 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubbayesian-cognitive-model-builder
When your agent uses it
Domain-validated guidance for building hierarchical Bayesian cognitive models with Stan/PyMC: prior specification, model structure, MCMC diagnostics, and posterior predictive checks
What it loads into context
Frontmatter
164 tokensAlways available to the agent
SKILL.md
5,484 tokensWhen the skill is activated
Reference documents
9,381 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- When NOT to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Model Structure Decision Tree
- Prior Selection Principles
- Common Cognitive Models in Bayesian Framework
- MCMC Diagnostics
- Model Comparison
- Common Pitfalls
- Reporting Checklist
- Key References
Files
SKILL.mdcore22,303 bytesreferences/diagnostics-checklist.mddoc18,795 bytesreferences/prior-selection-guide.mddoc16,997 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubparameter-recovery-checker
When your agent uses it
Guides parameter recovery studies to validate model identifiability before trusting fitted parameter values
What it loads into context
Frontmatter
110 tokensAlways available to the agent
SKILL.md
3,576 tokensWhen the skill is activated
Reference documents
1,947 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Why Parameter Recovery Matters
- Step-by-Step Recovery Procedure
- Model Recovery (Confusion Matrix)
- Sample Size Effects
- Landscape Analysis
- Reporting Standards
- Common Pitfalls
- References
Files
SKILL.mdcore15,121 bytesreferences/recovery-diagnostics.mddoc7,809 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubbrain-connectivity-modeler
When your agent uses it
Advises on functional/effective connectivity methods: PPI, DCM, Granger causality, graph theory
What it loads into context
Frontmatter
185 tokensAlways available to the agent
SKILL.md
6,119 tokensWhen the skill is activated
Reference documents
1,970 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Functional vs. Effective Connectivity
- Method Selection Decision Tree
- Functional Connectivity Methods
- Psychophysiological Interactions (PPI)
- Dynamic Causal Modeling (DCM)
- Granger Causality
- Graph Theory for Brain Networks
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore24,167 bytesSKILL.mdcore24,167 bytesSKILL.mdcore24,167 bytesreferences/method-implementation-guide.mddoc7,647 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneural-decoding-analysis
When your agent uses it
Domain-validated methods and decision logic for neural decoding, RSA, temporal generalization, and encoding models in systems neuroscience
What it loads into context
Frontmatter
152 tokensAlways available to the agent
SKILL.md
4,631 tokensWhen the skill is activated
Reference documents
6,629 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- When to Use Decoding vs. Univariate Analysis
- Method Selection Decision Tree
- Cross-Validated Classification (MVPA)
- Representational Similarity Analysis (RSA)
- Temporal Generalization (EEG/MEG)
- Encoding Models
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore19,758 bytesreferences/decoding-methods.mddoc11,801 bytesreferences/rsa-guide.mddoc15,139 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneural-population-analysis-guide
When your agent uses it
Guides dimensionality reduction and latent-variable analysis of neural populations (PCA, GPFA, dPCA)
What it loads into context
Frontmatter
154 tokensAlways available to the agent
SKILL.md
4,081 tokensWhen the skill is activated
Reference documents
3,244 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- When to Use Population Analysis vs. Single-Neuron Analysis
- Method Selection Decision Tree
- PCA for Neural Data
- GPFA -- Gaussian Process Factor Analysis
- dPCA -- Demixed Principal Component Analysis
- Population Decoding
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore17,972 bytesreferences/data-requirements.mddoc4,329 bytesreferences/method-comparison.mddoc8,058 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubspiking-network-model-builder
When your agent uses it
Assists building spiking neural network simulations: neuron models, connectivity, plasticity rules
What it loads into context
Frontmatter
143 tokensAlways available to the agent
SKILL.md
5,669 tokensWhen the skill is activated
Reference documents
3,077 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Step 1: Select a Neuron Model
- Step 2: Configure Synapses
- Step 3: Configure Network Connectivity
- Step 4: Implement Plasticity Rules
- Step 5: Set Simulation Parameters
- Step 6: Validate the Model
- Simulator Selection
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore20,470 bytesreferences/hh-parameters.mddoc4,212 bytesreferences/network-regimes.mddoc5,293 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubalphafold-database-fetch-and-analyze
When your agent uses it
Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
1,110 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
- Overview
- Core Rules
- Utility Scripts
- Interpreting the Output
Scripts executed separately
scripts/analyze_pae.pyscripts/analyze_plddt.pyscripts/fetch_structure.py
Files
SKILL.mdcore4,760 bytesSKILL.mdcore4,760 bytesSKILL.mdcore4,760 bytesSKILL.mdcore4,760 bytesreferences/citation.bibasset10,493 bytesscripts/analyze_pae.pyruns6,223 bytesscripts/analyze_plddt.pyruns3,940 bytesscripts/fetch_structure.pyruns5,018 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubcalcium-imaging-analysis-guide
When your agent uses it
Domain-validated pipeline guidance for calcium imaging data analysis: motion correction, ROI extraction, neuropil correction, spike inference, and quality control
What it loads into context
Frontmatter
147 tokensAlways available to the agent
SKILL.md
4,411 tokensWhen the skill is activated
Reference documents
7,986 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Decision Tree: Which Pipeline for Your Modality
- Core Pipeline Steps
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore17,760 bytesSKILL.mdcore17,760 bytesreferences/indicator-parameters.mddoc17,013 bytesreferences/pipeline-details.mddoc12,464 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubgtex-database
When your agent uses it
Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
1,647 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
- When to Use
- Core Rules
- Command Selection Guide
- Quick Start
- Commands
- Typical Workflows
Scripts executed separately
scripts/gtex_cli.py
Files
SKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesSKILL.mdcore6,071 bytesreferences/citation.bibasset5,807 bytesscripts/gtex_cli.pyruns8,904 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubhuman-protein-atlas-database
When your agent uses it
Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,644 tokensWhen the skill is activated
Reference documents
1,498 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- When to Use
- Command Selection Guide
- Quick Start
- Commands
- Core Rules
- API Versioning
- Common Errors
Scripts executed separately
scripts/hpa_cli.py
Files
SKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesSKILL.mdcore6,439 bytesreferences/citation.bibasset2,768 bytesreferences/search-api.mddoc5,893 bytesscripts/hpa_cli.pyruns8,325 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHuboptogenetics-protocol-designer
When your agent uses it
Domain-validated decision logic for optogenetic stimulation parameter selection, including opsin choice, light delivery, pulse protocols, fiber placement, and control conditions
What it loads into context
Frontmatter
165 tokensAlways available to the agent
SKILL.md
4,473 tokensWhen the skill is activated
Reference documents
10,439 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Decision Tree: Research Question to Protocol
- Common Pitfalls and Domain-Specific Warnings
- Viral Vector Quick Reference
- Protocol Assembly Checklist
- Key References
Files
SKILL.mdcore16,311 bytesreferences/opsin-catalog.mddoc12,742 bytesreferences/stimulation-parameters.mddoc21,485 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpdb-database
When your agent uses it
Use when you want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands). Supports searching by sequence similarity, structure similarity, chemical and other attributes. Also use to get metadata about biomolecular structure experiments.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
2,305 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
- Core Rules
- Attribute-based search workflow
- Similarity-based search workflow
- Full text search workflow
- File download workflow
- Metadata query workflow
Scripts executed separately
scripts/download_coordinate_files.pyscripts/fetch_pdb_metadata.pyscripts/fetch_schema.pyscripts/search_pdb.py
Files
SKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesSKILL.mdcore8,891 bytesreferences/citation.bibasset878 bytesscripts/download_coordinate_files.pyruns3,245 bytesscripts/fetch_pdb_metadata.pyruns1,893 bytesscripts/fetch_schema.pyruns7,720 bytesscripts/search_pdb.pyruns5,634 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpymol
When your agent uses it
Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.
What it loads into context
Frontmatter
95 tokensAlways available to the agent
SKILL.md
1,537 tokensWhen the skill is activated
Reference documents
4,602 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Overview
- Setup (Agent Instructions)
- Core Rules
- Quick Start
- Common Recipes
- Interpreting Output
Files
SKILL.mdcore6,233 bytesSKILL.mdcore6,233 bytesSKILL.mdcore6,233 bytesSKILL.mdcore6,233 bytesreferences/PYMOL_REFERENCE.mddoc5,454 bytesreferences/RECIPES.mddoc10,842 bytesreferences/citation.bibasset143 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHublesion-symptom-mapping-guide
When your agent uses it
Advises on lesion-symptom mapping methods: VLSM, disconnection analysis, network lesion mapping
What it loads into context
Frontmatter
158 tokensAlways available to the agent
SKILL.md
5,291 tokensWhen the skill is activated
Reference documents
3,736 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Method Selection Decision Tree
- Lesion Segmentation
- Voxel-Based Lesion-Symptom Mapping (VLSM)
- Multivariate Lesion-Symptom Mapping
- Disconnection Analysis
- Network Lesion Mapping
- Common Confounds
- Software
- Common Pitfalls
- Minimum Reporting Checklist
- Key References
Files
SKILL.mdcore21,390 bytesreferences/disconnection-guide.mddoc8,122 bytesreferences/vlsm-pipeline.mddoc6,677 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneuropsych-battery-selector
When your agent uses it
Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles
What it loads into context
Frontmatter
123 tokensAlways available to the agent
SKILL.md
4,313 tokensWhen the skill is activated
Reference documents
10,847 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Step 1: Clarify the Referral Question
- Step 2: Identify Target Cognitive Domains
- Step 3: Assemble the Battery
- Step 4: Select Appropriate Norms
- Step 5: Address Common Pitfalls
- Step 6: Condition-Specific Battery Recommendations
- Quick Reference: Test-to-Domain Mapping
- Key References
Files
SKILL.mdcore16,091 bytesreferences/deficit-profiles.mddoc21,650 bytesreferences/test-catalog.mddoc20,880 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubinfant-looking-time-designer
When your agent uses it
Designs habituation and preferential-looking paradigms with age-appropriate timing parameters and exclusion criteria
What it loads into context
Frontmatter
117 tokensAlways available to the agent
SKILL.md
4,580 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
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Paradigm Selection Decision Tree
- Habituation Paradigm Design
- Preferential Looking Design
- Violation-of-Expectation (VoE) Design
- General Timing Parameters
- Exclusion Criteria
- Coding Reliability
- Online vs. In-Lab Testing
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore18,038 bytesreferences/age-parameters.yamlasset5,959 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubtom-task-selector
When your agent uses it
Selects Theory of Mind tasks matched to target population, age, and construct with psychometric guidance
What it loads into context
Frontmatter
109 tokensAlways available to the agent
SKILL.md
6,103 tokensWhen the skill is activated
Reference documents
3,635 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- ToM Construct Taxonomy
- Task Selection Decision Tree
- Key Tasks with Parameters
- Psychometric Considerations
- Confounds and Controls
- Task Combination Recommendations
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore22,640 bytesreferences/task-database.mddoc13,306 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubnature-figure
When your agent uses it
Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics. Also trigger on general academic-writing figure needs even without the word "Nature", such as making figures/plots for a paper, scientific/academic plotting, data visualization for a manuscript, and Chinese phrasings like 论文配图、学术写作配图、科研绘图、科研作图、画图、作图、出图、论文图表、可视化.
What it loads into context
Frontmatter
257 tokensAlways available to the agent
SKILL.md
1,136 tokensWhen the skill is activated
Reference documents
31,068 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing protocol
- Why this split
Scripts executed separately
assets/figures4papers/figure_CellSpliceNet/plot_ablation.pyassets/figures4papers/figure_CellSpliceNet/plot_comparison.pyassets/figures4papers/figure_Cflows/diffusion_swiss_roll.pyassets/figures4papers/figure_Cflows/plot_comparison_Ablation.pyassets/figures4papers/figure_Cflows/plot_comparison_GeneRegulatory.pyassets/figures4papers/figure_Cflows/plot_comparison_Trajectory.pyassets/figures4papers/figure_Dispersion/plot_idea.pyassets/figures4papers/figure_Dispersion/plot_illustration.pyassets/figures4papers/figure_FPGM/plot_freq_prior.pyassets/figures4papers/figure_ImmunoStruct/plot_bars.pyassets/figures4papers/figure_ImmunoStruct/raw_data.pyassets/figures4papers/figure_RNAGenScape/plot_comparison.pyassets/figures4papers/figure_RNAGenScape/plot_hole_manifold.pyassets/figures4papers/figure_RNAGenScape/plot_manifold.pyassets/figures4papers/figure_RNAGenScape/plot_sweep.pyassets/figures4papers/figure_VIGIL/plot_comparison_radar.pyassets/figures4papers/figure_VIGIL/plot_posttraining.pyassets/figures4papers/figure_brainteaser/plot_brute_force.pyassets/figures4papers/figure_brainteaser/plot_correctness_by_category.pyassets/figures4papers/figure_brainteaser/plot_correctness_by_subcategory.pyassets/figures4papers/figure_brainteaser/plot_rewriting.pyassets/figures4papers/figure_brainteaser/plot_selfcorrection_math.pyassets/figures4papers/figure_ophthal_review/plot_composition.pyassets/figures4papers/figure_ophthal_review/plot_trend.py
Files
.gitignoreasset10 bytesREADME.mddoc21,447 bytesSKILL.mdcore5,244 bytesassets/chart-atlas/atlas-01-bar-charts.pngasset125,370 bytesassets/chart-atlas/atlas-02-line-trends.pngasset423,651 bytesassets/chart-atlas/atlas-03-heatmaps.pngasset159,834 bytesassets/chart-atlas/atlas-04-scatter-bubble.pngasset485,091 bytesassets/chart-atlas/atlas-05-radar-polar.pngasset630,054 bytesassets/chart-atlas/atlas-06-distributions.pngasset233,827 bytesassets/chart-atlas/atlas-07-forest-interval.pngasset270,166 bytesassets/chart-atlas/atlas-08-area-stacked.pngasset334,735 bytesassets/chart-atlas/atlas-09-image-plates.pngasset359,027 bytesassets/chart-atlas/atlas-10-network-matrix.pngasset312,125 bytesassets/figures4papers/assets/Dispersion_motivation.pngasset837,657 bytesassets/figures4papers/assets/Dispersion_observation.pngasset808,992 bytesassets/figures4papers/assets/Dispersion_observation_distillation.pngasset616,612 bytesassets/figures4papers/assets/ImmunoStruct_contrastive.pngasset502,211 bytesassets/figures4papers/assets/ImmunoStruct_results_CEDAR.pngasset1,281,557 bytesassets/figures4papers/assets/ImmunoStruct_results_IEDB.pngasset956,273 bytesassets/figures4papers/assets/ImmunoStruct_schematic.pngasset972,870 bytesassets/figures4papers/assets/RNAGenScape_schematic.pngasset1,000,298 bytesassets/figures4papers/figure_CellSpliceNet/figures/ablation.pngasset355,284 bytesassets/figures4papers/figure_CellSpliceNet/figures/comparison.pngasset813,084 bytesassets/figures4papers/figure_CellSpliceNet/plot_ablation.pyruns2,964 bytesassets/figures4papers/figure_CellSpliceNet/plot_comparison.pyruns3,909 bytesassets/figures4papers/figure_Cflows/diffusion_swiss_roll.pyruns3,545 bytesassets/figures4papers/figure_Cflows/figures/diffusion_swiss_roll.pngasset1,794,980 bytesassets/figures4papers/figure_Cflows/figures/fig2_comparison_GeneRegulatory.pdfasset24,757 bytesassets/figures4papers/figure_Cflows/figures/fig2_comparison_GeneRegulatory.pngasset287,419 bytesassets/figures4papers/figure_Cflows/figures/fig2_comparison_Trajectory.pdfasset19,791 bytesassets/figures4papers/figure_Cflows/figures/fig2_comparison_Trajectory.pngasset388,293 bytesassets/figures4papers/figure_Cflows/figures/figX_comparison_Ablation.pdfasset19,233 bytesassets/figures4papers/figure_Cflows/figures/figX_comparison_Ablation.pngasset328,952 bytesassets/figures4papers/figure_Cflows/plot_comparison_Ablation.pyruns2,506 bytesassets/figures4papers/figure_Cflows/plot_comparison_GeneRegulatory.pyruns3,022 bytesassets/figures4papers/figure_Cflows/plot_comparison_Trajectory.pyruns2,941 bytesassets/figures4papers/figure_Dispersion/figures/idea.pngasset384,839 bytesassets/figures4papers/figure_Dispersion/figures/illustration.pngasset762,950 bytesassets/figures4papers/figure_Dispersion/plot_idea.pyruns2,432 bytesassets/figures4papers/figure_Dispersion/plot_illustration.pyruns15,472 bytesassets/figures4papers/figure_FPGM/figures/freq_prior.pngasset641,033 bytesassets/figures4papers/figure_FPGM/plot_freq_prior.pyruns6,578 bytesassets/figures4papers/figure_ImmunoStruct/figures/bars_ablation_Cancer.pngasset816,715 bytesassets/figures4papers/figure_ImmunoStruct/figures/bars_ablation_IEDB.pngasset1,160,225 bytesassets/figures4papers/figure_ImmunoStruct/figures/bars_comparison_Cancer.pngasset799,770 bytesassets/figures4papers/figure_ImmunoStruct/figures/bars_comparison_IEDB.pngasset757,551 bytesassets/figures4papers/figure_ImmunoStruct/plot_bars.pyruns7,707 bytesassets/figures4papers/figure_ImmunoStruct/raw_data.pyruns4,459 bytesassets/figures4papers/figure_RNAGenScape/figures/manifold.pngasset108,276 bytesassets/figures4papers/figure_RNAGenScape/figures/manifold_holes.pngasset1,019,896 bytesassets/figures4papers/figure_RNAGenScape/figures/results_comparison_optimization.pngasset850,446 bytesassets/figures4papers/figure_RNAGenScape/figures/results_comparison_speed.pngasset92,362 bytesassets/figures4papers/figure_RNAGenScape/figures/results_sweep.pngasset142,120 bytesassets/figures4papers/figure_RNAGenScape/plot_comparison.pyruns11,236 bytesassets/figures4papers/figure_RNAGenScape/plot_hole_manifold.pyruns2,547 bytesassets/figures4papers/figure_RNAGenScape/plot_manifold.pyruns1,811 bytesassets/figures4papers/figure_RNAGenScape/plot_sweep.pyruns2,873 bytesassets/figures4papers/figure_VIGIL/figures/comparison_posttraining.pngasset249,289 bytesassets/figures4papers/figure_VIGIL/figures/comparison_radar.pngasset809,841 bytesassets/figures4papers/figure_VIGIL/plot_comparison_radar.pyruns7,397 bytesassets/figures4papers/figure_VIGIL/plot_posttraining.pyruns2,948 bytesassets/figures4papers/figure_brainteaser/figures/brute_force.pngasset1,753,162 bytesassets/figures4papers/figure_brainteaser/figures/correctness_by_category.pngasset655,498 bytesassets/figures4papers/figure_brainteaser/figures/correctness_by_subcategory.pngasset1,100,554 bytesassets/figures4papers/figure_brainteaser/figures/rewriting.pngasset410,105 bytesassets/figures4papers/figure_brainteaser/figures/selfcorrection_math.pngasset611,488 bytesassets/figures4papers/figure_brainteaser/plot_brute_force.pyruns10,181 bytesassets/figures4papers/figure_brainteaser/plot_correctness_by_category.pyruns6,403 bytesassets/figures4papers/figure_brainteaser/plot_correctness_by_subcategory.pyruns6,505 bytesassets/figures4papers/figure_brainteaser/plot_rewriting.pyruns3,694 bytesassets/figures4papers/figure_brainteaser/plot_selfcorrection_math.pyruns4,015 bytesassets/figures4papers/figure_ophthal_review/figures/composition_heatmap.pngasset279,533 bytesassets/figures4papers/figure_ophthal_review/figures/trend_by_month.pngasset364,102 bytesassets/figures4papers/figure_ophthal_review/plot_composition.pyruns3,032 bytesassets/figures4papers/figure_ophthal_review/plot_trend.pyruns5,531 bytesassets/gallery/fig1-material-mechanism-rich.pngasset570,018 bytesassets/gallery/fig2-spatial-imaging-rich.pngasset643,666 bytesassets/gallery/fig3-in-vivo-efficacy-rich.pngasset371,419 bytesassets/gallery/fig4-single-cell-systems-rich.pngasset392,735 bytesassets/gallery/fig5-validation-perturbation-rich.pngasset408,275 bytesevals/evals.jsonasset2,127 bytesmanifest.yamlasset2,999 bytesreferences/api.mddoc13,552 bytesreferences/backend-selection.mddoc4,694 bytesreferences/chart-types.mddoc8,911 bytesreferences/common-patterns.mddoc9,950 bytesreferences/demos.mddoc4,118 bytesreferences/design-theory.mddoc15,620 bytesreferences/figure-contract.mddoc3,970 bytesreferences/nature-2026-observations.mddoc5,622 bytesreferences/qa-contract.mddoc4,736 bytesreferences/r-template-index.mddoc3,903 bytesreferences/r-workflow.mddoc5,275 bytesreferences/tutorials.mddoc8,169 bytesstatic/core/contract.mddoc3,076 bytesstatic/core/stance.mddoc3,371 bytesstatic/fragments/backend/python.mddoc1,936 bytesstatic/fragments/backend/r.mddoc2,075 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmarkdown-report-writing
When your agent uses it
Guide AI agents to write beautifully formatted, well-illustrated Markdown reports with proper structure, diagrams, and compatibility across GitHub and Obsidian. Use this skill whenever the user asks you to write a report, project documentation, experiment report, README, technical document, or any long-form Markdown content. Also trigger when users mention Markdown formatting, Mermaid diagrams, report templates, or document publishing.
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
2,580 tokensWhen the skill is activated
Reference documents
2,247 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Core Philosophy: Three-Layer Writing Model
- Writing Principles
- Quality Checklist
- Standard Document Skeleton
- Layout & Typesetting Techniques
- Report Templates
- Choosing Tools for the Job
- File & Asset Management
- CI Quality Pipeline
- Quick Reference: Per-Environment Differences
- References
Files
SKILL.mdcore10,752 bytesSKILL.mdcore10,752 bytesSKILL.mdcore10,752 bytesSKILL.mdcore10,752 bytesSKILL.mdcore10,752 bytesreferences/compatibility-matrix.mddoc3,772 bytesreferences/templates.mddoc5,166 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneuroimaging-power-guide
When your agent uses it
Sample-size planning for fMRI/EEG studies using effect-size benchmarks and simulation-based power
What it loads into context
Frontmatter
181 tokensAlways available to the agent
SKILL.md
5,353 tokensWhen the skill is activated
Reference documents
2,233 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Why Neuroimaging Power Is Different
- Typical Effect Sizes in Neuroimaging
- Sample Size Benchmarks
- Power Decision Tree
- Simulation-Based Power Approaches
- Multiple Comparison Correction Impact on Power
- Test-Retest Reliability and Power
- Practical Power Calculation Workflow
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore20,061 bytesSKILL.mdcore20,061 bytesreferences/effect-size-lookup-tables.mddoc6,606 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubneuroimaging-sample-size-calculator
When your agent uses it
Simulation-based sample-size planning for neuroimaging studies using effect-size maps
What it loads into context
Frontmatter
170 tokensAlways available to the agent
SKILL.md
5,114 tokensWhen the skill is activated
Reference documents
2,525 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Research Planning Protocol
- ⚠<U+FE0F> Verification Notice
- Why Traditional Power Analysis Fails for Neuroimaging
- The Pilot-Data-Based Simulation Approach
- Tools and Implementations
- ROI-Based Power Shortcuts
- Current Sample Size Recommendations
- Registered Report Considerations
- Practical Workflow for Grant Applications
- Common Pitfalls
- Minimum Reporting Checklist
- References
Files
SKILL.mdcore20,798 bytesreferences/worked-examples.mddoc8,623 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdeeplabcut
When your agent uses it
Toolbox for markerless animal pose estimation with DeepLabCut. Covers single/multi-animal tracking, SuperAnimal pretrained models, 2D/3D pose estimation, keypoint labeling GUI, model training/evaluation, video analysis, and behavioral quantification. Use when the user needs animal pose estimation, behavior tracking, keypoint detection in videos, or mentions DeepLabCut/DLC/SuperAnimal.
What it loads into context
Frontmatter
134 tokensAlways available to the agent
SKILL.md
1,712 tokensWhen the skill is activated
Reference documents
4,430 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use This Skill
- Quick Decision Tree
- Reference Files (Progressive Disclosure)
- Installation
- Standard Pipeline Overview
- Key API Reference
- Common Pitfalls
Files
SKILL.mdcore6,937 bytesSKILL.mdcore6,937 bytesSKILL.mdcore6,937 bytesreferences/3d-pose.mddoc2,325 bytesreferences/maDLC.mddoc3,226 bytesreferences/modelzoo.mddoc3,515 bytesreferences/standard-pipeline.mddoc4,246 bytesreferences/utilities.mddoc3,336 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubliterature-search-arxiv
When your agent uses it
Search for scientific papers, preprints, and publications on arXiv. Extract metadata, abstracts, and download full-text PDFs or HTML versions of papers. Use when the user asks to find research papers, literature, or specific arXiv IDs.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
1,164 tokensWhen the skill is activated
Reference documents
282 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Core Rules
- Utility Scripts
- Reference
- Workflow
Scripts executed separately
scripts/download_paper.pyscripts/download_paper_source.pyscripts/search_arxiv.py
Files
SKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesSKILL.mdcore4,628 bytesreferences/citation.bibasset366 bytesreferences/query_syntax.mddoc997 bytesscripts/download_paper.pyruns3,455 bytesscripts/download_paper_source.pyruns2,881 bytesscripts/search_arxiv.pyruns5,118 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubliterature-search-biorxiv
When your agent uses it
Browse, filter, and download life sciences, biology, and medical preprints from bioRxiv and medRxiv. Supports fetching paper metadata by DOI, and browsing by date range with category and keyword filters. Keyword filtering is local, so date ranges MUST be narrow (1-4 weeks) with a category to prevent timeouts.
What it loads into context
Frontmatter
86 tokensAlways available to the agent
SKILL.md
1,996 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
- Search Strategy Guide (Read First)
- Core Rules
- Utility Scripts
- Valid Subject Categories
Scripts executed separately
scripts/search_by_dates.pyscripts/search_by_doi.py
Files
SKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesSKILL.mdcore7,747 bytesreferences/citation.bibasset3,018 bytesscripts/search_by_dates.pyruns8,611 bytesscripts/search_by_doi.pyruns2,101 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubliterature-search-europepmc
When your agent uses it
Search Europe PMC for scientific literature and download open-access full texts and PDFs. Retrieve full-text XML/plain text by PMCID, get citation lists and bibliography.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
2,295 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
- Core Rules
- Utility Scripts
- Common Workflows
Scripts executed separately
scripts/europepmc_api.py
Files
SKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesSKILL.mdcore8,357 bytesreferences/citation.bibasset2,022 bytesscripts/europepmc_api.pyruns11,419 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubliterature-search-openalex
When your agent uses it
Query the OpenAlex scholarly database for research papers, authors, institutions, topics, sources, publishers, funders, geo-locations, and keywords. Use when searching academic papers, resolving DOIs, downloading open-access PDFs, finding an author's publications, aggregating bibliometric data (citation counts, h-index, impact factor), exploring the research taxonomies, or performing DOI lookups.
What it loads into context
Frontmatter
97 tokensAlways available to the agent
SKILL.md
1,886 tokensWhen the skill is activated
Reference documents
10,274 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Core Rules
- Rate Limits
- CLI Reference
- Entity References
- Common Workflows
- Error Handling
Scripts executed separately
scripts/openalex_cli.py
Files
SKILL.mdcore7,407 bytesSKILL.mdcore7,407 bytesreferences/authors.mddoc3,703 bytesreferences/citation.bibasset299 bytesreferences/geo_and_language.mddoc1,982 bytesreferences/institutions.mddoc2,813 bytesreferences/publishers_funders.mddoc2,571 bytesreferences/sources.mddoc3,851 bytesreferences/taxonomy.mddoc2,865 bytesreferences/topics.mddoc1,188 bytesreferences/type_values.mddoc3,657 bytesreferences/works.mddoc17,281 bytesscripts/openalex_cli.pyruns20,156 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpubmed-database
When your agent uses it
Search PubMed for scientific literature, including published clinical trials. Fetch abstracts and full text. Link published research to biological databases (gene, protein, nucleotide, PubChem) to discover associations between papers and specific compounds or genes. Verify medical spelling, match raw citations, and cache result sets for bulk processing. Interfaces NCBI E-utilities and PMC BioC APIs.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
2,007 tokensWhen the skill is activated
Reference documents
8,767 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Core Rules
- Structure of the skill folder
- CLI Usage
- Essential Recipes
- Functions
Scripts executed separately
scripts/pubmed_api.py
Files
SKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesSKILL.mdcore8,343 bytesreferences/advanced-linking.mddoc5,520 bytesreferences/advanced-search.mddoc3,660 bytesreferences/bulk-workflows.mddoc3,599 bytesreferences/citation-matching.mddoc5,344 bytesreferences/citation.bibasset1,809 bytesreferences/cross-database-linking.mddoc4,025 bytesreferences/fetch-and-resolve.mddoc5,606 bytesreferences/search-and-discovery.mddoc4,948 bytesreferences/utilities.mddoc1,357 bytesscripts/pubmed_api.pyruns21,444 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubalphagenome-single-variant-analysis
When your agent uses it
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue/cell-type ontologies (UBERON/CL) or analyzing variants in chr:pos:ref>alt format.
What it loads into context
Frontmatter
138 tokensAlways available to the agent
SKILL.md
2,843 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
- Core Rules
- Environment Setup & Troubleshooting
- References
- Code Patterns
- Workflow Checklist
- Multi-Variant Workflow
Scripts executed separately
scripts/analyze_ism.pyscripts/generate_ontology_mapping.pyscripts/interpret_splicing.pyscripts/lookup_gene_info.pyscripts/resolve_ontology_terms.pyscripts/visualize_genome_tracks.pyscripts/visualize_variant_effects.py
Files
SKILL.mdcore11,690 bytesSKILL.mdcore11,690 bytesSKILL.mdcore11,690 bytesSKILL.mdcore11,690 bytesSKILL.mdcore11,690 bytespyproject.tomlasset269 bytesreferences/citation.bibasset823 bytesscripts/analyze_ism.pyruns10,378 bytesscripts/generate_ontology_mapping.pyruns4,965 bytesscripts/interpret_splicing.pyruns9,726 bytesscripts/lookup_gene_info.pyruns9,652 bytesscripts/resolve_ontology_terms.pyruns4,818 bytesscripts/visualize_genome_tracks.pyruns12,289 bytesscripts/visualize_variant_effects.pyruns36,440 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubclinvar-database
When your agent uses it
Use when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls for human genomic variants.
What it loads into context
Frontmatter
54 tokensAlways available to the agent
SKILL.md
4,015 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
- Overview
- When to Use
- Quick Start
- Core Rules
- Utility Scripts
- Typical Workflows
- Best Practices
- Common Mistakes
Scripts executed separately
scripts/clinvar_api.py
Files
SKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesSKILL.mdcore15,724 bytesreferences/citation.bibasset1,098 bytesscripts/clinvar_api.pyruns23,185 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubdbsnp-database
When your agent uses it
Use when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database. Resolves between rsIDs, genomic coordinates in VCF format, and HGVS strings. For an rsID, returns variant type, gene associations, clinical significance, allele frequencies, and genomic coordinates (GRCh38).
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
3,688 tokensWhen the skill is activated
Reference documents
1,025 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Core Rules
- When to Use
- Command Selection Guide
- Quick Start
- Commands
- Typical Workflows
- Assembly Defaults and Automatic Fallback
- NCBI API Key and Rate Limiting
- Troubleshooting HTTP 500 Errors
- Common Mistakes
Scripts executed separately
scripts/dbsnp_cli.py
Files
SKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesSKILL.mdcore13,639 bytesreferences/api-notes.mddoc3,762 bytesreferences/citation.bibasset368 bytesscripts/dbsnp_cli.pyruns18,439 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubgnomad-database
When your agent uses it
Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).
What it loads into context
Frontmatter
106 tokensAlways available to the agent
SKILL.md
764 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
- Core Rules
- Utility Scripts
- References
Scripts executed separately
scripts/get_gene_constraint.pyscripts/get_variant_frequency.pyscripts/search_variants.py
Files
SKILL.mdcore3,098 bytesSKILL.mdcore3,098 bytesSKILL.mdcore3,098 bytesSKILL.mdcore3,098 bytesreferences/citation.bibasset5,197 bytesscripts/get_gene_constraint.pyruns2,465 bytesscripts/get_variant_frequency.pyruns4,326 bytesscripts/search_variants.pyruns5,360 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubchembl-database
When your agent uses it
Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
2,911 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
- Prerequisites
- Core Rules
- Utility Script
- Common Options
- Reference
- Workflow
Scripts executed separately
scripts/chembl_api.py
Files
SKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesSKILL.mdcore11,504 bytesreferences/api_endpoints.mddoc2,832 bytesreferences/citation.bibasset3,639 bytesscripts/chembl_api.pyruns18,842 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubclinical-trials-database
When your agent uses it
Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility/inclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.
What it loads into context
Frontmatter
84 tokensAlways available to the agent
SKILL.md
3,237 tokensWhen the skill is activated
Reference documents
2,854 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Overview
- Core Rules
- Context Efficiency Warning
- Response Layout Summary
- Commands
- Pagination
- Advanced Querying
- References
Scripts executed separately
scripts/clinical_trials_api.py
Files
SKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesSKILL.mdcore12,708 bytesreferences/citation.bibasset376 bytesreferences/clinical_trials_api.mddoc6,331 bytesreferences/studies_schema.mddoc5,146 bytesscripts/clinical_trials_api.pyruns11,639 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubopenfda-database
When your agent uses it
Query, search, and download data from the openFDA API for drugs, devices, foods, tobacco, cosmetics, animal and veterinary products, substances, and transparency data. Use for FDA adverse events, recalls, labeling, approvals, shortages, 510(k) clearances, NDC lookups, and any FDA safety or regulatory data query across all 28 API endpoints.
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
2,282 tokensWhen the skill is activated
Reference documents
2,783 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Core Rules
- Utility Script
- Entity Resolution: Using .exact for Precision
- MedDRA Term Resolution
- Available Endpoints (28 total)
- Reference
- Recipes
- Workflow
Scripts executed separately
scripts/openfda_query.py
Files
SKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesSKILL.mdcore8,887 bytesreferences/api_endpoints.mddoc6,414 bytesreferences/citation.bibasset2,029 bytesreferences/recipes.mddoc3,930 bytesscripts/openfda_query.pyruns13,939 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubopentargets-database
When your agent uses it
Query Open Targets Platform for target-disease associations, drug target discovery, tractability/safety data, genetics/omics evidence, known drugs, for therapeutic target identification.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
2,297 tokensWhen the skill is activated
Reference documents
1,979 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Prerequisites
- Core Rules
- Quick Reference
- L2G Query Usage
- Querying by Region
- Advanced GraphQL Queries
- Confidence Star Ratings
- Tips and Common Mistakes
Scripts executed separately
scripts/query_opentargets.py
Files
SKILL.mdcore9,153 bytesSKILL.mdcore9,153 bytesSKILL.mdcore9,153 bytesreferences/OpenTargets_GraphQL_Guide.mddoc7,452 bytesreferences/citation.bibasset2,489 bytesscripts/query_opentargets.pyruns16,214 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubpubchem-database
When your agent uses it
Query PubChem, search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics. Use when a user asks about a specific chemical, drug, or molecule.
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
1,403 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
- Prerequisites
- Quick Start
- Core Rules
- Core Capabilities
- Advanced Context
- Complex Search & Biology
- Advanced Usage & Workflows
- Fallback Search Strategies
- Complex Queries and Multi-Step Tasks
Scripts executed separately
scripts/pubchem_api.py
Files
SKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesSKILL.mdcore5,615 bytesreferences/citation.bibasset2,042 bytesreferences/endpoints.mddoc2,448 bytesreferences/workflows.mddoc1,392 bytesscripts/pubchem_api.pyruns10,700 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubuv
When your agent uses it
Checks whether the uv Python package manager is installed and installs it if missing. Ensures uv is on PATH. Use when another skill requires uv as a prerequisite.
What it loads into context
Frontmatter
45 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
- Setup
Files
SKILL.mdcore1,246 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubspikeinterface-skill
When your agent uses it
Domain knowledge for building extracellular electrophysiology pipelines with SpikeInterface: loading data with extractors, preprocessing, running spike sorters, post-processing via SortingAnalyzer, quality metrics, curation, comparison, visualization, and export.
What it loads into context
Frontmatter
91 tokensAlways available to the agent
SKILL.md
5,969 tokensWhen the skill is activated
Reference documents
218,404 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 1. Purpose
- 2. When to Use This Skill
- 3. Reference Files (Progressive Disclosure)
- 4. Pipeline Overview
- 5. Quick Start
- 6. Key Concepts
- 7. Common Pitfalls
- 8. Installation and Import Shortcuts
Files
SKILL.mdcore26,220 bytesSKILL.mdcore26,220 bytesSKILL.mdcore26,220 bytesSKILL.mdcore26,220 bytesSKILL.mdcore26,220 bytesSKILL.mdcore26,220 bytesreferences/benchmark/INDEX.mddoc3,899 bytesreferences/benchmark/base_classes.mddoc8,290 bytesreferences/benchmark/cheatsheets.mddoc4,808 bytesreferences/benchmark/clustering_study.mddoc3,879 bytesreferences/benchmark/matching_study.mddoc3,043 bytesreferences/benchmark/merging_study.mddoc2,659 bytesreferences/benchmark/motion_estimation_study.mddoc3,614 bytesreferences/benchmark/motion_interpolation_study.mddoc3,513 bytesreferences/benchmark/package_exports.mddoc1,407 bytesreferences/benchmark/peak_detection_study.mddoc3,315 bytesreferences/benchmark/peak_localization_study.mddoc2,998 bytesreferences/benchmark/peak_selection_study.mddoc1,169 bytesreferences/benchmark/plot_helpers_a.mddoc3,756 bytesreferences/benchmark/plot_helpers_b.mddoc2,983 bytesreferences/benchmark/residual_analysis.mddoc2,139 bytesreferences/benchmark/sorter_study.mddoc3,591 bytesreferences/benchmark/sorter_study_no_gt.mddoc2,539 bytesreferences/benchmark/utility_helpers.mddoc728 bytesreferences/comparison/INDEX.mddoc3,076 bytesreferences/comparison/agreement_matching.mddoc1,678 bytesreferences/comparison/comparison_tools.mddoc7,917 bytesreferences/comparison/gt_specialised.mddoc3,301 bytesreferences/comparison/multi_comparisons.mddoc5,628 bytesreferences/comparison/overview.mddoc3,097 bytesreferences/comparison/pair_comparisons.mddoc11,410 bytesreferences/comparison/performance_metrics.mddoc1,328 bytesreferences/comparison/study_notes.mddoc3,641 bytesreferences/core/INDEX.mddoc5,731 bytesreferences/core/aggregation_slicing.mddoc6,054 bytesreferences/core/analyzer_extensions.mddoc4,138 bytesreferences/core/base_event.mddoc1,961 bytesreferences/core/base_extractor_a.mddoc5,544 bytesreferences/core/base_extractor_b.mddoc6,114 bytesreferences/core/base_recording_a.mddoc5,110 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No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubSkills included
- brainstorming
- dispatching-parallel-agents
- executing-plans
- finishing-a-development-branch
- receiving-code-review
- requesting-code-review
- subagent-driven-development
- systematic-debugging
- test-driven-development
- using-git-worktrees
- using-superpowers
- verification-before-completion
- writing-plans
- writing-skills
- brainstorming
- dispatching-parallel-agents
- executing-plans
- finishing-a-development-branch
- receiving-code-review
- requesting-code-review
- subagent-driven-development
- systematic-debugging
- test-driven-development
- using-git-worktrees
- using-superpowers
- verification-before-completion
- writing-plans
- writing-skills
- audit-code-artifact
- audit-data-integrity
- audit-evidence
- audit-feedback-loop
- audit-model-validation
- curate-research-trace
- create-data-inventory
- source-grounded-research-report
- contribute-skill
- contribute-skills-via-pr
- paper-to-skill
- repo-to-skill
- share-case
- share-usage
- verify-skill
- workflow-skill-creator
- cogsci-power-analysis
- cogsci-statistics
- cogsci-visualization
- research-literacy
- alternative-uses-task-designer
- cognitive-paradigm-design
- creativity-self-efficacy-mediation
- divergent-thinking-scoring
- drift-diffusion-model
- evidence-accumulation-selector
- signal-detection-analysis
- visual-search-array-generator
- reading-time-analysis
- self-paced-reading-designer
- sentence-stimulus-norming
- eeg-paradigm-designer
- eeg-preprocessing-pipeline-guide
- erp-analysis
- mne-python-guide
- brain-connectivity-modeler
- fmri-glm-analysis-guide
- fmri-preprocessing-pipeline-guide
- fmri-task-design-guide
- fmriprep
- netneurotools-guide
- neural-decoding-analysis
- pycortex-guide
- act-r-model-builder
- bayesian-cognitive-model-builder
- parameter-recovery-checker
- brain-connectivity-modeler
- neural-decoding-analysis
- neural-population-analysis-guide
- spiking-network-model-builder
- alphafold-database-fetch-and-analyze
- calcium-imaging-analysis-guide
- gtex-database
- human-protein-atlas-database
- optogenetics-protocol-designer
- pdb-database
- pymol
- lesion-symptom-mapping-guide
- neuropsych-battery-selector
- infant-looking-time-designer
- tom-task-selector
- nature-figure
- markdown-report-writing
- neuroimaging-power-guide
- neuroimaging-sample-size-calculator
- deeplabcut
- literature-search-arxiv
- literature-search-biorxiv
- literature-search-europepmc
- literature-search-openalex
- pubmed-database
- alphagenome-single-variant-analysis
- clinvar-database
- dbsnp-database
- gnomad-database
- chembl-database
- clinical-trials-database
- openfda-database
- opentargets-database
- pubchem-database
- uv
- spikeinterface-skill
Repository facts
- License
- AGPL-3.0
- Created
- Jun 13, 2026
- Last pushed
- Nov 4, 2026
- Forks
- 74
- Open issues
- 19
- Project activity
- Active
Rank over the last 12 weeks
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Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 3, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 296 notes
packages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/finishing-a-development-branch/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/requesting-code-review/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/test-driven-development/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpackages/backend-core/plugins/superpowers/6.2.0/skills/using-git-worktrees/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- 17 dangerous shell commandsin 11 files: brainstorming/scripts/stop-server.sh:22 brainstorming/scripts/stop-server.sh:22 brainstorming/scripts/start-server.sh:148 and 8 more
- 923 network referencesin 165 files: fmriprep/references/citation.md:31 pdb-database/scripts/fetch_schema.py:5 literature-search-openalex/scripts/openalex_cli.py:5 and 162 more
- 16 obfuscation signalsin 2 files: markdown-report-writing/references/templates.md:62 markdown-report-writing/SKILL.md:131
- No instruction overrides
- 79 executable scriptsin 79 files: brainstorming/scripts/helper.js:1 brainstorming/scripts/server.cjs:1 brainstorming/scripts/start-server.sh:1 and 76 more
- 128 references to secretsin 28 files: literature-search-openalex/scripts/openalex_cli.py:92 openfda-database/scripts/openfda_query.py:80 pubmed-database/scripts/pubmed_api.py:58 and 25 more
- No requests to vote in Hot
Show all 1,163 signals by file
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/scripts/helper.js
- Executable scriptline 1
Executable file
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/scripts/server.cjs
- Executable scriptline 1
Executable file - Network accessline 104
const STATE_DIR = path.join(SESSION_DIR, 'state'); const SUPERPOWERS_VERSION = readSuperpowersVersion(); const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; - Network accessline 105
const SUPERPOWERS_VERSION = readSuperpowersVersion(); const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; const TELEMETRY_DISABLE_ENV_VARS = [ - Network accessline 106
const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; - Access to secretsline 133
[Credential-related source omitted] - Access to secretsline 134
[Credential-related source omitted] - Network accessline 251
return '<div class="brand"><a href="https://github.com/obra/superpowers">' + logo + '<span class="brand-copy">' + text + '</span></a></div>';
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/scripts/start-server.sh
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/scripts/stop-server.sh
- Executable scriptline 1
#!/usr/bin/env bash - Dangerous shell operationline 22
rm -f "${STATE_DIR}/server-info" - Dangerous shell operationline 79
rm -f "$PID_FILE" "$SERVER_ID_FILE" - Dangerous shell operationline 109
rm -f "$PID_FILE" "$SERVER_ID_FILE" "${STATE_DIR}/server.log" - Dangerous shell operationline 114
rm -rf "$SESSION_DIR"
packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/visual-companion.md
- Network accessline 40
# Returns: {"type":"server-started","port":52341, # "url":"http://localhost:52341/?key=ab12…", - Network accessline 41
# "url":"http://localhost:52341/?key=ab12…", - Network accessline 48
**The URL contains a session key (`?key=…`).** The server rejects any request without it, so always give the user the **complete** URL from the `url` field — never strip the query string, and never hand out a bare `http://host:port`. The - Network accessline 49
without it, so always give the user the **complete** URL from the `url` field — never strip the query string, and never hand out a bare `http://host:port`. The key gates HTTP and WebSocket access so a stray browser tab or another machine on - Network accessline 50
never strip the query string, and never hand out a bare `http://host:port`. The - Access to secretsline 53
[Credential-related source omitted]
packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/SKILL.md
- Dangerous shell operationline 419
delete this plan's workspace (`rm -rf <workspace>`) — the git history is
packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/scripts/review-package
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/scripts/sdd-workspace
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.0/skills/subagent-driven-development/scripts/task-brief
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging/SKILL.md
packages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging/condition-based-waiting-example.ts
- Executable scriptline 1
Executable file
packages/backend-core/plugins/superpowers/6.2.0/skills/systematic-debugging/find-polluter.sh
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.0/skills/writing-skills/SKILL.md
- Network accessline 95
**Frontmatter (YAML):** - Two required fields: `name` and `description` (see [agentskills.io/specification](https://agentskills.io/specification) for all supported fields) - Network accessline 96
- Two required fields: `name` and `description` (see [agentskills.io/specification](https://agentskills.io/specification) for all supported fields) - Network accessline 636
**GREEN Phase - Write Minimal Skill:** - [ ] Name uses only letters, numbers, hyphens (no parentheses/special chars) - [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/spe - Network accessline 637
- [ ] Name uses only letters, numbers, hyphens (no parentheses/special chars) - [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/specification)) - [ ] Description starts w - Network accessline 638
- [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/specification))
packages/backend-core/plugins/superpowers/6.2.0/skills/writing-skills/anthropic-best-practices.md
- Network accessline 7
For conceptual background on how Skills work, see the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview). - Network accessline 13
The [context window](https://platform.claude.com/docs/en/build-with-claude/context-windows) is a public good. Your Skill shares the context window with everything else your agent needs to know, including: - Network accessline 152
For complete Skill structure details, see the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#skill-structure). - Network accessline 237
SKILL.md serves as an overview that points agents to detailed materials as needed, like a table of contents in an onboarding guide. For an explanation of how progressive disclosure works, see [How Skills work](https://platform.claude.com/do - Network accessline 249
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-simple-file.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=87782ff239b297d9a9e8e1b72ed72db9" alt="Simple SKILL.md file showing YAML frontmatter and - Network accessline 253
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-bundling-content.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=a5e0aa41e3d53985a7e3e43668a33ea3" alt="Bundling additional reference files like refe - Network accessline 919
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-executable-scripts.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=4bbc45f2c2e0bee9f2f0d5da669bad00" alt="Bundling executable scripts alongside instr - Network accessline 1011
List required packages in your SKILL.md and verify they're available in the [code execution tool documentation](https://platform.claude.com/docs/en/agents-and-tools/tool-use/code-execution-tool). - Network accessline 1015
Skills run in a code execution environment with filesystem access, bash commands, and code execution capabilities. For the conceptual explanation of this architecture, see [The Skills architecture](https://platform.claude.com/docs/en/agents - Network accessline 1051
For complete details on the technical architecture, see [How Skills work](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#how-skills-work) in the Skills overview. - Network accessline 1095
The SKILL.md frontmatter requires `name` (64 characters max) and `description` (1024 characters max) fields. See the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#skill-structure) for complete - Network accessline 1099
Keep SKILL.md body under 500 lines for optimal performance. If your content exceeds this, split it into separate files using the progressive disclosure patterns described earlier. For architectural details, see the [Skills overview](https:/ - Network accessline 1138
<CardGroup cols={2}> <Card title="Get started with Agent Skills" icon="rocket" href="https://platform.claude.com/docs/en/agents-and-tools/agent-skills/quickstart"> - Network accessline 1139
<Card title="Get started with Agent Skills" icon="rocket" href="https://platform.claude.com/docs/en/agents-and-tools/agent-skills/quickstart"> - Network accessline 1143
<Card title="Use Skills in Claude Code" icon="terminal" href="https://code.claude.com/docs/en/skills"> - Network accessline 1147
<Card title="Use Skills with the API" icon="code" href="https://platform.claude.com/docs/en/build-with-claude/skills-guide">
packages/backend-core/plugins/superpowers/6.2.0/skills/writing-skills/render-graphs.js
- Executable scriptline 1
#!/usr/bin/env node
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/scripts/helper.js
- Executable scriptline 1
Executable file
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/scripts/server.cjs
- Executable scriptline 1
Executable file - Network accessline 104
const STATE_DIR = path.join(SESSION_DIR, 'state'); const SUPERPOWERS_VERSION = readSuperpowersVersion(); const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; - Network accessline 105
const SUPERPOWERS_VERSION = readSuperpowersVersion(); const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; const TELEMETRY_DISABLE_ENV_VARS = [ - Network accessline 106
const SUPERPOWERS_BRAND_IMAGE_URL = 'https://primeradiant.com/brand/superpowers-visual-brainstorming-logo.png'; - Access to secretsline 133
[Credential-related source omitted] - Access to secretsline 134
[Credential-related source omitted] - Network accessline 251
return '<div class="brand"><a href="https://github.com/obra/superpowers">' + logo + '<span class="brand-copy">' + text + '</span></a></div>';
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/scripts/start-server.sh
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/scripts/stop-server.sh
- Executable scriptline 1
#!/usr/bin/env bash - Dangerous shell operationline 22
rm -f "${STATE_DIR}/server-info" - Dangerous shell operationline 79
rm -f "$PID_FILE" "$SERVER_ID_FILE" - Dangerous shell operationline 109
rm -f "$PID_FILE" "$SERVER_ID_FILE" "${STATE_DIR}/server.log" - Dangerous shell operationline 114
rm -rf "$SESSION_DIR"
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/brainstorming/visual-companion.md
- Network accessline 40
# Returns: {"type":"server-started","port":52341, # "url":"http://localhost:52341/?key=ab12…", - Network accessline 41
# "url":"http://localhost:52341/?key=ab12…", - Network accessline 48
**The URL contains a session key (`?key=…`).** The server rejects any request without it, so always give the user the **complete** URL from the `url` field — never strip the query string, and never hand out a bare `http://host:port`. The - Network accessline 49
without it, so always give the user the **complete** URL from the `url` field — never strip the query string, and never hand out a bare `http://host:port`. The key gates HTTP and WebSocket access so a stray browser tab or another machine on - Network accessline 50
never strip the query string, and never hand out a bare `http://host:port`. The - Access to secretsline 53
[Credential-related source omitted]
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development/SKILL.md
- Dangerous shell operationline 419
delete this plan's workspace (`rm -rf <workspace>`) — the git history is
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development/scripts/review-package
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development/scripts/sdd-workspace
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/subagent-driven-development/scripts/task-brief
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/systematic-debugging/SKILL.md
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/systematic-debugging/condition-based-waiting-example.ts
- Executable scriptline 1
Executable file
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/systematic-debugging/find-polluter.sh
- Executable scriptline 1
#!/usr/bin/env bash
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-skills/SKILL.md
- Network accessline 95
**Frontmatter (YAML):** - Two required fields: `name` and `description` (see [agentskills.io/specification](https://agentskills.io/specification) for all supported fields) - Network accessline 96
- Two required fields: `name` and `description` (see [agentskills.io/specification](https://agentskills.io/specification) for all supported fields) - Network accessline 636
**GREEN Phase - Write Minimal Skill:** - [ ] Name uses only letters, numbers, hyphens (no parentheses/special chars) - [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/spe - Network accessline 637
- [ ] Name uses only letters, numbers, hyphens (no parentheses/special chars) - [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/specification)) - [ ] Description starts w - Network accessline 638
- [ ] YAML frontmatter with required `name` and `description` fields (max 1024 chars; see [spec](https://agentskills.io/specification))
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-skills/anthropic-best-practices.md
- Network accessline 7
For conceptual background on how Skills work, see the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview). - Network accessline 13
The [context window](https://platform.claude.com/docs/en/build-with-claude/context-windows) is a public good. Your Skill shares the context window with everything else your agent needs to know, including: - Network accessline 152
For complete Skill structure details, see the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#skill-structure). - Network accessline 237
SKILL.md serves as an overview that points agents to detailed materials as needed, like a table of contents in an onboarding guide. For an explanation of how progressive disclosure works, see [How Skills work](https://platform.claude.com/do - Network accessline 249
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-simple-file.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=87782ff239b297d9a9e8e1b72ed72db9" alt="Simple SKILL.md file showing YAML frontmatter and - Network accessline 253
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-bundling-content.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=a5e0aa41e3d53985a7e3e43668a33ea3" alt="Bundling additional reference files like refe - Network accessline 919
<img src="https://mintcdn.com/anthropic-claude-docs/4Bny2bjzuGBK7o00/images/agent-skills-executable-scripts.png?fit=max&auto=format&n=4Bny2bjzuGBK7o00&q=85&s=4bbc45f2c2e0bee9f2f0d5da669bad00" alt="Bundling executable scripts alongside instr - Network accessline 1011
List required packages in your SKILL.md and verify they're available in the [code execution tool documentation](https://platform.claude.com/docs/en/agents-and-tools/tool-use/code-execution-tool). - Network accessline 1015
Skills run in a code execution environment with filesystem access, bash commands, and code execution capabilities. For the conceptual explanation of this architecture, see [The Skills architecture](https://platform.claude.com/docs/en/agents - Network accessline 1051
For complete details on the technical architecture, see [How Skills work](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#how-skills-work) in the Skills overview. - Network accessline 1095
The SKILL.md frontmatter requires `name` (64 characters max) and `description` (1024 characters max) fields. See the [Skills overview](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview#skill-structure) for complete - Network accessline 1099
Keep SKILL.md body under 500 lines for optimal performance. If your content exceeds this, split it into separate files using the progressive disclosure patterns described earlier. For architectural details, see the [Skills overview](https:/ - Network accessline 1138
<CardGroup cols={2}> <Card title="Get started with Agent Skills" icon="rocket" href="https://platform.claude.com/docs/en/agents-and-tools/agent-skills/quickstart"> - Network accessline 1139
<Card title="Get started with Agent Skills" icon="rocket" href="https://platform.claude.com/docs/en/agents-and-tools/agent-skills/quickstart"> - Network accessline 1143
<Card title="Use Skills in Claude Code" icon="terminal" href="https://code.claude.com/docs/en/skills"> - Network accessline 1147
<Card title="Use Skills with the API" icon="code" href="https://platform.claude.com/docs/en/build-with-claude/skills-guide">
packages/backend-core/plugins/superpowers/6.2.1-bp.1/skills/writing-skills/render-graphs.js
- Executable scriptline 1
#!/usr/bin/env node
packages/skills/skills/01_Meta-Skills/contribute-skill/SKILL.md
- Network accessline 44
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 53
- Requires `gh` CLI installed and authenticated - Run `gh auth status` to check - Install from https://cli.github.com/ and run `gh auth login` - Network accessline 55
- Install from https://cli.github.com/ and run `gh auth login` - Network accessline 130
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 232
xdg-open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/issues/new?labels=community-skill&title=%5BCommunity%20Skill%5D%20skill-name-here" 2>/dev/null || \ - Network accessline 233
open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/issues/new?labels=community-skill&title=%5BCommunity%20Skill%5D%20skill-name-here" 2>/dev/null || \ - Network accessline 234
echo "Please open: https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/issues/new?labels=community-skill" - Network accessline 260
You can submit it later by: 1. Opening https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/issues/new - Network accessline 261
1. Opening https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/issues/new
packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr/SKILL.md
- Network accessline 15
This skill encodes the complete workflow for contributing a new skill to the [NeuroAIHub/awesome_cognitive_and_neuroscience_skills](https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills) repository via GitHub Pull Request. - Network accessline 94
> thresholds, and citations require independent verification before use in > research. If you find errors, please open an issue at > https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills/issues. - Network accessline 96
> https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills/issues. - Network accessline 113
# 1. Fork on GitHub, then clone your fork git clone https://github.com/<your-username>/awesome_cognitive_and_neuroscience_skills.git - Network accessline 114
git clone https://github.com/<your-username>/awesome_cognitive_and_neuroscience_skills.git
packages/skills/skills/01_Meta-Skills/paper-to-skill/SKILL.md
- Network accessline 41
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/01_Meta-Skills/repo-to-skill/SKILL.md
- Network accessline 43
git clone https://github.com/<owner>/<repo>.git /tmp/skill-source-repo
packages/skills/skills/01_Meta-Skills/share-case/SKILL.md
- Network accessline 39
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 48
- Requires `gh` CLI installed and authenticated - Run `gh auth status` to check - Install from https://cli.github.com/ and run `gh auth login` - Network accessline 50
- Install from https://cli.github.com/ and run `gh auth login` - Network accessline 192
xdg-open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell" 2>/dev/null || \ - Network accessline 193
open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell" 2>/dev/null || \ - Network accessline 194
echo "Please open: https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell"
packages/skills/skills/01_Meta-Skills/share-usage/SKILL.md
- Network accessline 239
If `gh` is not installed or not authenticated, inform the user: > To share usage reports directly, you need the GitHub CLI. Install it from https://cli.github.com/ and run `gh auth login`. - Network accessline 240
> To share usage reports directly, you need the GitHub CLI. Install it from https://cli.github.com/ and run `gh auth login`. - Network accessline 299
You can manually share at: https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell - Network accessline 300
https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell
packages/skills/skills/01_Meta-Skills/verify-skill/SKILL.md
- Network accessline 45
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 57
If not authenticated, tell the user: > To submit verification reports, you need the GitHub CLI. Install it from https://cli.github.com/ and run `gh auth login`. - Network accessline 58
> To submit verification reports, you need the GitHub CLI. Install it from https://cli.github.com/ and run `gh auth login`.
packages/skills/skills/01_Meta-Skills/workflow-skill-creator/references/cli_script_template.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 49
BASE_URL = 'https://api.example.com/v1'
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-power-analysis/SKILL.md
- Network accessline 53
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-power-analysis/references/sample-size-guide.md
- Network accessline 308
- **Platform**: Windows, macOS (free) - **Download**: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower - Network accessline 309
- **Download**: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower - Network accessline 330
- **Install**: `install.packages("Superpower")` - **Web app**: https://arcstats.io/shiny/anova-power/ - Network accessline 331
- **Web app**: https://arcstats.io/shiny/anova-power/ - Network accessline 344
- **Platform**: Web-based (http://neuropowertools.org)
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-statistics/SKILL.md
- Network accessline 51
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/02_Cross-Domain_Foundation/cogsci-visualization/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/02_Cross-Domain_Foundation/research-literacy/SKILL.md
- Network accessline 36
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/03_Cognitive_Psychology/alternative-uses-task-designer/SKILL.md
- Network accessline 46
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 186
- Carson, S. H., Peterson, J. B., & Higgins, D. M. (2005). Reliability, validity, and factor structure of the Creative Achievement Questionnaire. *Creativity Research Journal*, 17(1), 37-50. - Guilford, J. P. (1967). *The nature of human in - Network accessline 187
- Guilford, J. P. (1967). *The nature of human intelligence*. McGraw-Hill. - Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human Behaviour*. https://doi.org/10.1038/s41562-024-019 - Network accessline 188
- Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human Behaviour*. https://doi.org/10.1038/s41562-024-01953-1
packages/skills/skills/03_Cognitive_Psychology/cognitive-paradigm-design/SKILL.md
- Network accessline 41
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/03_Cognitive_Psychology/creativity-self-efficacy-mediation/SKILL.md
- Network accessline 46
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 260
- Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. *Psychological Science*, 18(3), 233-239. - Hayes, A. F. (2022). *Introduction to mediation, moderation, and conditional process analysis* (3rd ed - Network accessline 261
- Hayes, A. F. (2022). *Introduction to mediation, moderation, and conditional process analysis* (3rd ed.). Guilford Press. - Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human B - Network accessline 262
- Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human Behaviour*. https://doi.org/10.1038/s41562-024-01953-1
packages/skills/skills/03_Cognitive_Psychology/divergent-thinking-scoring/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 159
- Compute **cosine distance** = 1 - cosine_similarity(prompt, response) 3. **Per-participant score**: Average semantic distance across all responses 4. **Platform**: SemDis (https://semdis.wlu.psu.edu/) — web-based tool by Beaty & Johnson ( - Network accessline 161
4. **Platform**: SemDis (https://semdis.wlu.psu.edu/) — web-based tool by Beaty & Johnson (2021) - Network accessline 227
- Beaty, R. E., & Johnson, D. R. (2021). Automating creativity assessment with SemDis: An open platform for computing semantic distance. *Behavior Research Methods*, 53(2), 757-780. - Guilford, J. P. (1967). *The nature of human intelligenc - Network accessline 228
- Guilford, J. P. (1967). *The nature of human intelligence*. McGraw-Hill. - Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human Behaviour*. https://doi.org/10.1038/s41562-024-019 - Network accessline 229
- Lee, B. C., & Chung, J. (2024). An empirical investigation of the impact of ChatGPT on creativity. *Nature Human Behaviour*. https://doi.org/10.1038/s41562-024-01953-1
packages/skills/skills/03_Cognitive_Psychology/divergent-thinking-scoring/references/scoring-rubric.md
- Network accessline 80
1. Go to https://semdis.wlu.psu.edu/
packages/skills/skills/03_Cognitive_Psychology/drift-diffusion-model/SKILL.md
- Network accessline 55
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/03_Cognitive_Psychology/drift-diffusion-model/references/fitting-guide.md
- Network accessline 198
| **Strengths** | Very fast; well-validated; supports multiple fitting methods; mature and widely cited | | **Limitations** | Command-line only; no hierarchical modeling; limited flexibility for custom models | | **URL** | https://www.psych - Network accessline 199
| **Limitations** | Command-line only; no hierarchical modeling; limited flexibility for custom models | | **URL** | https://www.psychologie.uni-heidelberg.de/ae/meth/fast-dm/ | | **Reference** | Voss, A., & Voss, J. (2007). Fast-dm: A free - Network accessline 200
| **URL** | https://www.psychologie.uni-heidelberg.de/ae/meth/fast-dm/ | - Network accessline 212
| **Strengths** | Hierarchical modeling; full posterior distributions; regression on parameters (link neural/physiological data to DDM parameters); well-documented | | **Limitations** | Slow for large datasets; requires MCMC convergence dia - Network accessline 213
| **Limitations** | Slow for large datasets; requires MCMC convergence diagnostics; Python 3 compatibility varies by version | | **URL** | https://github.com/hddm-devs/hddm | | **Reference** | Wiecki, T. V., Sofer, I., & Frank, M. J. (2013) - Network accessline 214
| **URL** | https://github.com/hddm-devs/hddm | - Network accessline 260
| **Strengths** | Maximum flexibility; supports collapsing bounds, leaky integration, custom noise; good documentation and tutorials | | **Limitations** | Slower than fast-dm for standard models; requires more programming expertise; no buil - Network accessline 261
| **Limitations** | Slower than fast-dm for standard models; requires more programming expertise; no built-in hierarchical modeling | | **URL** | https://pyddm.readthedocs.io/ | | **Reference** | Shinn, M., Lam, N. H., & Murray, J. D. (2020 - Network accessline 262
| **URL** | https://pyddm.readthedocs.io/ |
packages/skills/skills/03_Cognitive_Psychology/evidence-accumulation-selector/SKILL.md
- Network accessline 56
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/03_Cognitive_Psychology/signal-detection-analysis/SKILL.md
- Network accessline 55
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/03_Cognitive_Psychology/signal-detection-analysis/references/application-guide.md
- Network accessline 198
Software: Available at https://github.com/smfleming/HMeta-d (MATLAB and Python).
packages/skills/skills/03_Cognitive_Psychology/visual-search-array-generator/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/04_Psycholinguistics/reading-time-analysis/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/04_Psycholinguistics/self-paced-reading-designer/SKILL.md
- Network accessline 55
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/04_Psycholinguistics/sentence-stimulus-norming/SKILL.md
- Network accessline 58
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/04_Psycholinguistics/sentence-stimulus-norming/references/lexical-databases-guide.md
- Network accessline 9
**Source**: Brysbaert & New (2009) **URL**: https://www.ugent.be/pp/experimentele-psychologie/en/research/documents/subtlexus - Network accessline 10
**URL**: https://www.ugent.be/pp/experimentele-psychologie/en/research/documents/subtlexus - Network accessline 37
**Source**: van Heuven et al. (2014) **URL**: http://crr.ugent.be/archives/1423 - Network accessline 38
**URL**: http://crr.ugent.be/archives/1423 - Network accessline 49
**Source**: Brysbaert, Warriner, & Kuperman (2014) **URL**: http://crr.ugent.be/archives/1330 - Network accessline 50
**URL**: http://crr.ugent.be/archives/1330 - Network accessline 71
**Source**: Kuperman, Stadthagen-Gonzalez, & Brysbaert (2012) **URL**: http://crr.ugent.be/archives/806 - Network accessline 72
**URL**: http://crr.ugent.be/archives/806 - Network accessline 91
**Source**: Warriner, Kuperman, & Brysbaert (2013) **URL**: http://crr.ugent.be/archives/1003 - Network accessline 92
**URL**: http://crr.ugent.be/archives/1003 - Network accessline 113
| Tool | URL | Features | |------|-----|----------| | **N-Watch** | https://www.pc.rhul.ac.uk/staff/c.davis/Utilities/N-Watch/ | N, frequency-weighted N, bigram frequency | - Network accessline 114
|------|-----|----------| | **N-Watch** | https://www.pc.rhul.ac.uk/staff/c.davis/Utilities/N-Watch/ | N, frequency-weighted N, bigram frequency | | **CLEARPOND** | http://clearpond.northwestern.edu/ | Cross-linguistic; N for English, Dutch - Network accessline 115
| **N-Watch** | https://www.pc.rhul.ac.uk/staff/c.davis/Utilities/N-Watch/ | N, frequency-weighted N, bigram frequency | - Network accessline 116
| **CLEARPOND** | http://clearpond.northwestern.edu/ | Cross-linguistic; N for English, Dutch, French, German, Spanish | - Network accessline 117
| **English Lexicon Project** | https://elexicon.wustl.edu/ | N, OLD20, phonological N, and many other metrics | - Network accessline 131
**URL**: https://elexicon.wustl.edu/ - Network accessline 143
|------|-----|----------| | **WordSmith** | Various | Corpus analysis toolkit | | **ARC Nonword Database** | https://www.cogsci.mq.edu.au/research/resources/nwdb/ | Nonword generation with controlled properties | - Network accessline 144
| **WordSmith** | Various | Corpus analysis toolkit | | **ARC Nonword Database** | https://www.cogsci.mq.edu.au/research/resources/nwdb/ | Nonword generation with controlled properties | | **Wuggy** | http://crr.ugent.be/programs-data/wuggy - Network accessline 145
| **ARC Nonword Database** | https://www.cogsci.mq.edu.au/research/resources/nwdb/ | Nonword generation with controlled properties | - Network accessline 146
| **Wuggy** | http://crr.ugent.be/programs-data/wuggy | Pseudoword generation matching real-word properties |
packages/skills/skills/05_EEG_ERP/eeg-paradigm-designer/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/05_EEG_ERP/eeg-preprocessing-pipeline-guide/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/05_EEG_ERP/erp-analysis/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/05_EEG_ERP/mne-python-guide/SKILL.md
- Network accessline 50
> This skill was generated by AI from MNE-Python source code and academic literature. All parameters, thresholds, and citations require independent verification. If you find errors, please open an issue at https://github.com/NeuroAIHub/awes
packages/skills/skills/05_EEG_ERP/mne-python-guide/references/source_localization.md
- Dangerous shell operationline 125
rm = make_inverse_resolution_matrix(fwd, inv, method='dSPM', lambda2=lambda2)
packages/skills/skills/06_fMRI_Neuroimaging/brain-connectivity-modeler/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/06_fMRI_Neuroimaging/fmri-glm-analysis-guide/SKILL.md
- Network accessline 52
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/06_fMRI_Neuroimaging/fmri-preprocessing-pipeline-guide/SKILL.md
- Network accessline 56
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/06_fMRI_Neuroimaging/fmri-task-design-guide/SKILL.md
- Network accessline 58
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/SKILL.md
- Network accessline 18
confounds table, output spaces / TemplateFlow, susceptibility distortion correction, BIDS filters, troubleshooting, and how to cite. It is derived from the fMRIPrep 25.2.x (LTS) source tree (https://github.com/nipreps/fmriprep). - Network accessline 20
the fMRIPrep 25.2.x (LTS) source tree (https://github.com/nipreps/fmriprep). - Network accessline 63
- **Homepage**: https://fmriprep.org - Network accessline 64
- **Repo**: https://github.com/nipreps/fmriprep - Network accessline 129
# 2. Get a FreeSurfer license (free): https://surfer.nmr.mgh.harvard.edu/registration.html - Network accessline 236
- **Group-level statistics** — fMRIPrep is participant-level only. Use FitLins, Nilearn, SPM, FSL FEAT, etc. downstream. - **Denoising strategy selection** — see [Ciric 2017](https://doi.org/10.1016/j.neuroimage.2017.03.020) and [Parkes 201 - Network accessline 237
- **Denoising strategy selection** — see [Ciric 2017](https://doi.org/10.1016/j.neuroimage.2017.03.020) and [Parkes 2018](https://doi.org/10.1016/j.neuroimage.2017.12.073); fMRIPrep only supplies regressors. - Network accessline 239
- **Custom Nipype workflow edits** — for extension, read the API docs at https://fmriprep.readthedocs.io/en/latest/api.html. - Network accessline 243
- Community Q&A: https://neurostars.org/tag/fmriprep (canonical support channel) - Network accessline 244
- Bug reports: https://github.com/nipreps/fmriprep/issues - Network accessline 245
- Full docs: https://fmriprep.org / https://fmriprep.readthedocs.io - Network accessline 246
- Sample HTML report: https://fmriprep.org/en/latest/_static/SampleReport/sample_report.html
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/bids-filter.md
- Network accessline 38
`acquisition`, `run`, `direction`, `reconstruction`, `subject`, `task`, `echo`, `part`, etc. See the PyBIDS config: https://github.com/bids-standard/pybids/blob/main/src/bids/layout/config/bids.json - Network accessline 40
https://github.com/bids-standard/pybids/blob/main/src/bids/layout/config/bids.json - Network accessline 285
- fMRIPrep FAQ on filter files: https://fmriprep.readthedocs.io/en/latest/faq.html#how-do-I-select-only-certain-files-to-be-input-to-fMRIPrep - Network accessline 286
- PyBIDS entity dictionary: https://github.com/bids-standard/pybids/blob/main/src/bids/layout/config/bids.json - Network accessline 287
- BIDS entity table: https://bids-specification.readthedocs.io/en/stable/appendices/entity-table.html
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/citation.md
- Network accessline 31
Full rationale: https://www.nipreps.org/intro/transparency/#citation-boilerplates - Network accessline 60
> (2019). **fMRIPrep: a robust preprocessing pipeline for functional MRI.** > *Nature Methods, 16*, 111–116. > https://doi.org/10.1038/s41592-018-0235-4 - Network accessline 61
> *Nature Methods, 16*, 111–116. > https://doi.org/10.1038/s41592-018-0235-4 > [Preprint](https://doi.org/10.1101/306951) - Network accessline 62
> https://doi.org/10.1038/s41592-018-0235-4 - Network accessline 63
> [Preprint](https://doi.org/10.1101/306951) - Network accessline 71
> **Analysis of task-based functional MRI data preprocessed with fMRIPrep.** > *Nature Protocols, 15*, 2186–2202. > https://doi.org/10.1038/s41596-020-0327-3 - Network accessline 72
> *Nature Protocols, 15*, 2186–2202. > https://doi.org/10.1038/s41596-020-0327-3 > [Preprint](https://doi.org/10.1101/694364) - Network accessline 73
> https://doi.org/10.1038/s41596-020-0327-3 - Network accessline 74
> [Preprint](https://doi.org/10.1101/694364) - Network accessline 82
> fMRIPrep — Software DOI: https://doi.org/10.5281/zenodo.852659 - Network accessline 136
publisher = {Zenodo}, doi = {10.5281/zenodo.852659}, url = {https://doi.org/10.5281/zenodo.852659} - Network accessline 137
doi = {10.5281/zenodo.852659}, url = {https://doi.org/10.5281/zenodo.852659} } - Network accessline 138
url = {https://doi.org/10.5281/zenodo.852659} - Network accessline 155
- **FreeSurfer** — https://github.com/freesurfer/freesurfer - Network accessline 156
- **recon-all** — Dale AM, Fischl B, Sereno MI (1999). Cortical surface-based analysis. https://doi.org/10.1006/nimg.1998.0395 - **bbregister & BBR** — Greve DN, Fischl B (2009). - Network accessline 157
analysis. https://doi.org/10.1006/nimg.1998.0395 - Network accessline 158
- **bbregister & BBR** — Greve DN, Fischl B (2009). https://doi.org/10.1016/j.neuroimage.2009.06.060 - **mri_robust_template** — Reuter M, Rosas HD, Fischl B (2012). - Network accessline 159
https://doi.org/10.1016/j.neuroimage.2009.06.060 - Network accessline 160
- **mri_robust_template** — Reuter M, Rosas HD, Fischl B (2012). https://doi.org/10.1016/j.neuroimage.2012.02.084 - **mri_robust_register** — Reuter M, Rosas HD, Fischl B (2010). - Network accessline 161
https://doi.org/10.1016/j.neuroimage.2012.02.084 - Network accessline 163
https://doi.org/10.1016/j.neuroimage.2010.07.020 - Network accessline 165
- **ANTs** — Avants BB et al. (2015). https://doi.org/10.3389/fninf.2015.00005 - Network accessline 166
https://doi.org/10.3389/fninf.2015.00005 - Network accessline 167
- **antsRegistration (SyN)** — Avants BB et al. (2008). https://doi.org/10.1016/j.media.2007.06.004 - **N4BiasFieldCorrection** — Tustison NJ et al. (2010). - Network accessline 168
https://doi.org/10.1016/j.media.2007.06.004 - Network accessline 169
- **N4BiasFieldCorrection** — Tustison NJ et al. (2010). https://doi.org/10.1109/TMI.2010.2046908 - **antsBrainExtraction** — Avants BB et al. (2015). - Network accessline 170
https://doi.org/10.1109/TMI.2010.2046908 - Network accessline 172
https://doi.org/10.1038/sdata.2015.3 - Network accessline 174
- **FSL** — Jenkinson M et al. (2012). NeuroImage. https://doi.org/10.1016/j.neuroimage.2011.09.015 - Network accessline 175
https://doi.org/10.1016/j.neuroimage.2011.09.015 - Network accessline 176
- **FAST** — Zhang Y et al. (2001). https://doi.org/10.1109/42.906424 - **BET** — Smith SM (2002). - Network accessline 177
https://doi.org/10.1109/42.906424 - Network accessline 178
- **BET** — Smith SM (2002). https://doi.org/10.1002/hbm.10062 - **FLIRT** — Jenkinson M et al. (2002). - Network accessline 179
https://doi.org/10.1002/hbm.10062 - Network accessline 180
- **FLIRT** — Jenkinson M et al. (2002). https://doi.org/10.1006/nimg.2002.1132 - **MCFLIRT** — Jenkinson M (2002). - Network accessline 181
https://doi.org/10.1006/nimg.2002.1132 - Network accessline 183
https://doi.org/10.1006/nimg.2002.1132 - Network accessline 185
- **AFNI** — Cox RW (1996). https://doi.org/10.1006/cbmr.1996.0014 - Network accessline 186
https://doi.org/10.1006/cbmr.1996.0014 - Network accessline 188
- **Connectome Workbench** — https://humanconnectome.org/software/connectome-workbench - Network accessline 193
- **DVARS / Framewise Displacement** (Power et al. 2012, 2014): https://doi.org/10.1016/j.neuroimage.2011.10.018 - Network accessline 194
https://doi.org/10.1016/j.neuroimage.2011.10.018 - Network accessline 195
- **DVARS improvements** — Afyouni & Nichols (2018): https://arxiv.org/abs/1704.01469 - **RMSD** — Jenkinson M et al. (2002): - Network accessline 196
https://arxiv.org/abs/1704.01469 - Network accessline 197
- **RMSD** — Jenkinson M et al. (2002): https://doi.org/10.1006/nimg.2002.1132 - **a/tCompCor** — Behzadi Y et al. (2007): - Network accessline 198
https://doi.org/10.1006/nimg.2002.1132 - Network accessline 199
- **a/tCompCor** — Behzadi Y et al. (2007): https://doi.org/10.1016/j.neuroimage.2007.04.042 - **aCompCor refinement (WM/CSF split)** — Muschelli J et al. (2014): - Network accessline 200
https://doi.org/10.1016/j.neuroimage.2007.04.042 - Network accessline 201
- **aCompCor refinement (WM/CSF split)** — Muschelli J et al. (2014): https://doi.org/10.1016/j.neuroimage.2014.03.028 - **Motion parameter expansion** — Satterthwaite TD et al. (2013): - Network accessline 202
https://doi.org/10.1016/j.neuroimage.2014.03.028 - Network accessline 203
- **Motion parameter expansion** — Satterthwaite TD et al. (2013): https://doi.org/10.1016/j.neuroimage.2012.08.052 - **Crown / brain-edge PCA** — Provins C et al. (2022): - Network accessline 204
https://doi.org/10.1016/j.neuroimage.2012.08.052 - Network accessline 205
- **Crown / brain-edge PCA** — Provins C et al. (2022): https://doi.org/10.31219/osf.io/hz52v; Patriat R et al. (2017): https://doi.org/10.1016/j.neuroimage.2016.08.051 - Network accessline 206
https://doi.org/10.31219/osf.io/hz52v; Patriat R et al. (2017): - Network accessline 207
https://doi.org/10.1016/j.neuroimage.2016.08.051 - Network accessline 211
- **Nipype** — Gorgolewski KJ et al. (2011): https://doi.org/10.3389/fninf.2011.00013 + - Network accessline 212
https://doi.org/10.3389/fninf.2011.00013 + - Network accessline 213
https://doi.org/10.5281/zenodo.581704 - Network accessline 214
- **Nilearn** — Abraham A et al. (2014): https://doi.org/10.3389/fninf.2014.00014 - **NiBabel** — Brett M et al.: - Network accessline 215
https://doi.org/10.3389/fninf.2014.00014 - Network accessline 217
https://doi.org/10.5281/zenodo.60808 - Network accessline 221
- **HCP fsLR / grayordinates** — Glasser MF et al. (2016): https://doi.org/10.1038/nature18933 - Network accessline 222
https://doi.org/10.1038/nature18933 - Network accessline 226
- **Slice-timing referenced middle of TR + Power motion recommendation** — Power JD et al. (2017): https://doi.org/10.1371/journal.pone.0182939 - Network accessline 227
Power JD et al. (2017): https://doi.org/10.1371/journal.pone.0182939 - **Lesion cost-function masking** — Brett M et al. (2001): - Network accessline 228
https://doi.org/10.1371/journal.pone.0182939 - Network accessline 229
- **Lesion cost-function masking** — Brett M et al. (2001): https://doi.org/10.1006/nimg.2001.0845 - **Carpetplot QA** — Power JD (2016): - Network accessline 230
https://doi.org/10.1006/nimg.2001.0845 - Network accessline 232
https://doi.org/10.1016/j.neuroimage.2016.08.009 - Network accessline 237
- **Ciric R et al. (2017)** — Benchmarking confound-regression strategies: https://doi.org/10.1016/j.neuroimage.2017.03.020 - Network accessline 238
https://doi.org/10.1016/j.neuroimage.2017.03.020 - Network accessline 239
- **Parkes L et al. (2018)** — Evaluation of motion correction strategies: https://doi.org/10.1016/j.neuroimage.2017.12.073 - **Greve DN et al. (2013)** — Sources of noise in fMRI: - Network accessline 240
https://doi.org/10.1016/j.neuroimage.2017.12.073 - Network accessline 242
https://doi.org/10.1007/s11336-013-9344-2 - Network accessline 252
> The methods text is the auto-generated fMRIPrep citation boilerplate, > distributed as CC0 public-domain and intended to be used verbatim. See > https://www.nipreps.org/intro/transparency/#citation-boilerplates. - Network accessline 254
> https://www.nipreps.org/intro/transparency/#citation-boilerplates.
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/cli-reference.md
- Network accessline 166
| Flag | Type / Default | Description | |------|----------------|-------------| | `--fs-license-file` | file path | Path to FreeSurfer license.txt. Register free at https://surfer.nmr.mgh.harvard.edu/registration.html | - Network accessline 167
|------|----------------|-------------| | `--fs-license-file` | file path | Path to FreeSurfer license.txt. Register free at https://surfer.nmr.mgh.harvard.edu/registration.html | | `--fs-subjects-dir` | dir path | Existing FreeSurfer subje - Network accessline 168
| `--fs-license-file` | file path | Path to FreeSurfer license.txt. Register free at https://surfer.nmr.mgh.harvard.edu/registration.html |
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/installation.md
- Network accessline 48
Docker Hub tags: https://hub.docker.com/r/nipreps/fmriprep/tags/ - Network accessline 121
Extended HPC / TemplateFlow docs: https://www.nipreps.org/apps/singularity/ - Network accessline 122
https://www.nipreps.org/apps/singularity/ - Network accessline 151
git clone https://github.com/nipreps/fmriprep.git - Network accessline 211
Register (free): https://surfer.nmr.mgh.harvard.edu/registration.html - Network accessline 277
wget https://raw.githubusercontent.com/nipreps/fmriprep/master/scripts/fetch_templates.py - Network accessline 286
Apptainer + TemplateFlow guide: https://www.nipreps.org/apps/singularity/#templateflow-and-singularity - Network accessline 287
https://www.nipreps.org/apps/singularity/#templateflow-and-singularity
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/outputs.md
- Network accessline 8
Everything follows the [BIDS-Derivatives](https://bids-specification.readthedocs.io/en/stable/05-derivatives/01-introduction.html) - Network accessline 348
Filename entity dictionary: https://bids-specification.readthedocs.io/en/stable/appendices/entity-table.html - Network accessline 349
https://bids-specification.readthedocs.io/en/stable/appendices/entity-table.html
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/sdc-fieldmaps.md
- Network accessline 8
SDC in fMRIPrep is delegated to the **SDCFlows** package. Full theoretical reference: https://www.nipreps.org/sdcflows/master/api/sdcflows.workflows.fit.fieldmap.html - Network accessline 9
reference: https://www.nipreps.org/sdcflows/master/api/sdcflows.workflows.fit.fieldmap.html - Network accessline 33
BIDS fieldmap spec: https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/01-magnetic-resonance-imaging-data.html#types-of-fieldmaps - Network accessline 34
https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/01-magnetic-resonance-imaging-data.html#types-of-fieldmaps
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/spaces.md
- Network accessline 66
Full template catalog: https://www.templateflow.org - Network accessline 107
`cohort-2` for MNIPediatricAsym = prepuberty phase (4.5–8.5 y). See the template description JSON at https://github.com/templateflow/tpl-MNIPediatricAsym. - Network accessline 109
https://github.com/templateflow/tpl-MNIPediatricAsym. - Network accessline 182
Full guide: https://www.templateflow.org/python-client/tutorials.html - Network accessline 245
wget https://raw.githubusercontent.com/nipreps/fmriprep/master/scripts/fetch_templates.py
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/troubleshooting-faq.md
- Network accessline 58
Related issues: [nipreps/smriprep#12](https://github.com/nipreps/smriprep/issues/12), - Network accessline 59
[nipreps/smriprep#12](https://github.com/nipreps/smriprep/issues/12), - Network accessline 60
[nipreps/fmriprep#939](https://github.com/nipreps/fmriprep/issues/939). - Network accessline 78
NeuroStars threads: - https://neurostars.org/t/memory-issue-when-processing-large-amount-of-data/2562 - Network accessline 79
- https://neurostars.org/t/memory-issue-when-processing-large-amount-of-data/2562 - Network accessline 80
- https://neurostars.org/t/how-much-ram-cpus-is-reasonable-to-run-pipelines-like-fmriprep/1086 - Network accessline 81
- https://neurostars.org/t/memory-allocation-issues-with-fmriprep-singularity-and-hpc/2759 - Network accessline 82
- https://neurostars.org/t/fmriprep-v1-0-12-hanging/1661 - Dangerous shell operationline 120
rm -f <output_dir>/sourcedata/freesurfer/sub-XX/scripts/IsRunning.* - Network accessline 127
Full FreeSurfer explanation: https://surfer.nmr.mgh.harvard.edu/fswiki/RunningFreeSurferInParallel - Network accessline 128
https://surfer.nmr.mgh.harvard.edu/fswiki/RunningFreeSurferInParallel - Network accessline 152
Detailed workaround: https://neurostars.org/t/updated-fmriprep-workaround-for-running-subjects-in-parallel/6677 - Network accessline 153
https://neurostars.org/t/updated-fmriprep-workaround-for-running-subjects-in-parallel/6677 - Network accessline 185
Live list: https://github.com/nipreps/fmriprep/blob/master/.versions.json - Network accessline 186
https://github.com/nipreps/fmriprep/blob/master/.versions.json - Network accessline 206
Full guide: https://www.nipreps.org/apps/singularity/ - Network accessline 277
NeuroStars long thread on the "anatomical fast-track" pattern: https://neurostars.org/t/fmriprep-how-to-reuse-longitudinal-and-pre-run-freesurfer/4585/15 - Network accessline 278
https://neurostars.org/t/fmriprep-how-to-reuse-longitudinal-and-pre-run-freesurfer/4585/15 - Network accessline 371
Register (free): https://surfer.nmr.mgh.harvard.edu/registration.html - Network accessline 399
Deep dive: https://reproducibility.stanford.edu/slice-timing-correction-in-fmriprep-and-linear-modeling/ - Network accessline 400
https://reproducibility.stanford.edu/slice-timing-correction-in-fmriprep-and-linear-modeling/ - Network accessline 407
1. Update to the latest patch of the same minor version (e.g. 25.2.x). 2. Check the flagged versions list (`.versions.json`). 3. Search NeuroStars: https://neurostars.org/tag/fmriprep - Network accessline 408
2. Check the flagged versions list (`.versions.json`). 3. Search NeuroStars: https://neurostars.org/tag/fmriprep 4. Check open + closed GitHub issues: https://github.com/nipreps/fmriprep/issues - Network accessline 409
3. Search NeuroStars: https://neurostars.org/tag/fmriprep - Network accessline 410
4. Check open + closed GitHub issues: https://github.com/nipreps/fmriprep/issues - Network accessline 418
Issue tracker: https://github.com/nipreps/fmriprep/issues - Network accessline 419
Support forum (preferred for usage questions): https://neurostars.org/tag/fmriprep
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/usage-examples.md
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/versions-dependencies.md
- Network accessline 24
- **Python required**: 3.10 – 3.13 (container uses **3.12**) - **Version scheme**: `nipreps-calver` (calendar-based; `YY.M.PATCH`). - **Repo**: https://github.com/nipreps/fmriprep - Network accessline 26
- **Repo**: https://github.com/nipreps/fmriprep - Network accessline 110
| Package | Role | Repo | |---------|------|------| | `niworkflows` | Shared Nipype interfaces and utility workflows | https://github.com/nipreps/niworkflows | - Network accessline 111
|---------|------|------| | `niworkflows` | Shared Nipype interfaces and utility workflows | https://github.com/nipreps/niworkflows | | `smriprep` | Anatomical (T1w/T2w) preprocessing sub-workflow | https://github.com/nipreps/smriprep | - Network accessline 112
| `niworkflows` | Shared Nipype interfaces and utility workflows | https://github.com/nipreps/niworkflows | - Network accessline 113
| `smriprep` | Anatomical (T1w/T2w) preprocessing sub-workflow | https://github.com/nipreps/smriprep | - Network accessline 114
| `sdcflows` | Susceptibility-distortion correction | https://github.com/nipreps/sdcflows | - Network accessline 115
| `nireports` | HTML report generation + reportlets | https://github.com/nipreps/nireports | - Network accessline 116
| `nitransforms` | ITK/ANTs/FreeSurfer transform I/O and application | https://github.com/nipreps/nitransforms | - Network accessline 117
| `templateflow` | Template registry / fetcher | https://github.com/templateflow/templateflow | - Network accessline 118
| `tedana` | Multi-echo T2* fitting + denoising | https://github.com/ME-ICA/tedana | - Dangerous shell operationline 181
docker rm tmp - Network accessline 201
| 1.0.1 – 20.0.5 (many) | Phase-difference fieldmap bug (some also had Nipype instability at 1.5.x) | | 20.0.0rc1 – 20.0.2 | fsLR resampling error when `--cifti-output` was used | | 20.1.0 – 20.2.1 | Functional outputs in standard space can - Network accessline 203
| 20.1.0 – 20.2.1 | Functional outputs in standard space can be wrong depending on orientation headers (see [issue #2307](https://github.com/nipreps/fmriprep/issues/2307)) | - Network accessline 205
Live authoritative list: https://github.com/nipreps/fmriprep/blob/master/.versions.json - Network accessline 206
https://github.com/nipreps/fmriprep/blob/master/.versions.json - Network accessline 227
Release notes for every version live in `CHANGES.rst` in the repo and on https://fmriprep.readthedocs.io/en/latest/changes.html. - Network accessline 228
https://fmriprep.readthedocs.io/en/latest/changes.html.
packages/skills/skills/06_fMRI_Neuroimaging/fmriprep/references/workflows.md
- Network accessline 379
Sample report: https://fmriprep.org/en/latest/_static/SampleReport/sample_report.html
packages/skills/skills/06_fMRI_Neuroimaging/netneurotools-guide/SKILL.md
- Access to secretsline 212
[Credential-related source omitted]
packages/skills/skills/06_fMRI_Neuroimaging/neural-decoding-analysis/SKILL.md
- Network accessline 51
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/07_Computational_Modeling/act-r-model-builder/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/07_Computational_Modeling/bayesian-cognitive-model-builder/SKILL.md
- Network accessline 61
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/07_Computational_Modeling/parameter-recovery-checker/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/08_Computational_Neuroscience/brain-connectivity-modeler/SKILL.md
- Network accessline 57
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/08_Computational_Neuroscience/neural-decoding-analysis/SKILL.md
- Network accessline 51
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/08_Computational_Neuroscience/neural-population-analysis-guide/SKILL.md
- Network accessline 66
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/08_Computational_Neuroscience/spiking-network-model-builder/SKILL.md
- Network accessline 65
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/SKILL.md
- Network accessline 18
.licenses/alphafold_database_fetch_and_analyze_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://alphafold.ebi.ac.uk/, then (2) create the file - Network accessline 19
exist in the workspace root directory then (1) prominently notify the user to check the terms at https://alphafold.ebi.ac.uk/, then (2) create the file recording the notification text and timestamp. - Network accessline 20
to check the terms at https://alphafold.ebi.ac.uk/, then (2) create the file - Network accessline 32
- The user only has a protein name, gene name, or amino acid sequence (no UniProt ID) — ask them to look up the ID on [UniProt](https://www.uniprot.org). - Network accessline 33
UniProt ID) — ask them to look up the ID on [UniProt](https://www.uniprot.org). - The user wants to search for structural homologs (use **Foldseek**). - Network accessline 34
[UniProt](https://www.uniprot.org).
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/references/citation.bib
- Network accessline 1
@ARTICLE{Varadi2022, ABSTRACT = {The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of - Network accessline 2
ABSTRACT = {The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabl - Network accessline 3
AUTHOR = {Varadi, Mihaly and Anyango, Stephen and Deshpande, Mandar and Nair, Sreenath and Natassia, Cindy and Yordanova, Galabina and Yuan, David and Stroe, Oana and Wood, Gemma and Laydon, Agata and Žídek, Augustin and Green, Tim and Tuny - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkab1061}, - Network accessline 5
DATE = {2022-01}, DOI = {10.1093/nar/gkab1061}, EPRINT = {https://academic.oup.com/nar/article-pdf/50/D1/D439/43502749/gkab1061.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkab1061}, EPRINT = {https://academic.oup.com/nar/article-pdf/50/D1/D439/43502749/gkab1061.pdf}, ISSN = {0305-1048}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/50/D1/D439/43502749/gkab1061.pdf}, - Network accessline 16
@ARTICLE{Varadi2024, ABSTRACT = {The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expand - Network accessline 17
ABSTRACT = {The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 30 - Network accessline 18
AUTHOR = {Varadi, Mihaly and Bertoni, Damian and Magana, Paulyna and Paramval, Urmila and Pidruchna, Ivanna and Radhakrishnan, Malarvizhi and Tsenkov, Maxim and Nair, Sreenath and Mirdita, Milot and Yeo, Jingi and Kovalevskiy, Oleg and Tuny - Network accessline 19
URL = {https://doi.org/10.1093/nar/gkad1011}, - Network accessline 20
DATE = {2024-01}, DOI = {10.1093/nar/gkad1011}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D368/55039845/gkad1011.pdf}, - Network accessline 21
DOI = {10.1093/nar/gkad1011}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D368/55039845/gkad1011.pdf}, ISSN = {0305-1048}, - Network accessline 22
EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D368/55039845/gkad1011.pdf}, - Network accessline 32
ABSTRACT = {Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1--4, the structures of around 100,000 unique proteins have b - Network accessline 33
AUTHOR = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and Žídek, Augustin and Potapenko, Anna and Bridgland, Alex and Meyer, - Network accessline 34
URL = {https://doi.org/10.1038/s41586-021-03819-2}, - Network accessline 46
ABSTRACT = {Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17{\% - Network accessline 47
AUTHOR = {Tunyasuvunakool, Kathryn and Adler, Jonas and Wu, Zachary and Green, Tim and Zielinski, Michal and Žídek, Augustin and Bridgland, Alex and Cowie, Andrew and Meyer, Clemens and Laydon, Agata and Velankar, Sameer and Kleywegt, Gerar - Network accessline 48
URL = {https://doi.org/10.1038/s41586-021-03828-1},
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/scripts/analyze_pae.py
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/scripts/analyze_plddt.py
packages/skills/skills/09_Cellular_Molecular_Neuroscience/alphafold-database-fetch-and-analyze/scripts/fetch_structure.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 30
CLIENT = http_client.HttpClient("https://alphafold.ebi.ac.uk", qps=1.0) - Network accessline 35
uniprot_id = uniprot_id.strip().upper() api_url = f"https://alphafold.ebi.ac.uk/api/prediction/{uniprot_id}" - Network accessline 36
api_url = f"https://alphafold.ebi.ac.uk/api/prediction/{uniprot_id}"
packages/skills/skills/09_Cellular_Molecular_Neuroscience/calcium-imaging-analysis-guide/SKILL.md
- Network accessline 50
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/09_Cellular_Molecular_Neuroscience/calcium-imaging-analysis-guide/references/pipeline-details.md
- Network accessline 11
- **Language**: Python - **Modality**: Primarily 2P; 1P support via preprocessing - **Repository**: [MouseLand/suite2p](https://github.com/MouseLand/suite2p) - Network accessline 12
- **Modality**: Primarily 2P; 1P support via preprocessing - **Repository**: [MouseLand/suite2p](https://github.com/MouseLand/suite2p) - **Key features**: - Network accessline 13
- **Repository**: [MouseLand/suite2p](https://github.com/MouseLand/suite2p) - Network accessline 25
- **Language**: Python (MATLAB version also available) - **Modality**: 2P and 1P (via CNMF-E mode) - **Repository**: [flatironinstitute/CaImAn](https://github.com/flatironinstitute/CaImAn) - Network accessline 26
- **Modality**: 2P and 1P (via CNMF-E mode) - **Repository**: [flatironinstitute/CaImAn](https://github.com/flatironinstitute/CaImAn) - **Key features**: - Network accessline 27
- **Repository**: [flatironinstitute/CaImAn](https://github.com/flatironinstitute/CaImAn) - Network accessline 55
- **Language**: MATLAB - **Modality**: 1P / miniscope only - **Repository**: [JinghaoLu/MIN1PIPE](https://github.com/JinghaoLu/MIN1PIPE) - Network accessline 56
- **Modality**: 1P / miniscope only - **Repository**: [JinghaoLu/MIN1PIPE](https://github.com/JinghaoLu/MIN1PIPE) - **Key features**: - Network accessline 57
- **Repository**: [JinghaoLu/MIN1PIPE](https://github.com/JinghaoLu/MIN1PIPE)
packages/skills/skills/09_Cellular_Molecular_Neuroscience/gtex-database/SKILL.md
- Network accessline 20
2. **User Notification**: If .licenses/gtex_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://gtexportal.org/home/license and - Network accessline 21
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://gtexportal.org/home/license and https://gtexportal.org/home/documentationPage#gtexApi, then (2) create the - Network accessline 22
the user to check the terms at https://gtexportal.org/home/license and - Network accessline 23
https://gtexportal.org/home/documentationPage#gtexApi, then (2) create the
packages/skills/skills/09_Cellular_Molecular_Neuroscience/gtex-database/references/citation.bib
- Network accessline 3
AUTHOR = {{The GTEx Consortium} and Aguet, François and Anand, Shankara and Ardlie, Kristin G. and Gabriel, Stacey and Getz, Gad A. and Graubert, Aaron and Hadley, Kane and Handsaker, Robert E. and Huang, Katherine H. and Kashin, Seva and L - Network accessline 4
URL = {https://www.science.org/doi/abs/10.1126/science.aaz1776}, - Network accessline 5
DATE = {2020}, DOI = {10.1126/science.aaz1776}, EPRINT = {https://www.science.org/doi/pdf/10.1126/science.aaz1776}, - Network accessline 6
DOI = {10.1126/science.aaz1776}, EPRINT = {https://www.science.org/doi/pdf/10.1126/science.aaz1776}, JOURNALTITLE = {Science}, - Network accessline 7
EPRINT = {https://www.science.org/doi/pdf/10.1126/science.aaz1776},
packages/skills/skills/09_Cellular_Molecular_Neuroscience/gtex-database/scripts/gtex_cli.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 35
BASE_URL = 'https://gtexportal.org/api/v2'
packages/skills/skills/09_Cellular_Molecular_Neuroscience/human-protein-atlas-database/SKILL.md
- Network accessline 23
does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.proteinatlas.org/about/licence, then (2) create the file - Network accessline 24
notify the user to check the terms at https://www.proteinatlas.org/about/licence, then (2) create the file recording the notification text and timestamp. - Network accessline 25
https://www.proteinatlas.org/about/licence, then (2) create the file
packages/skills/skills/09_Cellular_Molecular_Neuroscience/human-protein-atlas-database/references/citation.bib
- Network accessline 2
ABSTRACT = {Sequencing the human genome gave new insights into human biology and disease. However, the ultimate goal is to understand the dynamic expression of each of the approximately 20,000 protein-coding genes and the function of each p - Network accessline 3
AUTHOR = {Uhlén, Mathias and Fagerberg, Linn and Hallström, Björn M. and Lindskog, Cecilia and Oksvold, Per and Mardinoglu, Adil and Sivertsson, Åsa and Kampf, Caroline and Sjöstedt, Evelina and Asplund, Anna and Olsson, IngMarie and Edlund - Network accessline 4
URL = {https://www.science.org/doi/abs/10.1126/science.1260419}, - Network accessline 5
DATE = {2015}, DOI = {10.1126/science.1260419}, EPRINT = {https://www.science.org/doi/pdf/10.1126/science.1260419}, - Network accessline 6
DOI = {10.1126/science.1260419}, EPRINT = {https://www.science.org/doi/pdf/10.1126/science.1260419}, JOURNALTITLE = {Science}, - Network accessline 7
EPRINT = {https://www.science.org/doi/pdf/10.1126/science.1260419},
packages/skills/skills/09_Cellular_Molecular_Neuroscience/human-protein-atlas-database/scripts/hpa_cli.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 35
BASE_URL = 'https://www.proteinatlas.org/' - Network accessline 89
# The XML namespace is usually specified, e.g., # xmlns="http://www.proteinatlas.org/search/download/proteinatlas.xsd" - Network accessline 90
# xmlns="http://www.proteinatlas.org/search/download/proteinatlas.xsd"
packages/skills/skills/09_Cellular_Molecular_Neuroscience/optogenetics-protocol-designer/SKILL.md
- Network accessline 50
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/SKILL.md
- Network accessline 17
2. **User Notification**: If .licenses/pdb_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.rcsb.org/pages/usage-policy, then - Network accessline 18
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.rcsb.org/pages/usage-policy, then (2) create the file recording the notification text and timestamp. - Network accessline 19
the user to check the terms at https://www.rcsb.org/pages/usage-policy, then - Network accessline 117
See https://search.rcsb.org/#search-services for more details.
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/references/citation.bib
- Network accessline 1
@ARTICLE{Berman2000, ABSTRACT = {The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for d - Network accessline 2
ABSTRACT = {The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and acce - Network accessline 3
AUTHOR = {Berman, Helen M. and Westbrook, John and Feng, Zukang and Gilliland, Gary and Bhat, T. N. and Weissig, Helge and Shindyalov, Ilya N. and Bourne, Philip E.}, URL = {https://doi.org/10.1093/nar/28.1.235}, DATE = {2000-01}, - Network accessline 4
URL = {https://doi.org/10.1093/nar/28.1.235}, - Network accessline 5
DATE = {2000-01}, DOI = {10.1093/nar/28.1.235}, EPRINT = {https://academic.oup.com/nar/article-pdf/28/1/235/9895144/280235.pdf}, - Network accessline 6
DOI = {10.1093/nar/28.1.235}, EPRINT = {https://academic.oup.com/nar/article-pdf/28/1/235/9895144/280235.pdf}, ISSN = {0305-1048}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/28/1/235/9895144/280235.pdf},
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/scripts/download_coordinate_files.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 31
CLIENT = http_client.HttpClient("https://files-beta.rcsb.org", qps=5.0) - Network accessline 49
"**Check with the user**, then consider downloading a copy of all" f" {args.format} files using the recommended bulk script at " "https://cdn.rcsb.org/wwpdb/docs/BetaArchiveBatchDownloader.py.", - Network accessline 50
f" {args.format} files using the recommended bulk script at " "https://cdn.rcsb.org/wwpdb/docs/BetaArchiveBatchDownloader.py.", file=sys.stderr, - Network accessline 51
"https://cdn.rcsb.org/wwpdb/docs/BetaArchiveBatchDownloader.py.",
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/scripts/fetch_pdb_metadata.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 30
CLIENT = http_client.HttpClient("https://data.rcsb.org", qps=2.0) - Network accessline 39
encoded_query = urllib.parse.quote(args.query.strip()) url = f"https://data.rcsb.org/graphql?query={encoded_query}" - Network accessline 40
url = f"https://data.rcsb.org/graphql?query={encoded_query}"
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/scripts/fetch_schema.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 29
SEARCH_CLIENT = http_client.HttpClient("https://search.rcsb.org", qps=2.0) - Network accessline 30
DATA_CLIENT = http_client.HttpClient("https://data.rcsb.org", qps=2.0) - Network accessline 33
API_URLS = { "search_structure": "https://search.rcsb.org/rcsbsearch/v2/metadata/schema", - Network accessline 34
"search_structure": "https://search.rcsb.org/rcsbsearch/v2/metadata/schema", - Network accessline 35
"search_chemical": ( "https://search.rcsb.org/rcsbsearch/v2/metadata/chemical/schema" ), - Network accessline 36
"https://search.rcsb.org/rcsbsearch/v2/metadata/chemical/schema" - Network accessline 37
), "data_entry": "https://data.rcsb.org/rest/v1/schema/entry", "data_polymer_entity": ( - Network accessline 38
"data_entry": "https://data.rcsb.org/rest/v1/schema/entry", - Network accessline 39
"data_polymer_entity": ( "https://data.rcsb.org/rest/v1/schema/polymer_entity" ), - Network accessline 40
"https://data.rcsb.org/rest/v1/schema/polymer_entity" - Network accessline 41
), "data_polymer_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/polymer_entity_instance" - Network accessline 42
"data_polymer_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/polymer_entity_instance" ), - Network accessline 43
"https://data.rcsb.org/rest/v1/schema/polymer_entity_instance" - Network accessline 44
), "data_assembly": "https://data.rcsb.org/rest/v1/schema/assembly", "data_non_polymer_entity": ( - Network accessline 45
"data_assembly": "https://data.rcsb.org/rest/v1/schema/assembly", - Network accessline 46
"data_non_polymer_entity": ( "https://data.rcsb.org/rest/v1/schema/nonpolymer_entity" ), - Network accessline 47
"https://data.rcsb.org/rest/v1/schema/nonpolymer_entity" - Network accessline 48
), "data_non_polymer_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/nonpolymer_entity_instance" - Network accessline 49
"data_non_polymer_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/nonpolymer_entity_instance" ), - Network accessline 50
"https://data.rcsb.org/rest/v1/schema/nonpolymer_entity_instance" - Network accessline 51
), "data_branched_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/branched_entity_instance" - Network accessline 52
"data_branched_entity_instance": ( "https://data.rcsb.org/rest/v1/schema/branched_entity_instance" ), - Network accessline 53
"https://data.rcsb.org/rest/v1/schema/branched_entity_instance" - Network accessline 54
), "data_branched_entity": ( "https://data.rcsb.org/rest/v1/schema/branched_entity" - Network accessline 55
"data_branched_entity": ( "https://data.rcsb.org/rest/v1/schema/branched_entity" ), - Network accessline 56
"https://data.rcsb.org/rest/v1/schema/branched_entity" - Network accessline 57
), "data_chemical_component": "https://data.rcsb.org/rest/v1/schema/chem_comp", } - Network accessline 58
"data_chemical_component": "https://data.rcsb.org/rest/v1/schema/chem_comp",
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pdb-database/scripts/search_pdb.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 35
CLIENT = http_client.HttpClient("https://search.rcsb.org", qps=2.0) - Network accessline 89
json_payload = json.dumps(payload, separators=(",", ":")) encoded_query = urllib.parse.quote(json_payload) url = f"https://search.rcsb.org/rcsbsearch/v2/query?json={encoded_query}" - Network accessline 91
url = f"https://search.rcsb.org/rcsbsearch/v2/query?json={encoded_query}"
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pymol/SKILL.md
- Network accessline 18
2. **User Notification**: If .licenses/pymol_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the license at https://www.pymol.org/, then (2) create the file - Network accessline 19
in the workspace root directory then (1) prominently notify the user to check the license at https://www.pymol.org/, then (2) create the file recording the notification text and timestamp. - Network accessline 20
check the license at https://www.pymol.org/, then (2) create the file - Access to secretsline 90
[Credential-related source omitted]
packages/skills/skills/09_Cellular_Molecular_Neuroscience/pymol/references/PYMOL_REFERENCE.md
- Network accessline 138
container will time out. 2. **Selection case sensitivity** — `"chain a"` is NOT the same as `"chain A"`. 3. **`cmd.fetch()` will fail** — there is no network inside the container. Use - Network accessline 139
2. **Selection case sensitivity** — `"chain a"` is NOT the same as `"chain A"`. 3. **`cmd.fetch()` will fail** — there is no network inside the container. Use `cmd.load()` with pre-downloaded files. - Network accessline 140
3. **`cmd.fetch()` will fail** — there is no network inside the container. Use
packages/skills/skills/10_Clinical_Neuropsychology/lesion-symptom-mapping-guide/SKILL.md
- Network accessline 67
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/10_Clinical_Neuropsychology/neuropsych-battery-selector/SKILL.md
- Network accessline 63
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/11_Developmental_Cognition/infant-looking-time-designer/SKILL.md
- Network accessline 49
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/12_Social_Cognition/tom-task-selector/SKILL.md
- Network accessline 47
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome
packages/skills/skills/13_Visualization/nature-figure/README.md
- Network accessline 16
Derived from production scripts in [figures4papers](https://github.com/ChenLiu-1996/figures4papers)
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_CellSpliceNet/plot_ablation.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_CellSpliceNet/plot_comparison.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Cflows/diffusion_swiss_roll.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Cflows/plot_comparison_Ablation.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Cflows/plot_comparison_GeneRegulatory.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Cflows/plot_comparison_Trajectory.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Dispersion/plot_idea.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_Dispersion/plot_illustration.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_FPGM/plot_freq_prior.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_ImmunoStruct/plot_bars.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_ImmunoStruct/raw_data.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_RNAGenScape/plot_comparison.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_RNAGenScape/plot_hole_manifold.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_RNAGenScape/plot_manifold.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_RNAGenScape/plot_sweep.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_VIGIL/plot_comparison_radar.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_VIGIL/plot_posttraining.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_brainteaser/plot_brute_force.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_brainteaser/plot_correctness_by_category.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_brainteaser/plot_correctness_by_subcategory.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_brainteaser/plot_rewriting.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_brainteaser/plot_selfcorrection_math.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_ophthal_review/plot_composition.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/assets/figures4papers/figure_ophthal_review/plot_trend.py
- Executable scriptline 1
Executable file
packages/skills/skills/13_Visualization/nature-figure/references/demos.md
packages/skills/skills/13_Visualization/nature-figure/references/design-theory.md
- Network accessline 3
Derived from scripts in the [figures4papers](https://github.com/ChenLiu-1996/figures4papers) repository
packages/skills/skills/13_Visualization/nature-figure/references/qa-contract.md
- Network accessline 10
- Nature research figure guide: `https://research-figure-guide.nature.com/` - Network accessline 11
- Nature building/exporting panels: `https://research-figure-guide.nature.com/figures/building-and-exporting-figure-panels/` - Network accessline 12
- Nature preparing figures/specifications: `https://research-figure-guide.nature.com/figures/preparing-figures-our-specifications/` - Network accessline 13
- Nature initial submission and statistics guidance: `https://www.nature.com/nature/for-authors/initial-submission` - Network accessline 14
- Nature formatting guide: `https://www.nature.com/nature/for-authors/formatting-guide` - Network accessline 15
- Journal of Cell Biology figure/video guidelines for microscopy-oriented image QA: `https://rupress.org/jcb/pages/fig-vid-guidelines` - Network accessline 16
- Elsevier/Cell-family image-manipulation baseline: `https://www.sciencedirect.com/journal/the-cell-surface/publish/guide-for-authors`
packages/skills/skills/14_Writing/markdown-report-writing/SKILL.md
packages/skills/skills/14_Writing/markdown-report-writing/references/templates.md
- Possible obfuscationline 62
<U+200B>```mermaid - Possible obfuscationline 68
<U+200B>``` - Possible obfuscationline 167
<U+200B>```mermaid - Possible obfuscationline 173
<U+200B>``` - Possible obfuscationline 248
<U+200B>```bash - Possible obfuscationline 250
<U+200B>``` - Possible obfuscationline 254
<U+200B>```bash - Possible obfuscationline 256
<U+200B>``` - Possible obfuscationline 260
<U+200B>```bash - Possible obfuscationline 262
<U+200B>``` - Possible obfuscationline 266
<U+200B>```mermaid - Possible obfuscationline 271
<U+200B>```
packages/skills/skills/15_Others/neuroimaging-power-guide/SKILL.md
- Network accessline 56
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 196
**Advantage**: Does not require individual subject data; can use published group maps **URL**: https://neuropowertools.org - Network accessline 197
**URL**: https://neuropowertools.org
packages/skills/skills/15_Others/neuroimaging-sample-size-calculator/SKILL.md
- Network accessline 55
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please [open an issue](https://github.com/HaoxuanLiTHUAI/awesome - Network accessline 165
| Method | Fits mixture model to peak distribution; estimates prevalence and effect size | | Output | Power estimates at varying N; optimal sample size for target power | | Access | Web-based: https://neuropowertools.org | - Network accessline 166
| Output | Power estimates at varying N; optimal sample size for target power | | Access | Web-based: https://neuropowertools.org | | Strengths | Does not require individual subject data; works with published maps | - Network accessline 167
| Access | Web-based: https://neuropowertools.org |
packages/skills/skills/16_Animal_Behavior/deeplabcut/SKILL.md
- Network accessline 6
- "Claude (AI-assisted)" review_status: "ai-generated" source: "https://github.com/DeepLabCut/DeepLabCut" - Network accessline 7
review_status: "ai-generated" source: "https://github.com/DeepLabCut/DeepLabCut" --- - Network accessline 8
source: "https://github.com/DeepLabCut/DeepLabCut" - Network accessline 149
1. **Wrong PyTorch version**: Always install PyTorch BEFORE deeplabcut. Check [pytorch.org](https://pytorch.org) for the correct CUDA version.
packages/skills/skills/17_Literature_Databases/literature-search-arxiv/SKILL.md
- Network accessline 17
not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://info.arxiv.org/help/api/index.html and to always check the license - Network accessline 18
notify the user to check the terms at https://info.arxiv.org/help/api/index.html and to always check the license of the papers retrieved by the skill for any restrictions, then (2) create - Network accessline 19
https://info.arxiv.org/help/api/index.html and to always check the license
packages/skills/skills/17_Literature_Databases/literature-search-arxiv/references/citation.bib
- Network accessline 12
@ONLINE{arXiv2026, AUTHOR = {{arXiv}}, URL = {https://info.arxiv.org/help/api/index.html}, - Network accessline 13
AUTHOR = {{arXiv}}, URL = {https://info.arxiv.org/help/api/index.html}, TITLE = {{arXiv API Access}}, - Network accessline 14
URL = {https://info.arxiv.org/help/api/index.html},
packages/skills/skills/17_Literature_Databases/literature-search-arxiv/scripts/download_paper.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 34
_CLIENT = http_client.HttpClient("https://arxiv.org/", qps=1.0 / 3.0) - Network accessline 78
if args.format == "pdf": url = f"https://arxiv.org/pdf/{paper_id}.pdf" - Network accessline 79
url = f"https://arxiv.org/pdf/{paper_id}.pdf" - Network accessline 80
elif args.format == "html": url = f"https://arxiv.org/html/{paper_id}" else: - Network accessline 81
url = f"https://arxiv.org/html/{paper_id}"
packages/skills/skills/17_Literature_Databases/literature-search-arxiv/scripts/download_paper_source.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 34
_CLIENT = http_client.HttpClient("https://export.arxiv.org/", qps=1.0 / 3.0) - Network accessline 73
url = f"https://export.arxiv.org/e-print/{paper_id}" print(f"Attempting to download source from {url}...")
packages/skills/skills/17_Literature_Databases/literature-search-arxiv/scripts/search_arxiv.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 37
_BASE_URL = "http://export.arxiv.org/api/query?" - Network accessline 114
for entry in root.findall("{http://www.w3.org/2005/Atom}entry"): - Network accessline 121
# Extract just the ID part (e.g., http://arxiv.org/abs/2305.10601v1 - Network accessline 134
paper["published"] = child.text elif tag == "author": for name_node in child.findall("{http://www.w3.org/2005/Atom}name"): - Network accessline 135
elif tag == "author": for name_node in child.findall("{http://www.w3.org/2005/Atom}name"): authors.append(name_node.text) - Network accessline 136
for name_node in child.findall("{http://www.w3.org/2005/Atom}name"):
packages/skills/skills/17_Literature_Databases/literature-search-biorxiv/SKILL.md
- Network accessline 17
2. **User Notification**: If .licenses/literature_search_biorxiv_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://api.biorxiv.org/ and - Network accessline 18
does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://api.biorxiv.org/ and https://www.biorxiv.org/content/about-biorxiv and to always check the - Network accessline 19
notify the user to check the terms at https://api.biorxiv.org/ and - Network accessline 20
https://www.biorxiv.org/content/about-biorxiv and to always check the
packages/skills/skills/17_Literature_Databases/literature-search-biorxiv/references/citation.bib
- Network accessline 3
AUTHOR = {Sever, Richard and Hindle, Samantha and Roeder, Ted and Fereres, Sol and Fernández Gayol, Olaya and Ghosh, Sanchari and Proietti Onori, Martina and Croushore, Emma and Black, Kevin-John and Sussman, Linda and Argentine, Janet and - Network accessline 4
PUBLISHER = {Cold Spring Harbor Laboratory}, URL = {https://www.biorxiv.org/content/early/2026/02/26/833400}, DATE = {2026}, - Network accessline 5
URL = {https://www.biorxiv.org/content/early/2026/02/26/833400}, - Network accessline 6
DATE = {2026}, DOI = {10.1101/833400}, EPRINT = {https://www.biorxiv.org/content/early/2026/02/26/833400.full.pdf}, - Network accessline 7
DOI = {10.1101/833400}, EPRINT = {https://www.biorxiv.org/content/early/2026/02/26/833400.full.pdf}, JOURNALTITLE = {bioRxiv}, - Network accessline 8
EPRINT = {https://www.biorxiv.org/content/early/2026/02/26/833400.full.pdf},
packages/skills/skills/17_Literature_Databases/literature-search-biorxiv/scripts/search_by_dates.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 29
client = http_client.HttpClient(base_url="https://api.biorxiv.org/", qps=1.0) - Network accessline 135
base_url = ( f"https://api.biorxiv.org/details/{args.server}" - Network accessline 136
f"https://api.biorxiv.org/details/{args.server}"
packages/skills/skills/17_Literature_Databases/literature-search-biorxiv/scripts/search_by_doi.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 29
_CLIENT = http_client.HttpClient(base_url="https://api.biorxiv.org/", qps=1.0) - Network accessline 35
doi = args.doi.replace("https://doi.org/", "").replace("http://doi.org/", "") - Network accessline 36
url = f"https://api.biorxiv.org/details/{args.server}/{doi}"
packages/skills/skills/17_Literature_Databases/literature-search-europepmc/SKILL.md
- Network accessline 11
A skill for searching, downloading, and exploring open-access papers from [Europe PMC](https://europepmc.org/) — a comprehensive, free life-science - Network accessline 12
[Europe PMC](https://europepmc.org/) — a comprehensive, free life-science - Network accessline 20
2. **User Notification**: If .licenses/literature_search_europepmc_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://europepmc.org/ and to always - Network accessline 21
does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://europepmc.org/ and to always check the license of the papers retrieved by the skill for any restrictions, - Network accessline 22
notify the user to check the terms at https://europepmc.org/ and to always - Network accessline 49
Search Europe PMC by query. Supports DOI lookup, keyword search, author search, PMID lookup, and the full [Europe PMC search syntax](https://europepmc.org/searchsyntax). - Network accessline 51
[Europe PMC search syntax](https://europepmc.org/searchsyntax).
packages/skills/skills/17_Literature_Databases/literature-search-europepmc/references/citation.bib
- Network accessline 1
@ARTICLE{Rosonovski2024, ABSTRACT = {Europe PMC (https://europepmc.org/) is an open access database of life science journal articles and preprints, which contains over 42 million abstracts and over 9 million full text articles accessible - Network accessline 2
ABSTRACT = {Europe PMC (https://europepmc.org/) is an open access database of life science journal articles and preprints, which contains over 42 million abstracts and over 9 million full text articles accessible via the website, APIs and b - Network accessline 3
AUTHOR = {Rosonovski, Summer and Levchenko, Maria and Bhatnagar, Rajat and Chandrasekaran, Umamageswari and Faulk, Lynne and Hassan, Islam and Jeffryes, Matt and Mubashar, Syed Irtaza and Nassar, Maaly and Jayaprabha Palanisamy, Madhumietha - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkad1085}, - Network accessline 5
DATE = {2024-01}, DOI = {10.1093/nar/gkad1085}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1668/55040834/gkad1085.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkad1085}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1668/55040834/gkad1085.pdf}, ISSN = {0305-1048}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1668/55040834/gkad1085.pdf},
packages/skills/skills/17_Literature_Databases/literature-search-europepmc/scripts/europepmc_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 41
_API_BASE = "https://www.ebi.ac.uk/europepmc/webservices/rest/" - Network accessline 42
_PDF_BASE = "https://europepmc.org/" - Network accessline 45
_API_BASE, qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc", - Network accessline 46
qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc", ) - Network accessline 47
referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc", - Network accessline 50
_PDF_BASE, qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc", - Network accessline 51
qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc", ) - Network accessline 52
referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-europepmc",
packages/skills/skills/17_Literature_Databases/literature-search-openalex/SKILL.md
- Network accessline 18
2. **User Notification**: If .licenses/literature_search_openalex_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://developers.openalex.org/ and - Network accessline 19
does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://developers.openalex.org/ and to always check the license of the papers retrieved by the skill for any - Network accessline 20
notify the user to check the terms at https://developers.openalex.org/ and - Access to secretsline 26
[Credential-related source omitted] - Access to secretsline 46
[Credential-related source omitted] - Network accessline 130
# DOI lookup uv run scripts/openalex_cli.py get works "https://doi.org/10.1038/s41586-021-03819-2" - Network accessline 131
uv run scripts/openalex_cli.py get works "https://doi.org/10.1038/s41586-021-03819-2"
packages/skills/skills/17_Literature_Databases/literature-search-openalex/scripts/openalex_cli.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 45
BASE_URL = "https://api.openalex.org" - Network accessline 46
PDF_BASE_URL = "https://content.openalex.org" - Network accessline 49
BASE_URL, qps=10.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", - Network accessline 50
qps=10.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", ) - Network accessline 51
referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", - Network accessline 54
PDF_BASE_URL, qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", - Network accessline 55
qps=1.0, referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", ) - Network accessline 56
referer="https://github.com/google-deepmind/science-skills/tree/main/literature-search-openalex", - Access to secretsline 92
[Credential-related source omitted] - Access to secretsline 93
[Credential-related source omitted] - Access to secretsline 100
[Credential-related source omitted] - Access to secretsline 103
[Credential-related source omitted] - Access to secretsline 104
[Credential-related source omitted] - Access to secretsline 106
[Credential-related source omitted] - Access to secretsline 109
[Credential-related source omitted] - Access to secretsline 115
[Credential-related source omitted] - Access to secretsline 125
[Credential-related source omitted] - Access to secretsline 139
[Credential-related source omitted] - Network accessline 141
try: if url.startswith(PDF_BASE_URL): resp = _PDF_CLIENT.fetch(full_url, max_retries=max_retries) - Network accessline 142
if url.startswith(PDF_BASE_URL): resp = _PDF_CLIENT.fetch(full_url, max_retries=max_retries) elif url.startswith(BASE_URL): - Network accessline 143
resp = _PDF_CLIENT.fetch(full_url, max_retries=max_retries) - Network accessline 144
elif url.startswith(BASE_URL): resp = _API_CLIENT.fetch(full_url, max_retries=max_retries) else: - Network accessline 145
resp = _API_CLIENT.fetch(full_url, max_retries=max_retries) - Access to secretsline 153
[Credential-related source omitted] - Network accessline 211
[Credential-related source omitted] - Access to secretsline 211
[Credential-related source omitted] - Network accessline 213
# Construct search URL (e.g., https://api.openalex.org/works) - Access to secretsline 219
[Credential-related source omitted] - Network accessline 243
Accepted formats: - Short IDs: W2741809807, A5023888391 - Full OpenAlex URLs: https://openalex.org/W2741809807 - Network accessline 244
- Short IDs: W2741809807, A5023888391 - Full OpenAlex URLs: https://openalex.org/W2741809807 - DOIs: https://doi.org/10.xxx - Network accessline 245
- Full OpenAlex URLs: https://openalex.org/W2741809807 - Network accessline 246
- DOIs: https://doi.org/10.xxx - Network accessline 248
return bool( _OPENALEX_SHORT_ID_RE.match(entity_id) or entity_id.startswith("https://openalex.org/") - Network accessline 249
_OPENALEX_SHORT_ID_RE.match(entity_id) or entity_id.startswith("https://openalex.org/") or entity_id.startswith("https://doi.org/") - Network accessline 250
or entity_id.startswith("https://openalex.org/") - Network accessline 251
or entity_id.startswith("https://doi.org/") - Access to secretsline 260
[Credential-related source omitted] - Network accessline 270
# Construct entity-specific URL (e.g., https://api.openalex.org/works/W123) - Access to secretsline 278
[Credential-related source omitted] - Access to secretsline 333
[Credential-related source omitted] - Access to secretsline 344
[Credential-related source omitted] - Access to secretsline 352
[Credential-related source omitted] - Access to secretsline 390
[Credential-related source omitted] - Access to secretsline 397
[Credential-related source omitted] - Access to secretsline 425
[Credential-related source omitted] - Access to secretsline 430
[Credential-related source omitted] - Access to secretsline 442
[Credential-related source omitted] - Access to secretsline 478
[Credential-related source omitted] - Access to secretsline 486
[Credential-related source omitted] - Access to secretsline 492
[Credential-related source omitted] - Access to secretsline 514
[Credential-related source omitted] - Access to secretsline 527
[Credential-related source omitted] - Access to secretsline 534
[Credential-related source omitted] - Access to secretsline 538
[Credential-related source omitted]
packages/skills/skills/17_Literature_Databases/pubmed-database/SKILL.md
- Network accessline 18
2. **User Notification**: If .licenses/pubmed_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://pubmed.ncbi.nlm.nih.gov/disclaimer/ - Network accessline 19
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://pubmed.ncbi.nlm.nih.gov/disclaimer/ and https://www.ncbi.nlm.nih.gov/home/about/policies/ and to always check - Network accessline 20
the user to check the terms at https://pubmed.ncbi.nlm.nih.gov/disclaimer/ - Network accessline 21
and https://www.ncbi.nlm.nih.gov/home/about/policies/ and to always check - Access to secretsline 26
[Credential-related source omitted] - Network accessline 27
to 10 requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You - Network accessline 28
if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe credentials protocol in the `credentials` skill to - Network accessline 29
for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You - Access to secretsline 46
[Credential-related source omitted]
packages/skills/skills/17_Literature_Databases/pubmed-database/references/advanced-linking.md
- Network accessline 42
This list covers the most common `pubmed → X` links. For the full list of all ELink linknames across all NCBI databases, see the [NCBI Entrez Links catalog](https://eutils.ncbi.nlm.nih.gov/entrez/query/static/entrezlinks.html). - Network accessline 44
[NCBI Entrez Links catalog](https://eutils.ncbi.nlm.nih.gov/entrez/query/static/entrezlinks.html).
packages/skills/skills/17_Literature_Databases/pubmed-database/references/citation.bib
- Network accessline 1
@ARTICLE{Sayers2025, ABSTRACT = {The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence repository and the PubMed® repository of citations a - Network accessline 2
ABSTRACT = {The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence repository and the PubMed® repository of citations and abstracts published - Network accessline 3
AUTHOR = {Sayers, Eric W and Beck, Jeffrey and Bolton, Evan E and Brister, J Rodney and Chan, Jessica and Connor, Ryan and Feldgarden, Michael and Fine, Anna M and Funk, Kathryn and Hoffman, Jinna and Kannan, Sivakumar and Kelly, Christophe - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkae979}, - Network accessline 5
DATE = {2025-01}, DOI = {10.1093/nar/gkae979}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D20/60586411/gkae979.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkae979}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D20/60586411/gkae979.pdf}, ISSN = {1362-4962}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D20/60586411/gkae979.pdf},
packages/skills/skills/17_Literature_Databases/pubmed-database/references/cross-database-linking.md
packages/skills/skills/17_Literature_Databases/pubmed-database/references/search-and-discovery.md
packages/skills/skills/17_Literature_Databases/pubmed-database/scripts/pubmed_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 45
EUTILS_BASE = "https://eutils.ncbi.nlm.nih.gov" - Network accessline 46
PMC_BIOC_BASE = ( "https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json" ) - Network accessline 47
"https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json" - Access to secretsline 58
[Credential-related source omitted] - Access to secretsline 67
[Credential-related source omitted] - Access to secretsline 79
[Credential-related source omitted] - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Access to secretsline 86
[Credential-related source omitted] - Access to secretsline 87
[Credential-related source omitted] - Network accessline 127
try: data_bytes = urllib.parse.urlencode(params).encode("utf-8") resp = get_eutils_client().fetch(url, method="POST", data=data_bytes) - Network accessline 128
data_bytes = urllib.parse.urlencode(params).encode("utf-8") resp = get_eutils_client().fetch(url, method="POST", data=data_bytes) return resp.text - Network accessline 129
resp = get_eutils_client().fetch(url, method="POST", data=data_bytes) - Access to secretsline 636
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/SKILL.md
- Network accessline 21
.licenses/alphagenome_single_variant_analysis_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://deepmind.google.com/science/alphagenome/, then - Network accessline 22
exist in the workspace root directory then (1) prominently notify the user to check the terms at https://deepmind.google.com/science/alphagenome/, then (2) create the file recording the notification text and timestamp. - Network accessline 23
to check the terms at https://deepmind.google.com/science/alphagenome/, then - Network accessline 26
Create one if it does not exist. 4. **`ALPHAGENOME_API_KEY`**: This skill requires an API key to function. You can register for a key at https://deepmind.google.com/science/alphagenome/. - Network accessline 27
[Credential-related source omitted] - Access to secretsline 27
[Credential-related source omitted] - Network accessline 28
You can register for a key at https://deepmind.google.com/science/alphagenome/. - Access to secretsline 42
[Credential-related source omitted] - Network accessline 103
instructions in [Prerequisites](#prerequisites). - **Registry Authentication Error (401)**: If `uv` fails with 401 Unauthorized for a private registry, set `UV_INDEX_URL=https://pypi.org/simple` before - Network accessline 104
- **Registry Authentication Error (401)**: If `uv` fails with 401 Unauthorized for a private registry, set `UV_INDEX_URL=https://pypi.org/simple` before running the script. - Network accessline 105
for a private registry, set `UV_INDEX_URL=https://pypi.org/simple` before - Access to secretsline 161
[Credential-related source omitted] - Access to secretsline 162
[Credential-related source omitted] - Access to secretsline 165
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/analyze_ism.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Access to secretsline 184
[Credential-related source omitted] - Access to secretsline 185
[Credential-related source omitted] - Access to secretsline 186
[Credential-related source omitted] - Access to secretsline 190
[Credential-related source omitted] - Access to secretsline 274
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/generate_ontology_mapping.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Access to secretsline 123
[Credential-related source omitted] - Access to secretsline 125
[Credential-related source omitted] - Access to secretsline 126
[Credential-related source omitted] - Access to secretsline 128
[Credential-related source omitted] - Access to secretsline 129
[Credential-related source omitted] - Access to secretsline 134
[Credential-related source omitted] - Access to secretsline 163
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/interpret_splicing.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Access to secretsline 114
[Credential-related source omitted] - Access to secretsline 115
[Credential-related source omitted] - Access to secretsline 116
[Credential-related source omitted] - Access to secretsline 118
[Credential-related source omitted] - Access to secretsline 271
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/lookup_gene_info.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 49
GTF_URL = ( 'https://storage.googleapis.com/alphagenome/reference/gencode/' - Network accessline 50
'https://storage.googleapis.com/alphagenome/reference/gencode/' - Access to secretsline 265
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/resolve_ontology_terms.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Access to secretsline 106
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/visualize_genome_tracks.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 57
GTF_URL = ( 'https://storage.googleapis.com/alphagenome/reference/gencode/' - Network accessline 58
'https://storage.googleapis.com/alphagenome/reference/gencode/' - Access to secretsline 66
[Credential-related source omitted] - Access to secretsline 67
[Credential-related source omitted] - Access to secretsline 68
[Credential-related source omitted] - Access to secretsline 70
[Credential-related source omitted] - Access to secretsline 348
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis/scripts/visualize_variant_effects.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 69
GTF_URL = ( 'https://storage.googleapis.com/alphagenome/reference/gencode/' - Network accessline 70
'https://storage.googleapis.com/alphagenome/reference/gencode/' - Access to secretsline 1017
[Credential-related source omitted] - Access to secretsline 1018
[Credential-related source omitted] - Access to secretsline 1019
[Credential-related source omitted] - Access to secretsline 1022
[Credential-related source omitted] - Access to secretsline 1134
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/clinvar-database/SKILL.md
- Network accessline 15
2. **User Notification**: If .licenses/clinvar_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ncbi.nlm.nih.gov/clinvar/, then - Network accessline 16
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ncbi.nlm.nih.gov/clinvar/, then (2) create the file recording the notification text and timestamp. - Network accessline 17
the user to check the terms at https://www.ncbi.nlm.nih.gov/clinvar/, then - Access to secretsline 21
[Credential-related source omitted] - Network accessline 22
requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** - Network accessline 23
user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe credentials protocol in the `credentials` skill to check for - Network accessline 24
key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** - Access to secretsline 85
[Credential-related source omitted] - Network accessline 335
You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe - Network accessline 336
https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe - Access to secretsline 359
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/clinvar-database/scripts/clinvar_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 57
BASE_URL = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/' - Access to secretsline 61
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Access to secretsline 82
[Credential-related source omitted] - Network accessline 88
try: resp = self.client.fetch(full_url) - Network accessline 89
resp = self.client.fetch(full_url) - Network accessline 95
' INSTRUCTION: Pause execution and inform the user that an NCBI API' ' Key is required to increase the rate limit, providing the URL' ' https://www.ncbi.nlm.nih.gov/clinvar/docs/api_http/ for' - Network accessline 96
' Key is required to increase the rate limit, providing the URL' ' https://www.ncbi.nlm.nih.gov/clinvar/docs/api_http/ for' ' instructions on how to obtain one. The user will need to set the' - Network accessline 97
' https://www.ncbi.nlm.nih.gov/clinvar/docs/api_http/ for' - Access to secretsline 99
[Credential-related source omitted] - Access to secretsline 613
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/dbsnp-database/SKILL.md
- Network accessline 17
2. **User Notification**: If .licenses/dbsnp_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ncbi.nlm.nih.gov/snp/, then (2) - Network accessline 18
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ncbi.nlm.nih.gov/snp/, then (2) create the file recording the notification text and timestamp. - Network accessline 19
the user to check the terms at https://www.ncbi.nlm.nih.gov/snp/, then (2) - Access to secretsline 23
[Credential-related source omitted] - Network accessline 24
requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** - Network accessline 25
user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe credentials protocol in the `credentials` skill to check for - Network accessline 26
key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** - Network accessline 32
- **Use the Wrapper**: ALWAYS execute the provided wrapper script `scripts/dbsnp_cli.py` to query the database rather than constructing custom HTTP or curl requests. The script automatically handles rate limiting, - Network accessline 33
`scripts/dbsnp_cli.py` to query the database rather than constructing custom HTTP or curl requests. The script automatically handles rate limiting, retries, and JSON parsing. - Network accessline 34
HTTP or curl requests. The script automatically handles rate limiting, - Network accessline 302
You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe - Network accessline 303
https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe
packages/skills/skills/18_Genetics_Genomics/dbsnp-database/references/api-notes.md
packages/skills/skills/18_Genetics_Genomics/dbsnp-database/scripts/dbsnp_cli.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 42
_BASE_URL = "https://api.ncbi.nlm.nih.gov" - Access to secretsline 55
[Credential-related source omitted] - Access to secretsline 56
[Credential-related source omitted] - Access to secretsline 88
[Credential-related source omitted] - Access to secretsline 89
[Credential-related source omitted] - Access to secretsline 91
[Credential-related source omitted] - Network accessline 99
"AGENT INSTRUCTION: Pause execution and inform the user that an NCBI " "API Key is required. Direct them to " "https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/" - Network accessline 100
"API Key is required. Direct them to " "https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/" "new-api-keys-for-the-e-utilities/ and ask them to set the " - Network accessline 101
"https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/" - Access to secretsline 103
[Credential-related source omitted] - Access to secretsline 511
[Credential-related source omitted]
packages/skills/skills/18_Genetics_Genomics/gnomad-database/SKILL.md
- Network accessline 18
2. **User Notification**: If .licenses/gnomad_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://gnomad.broadinstitute.org/policies - Network accessline 19
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://gnomad.broadinstitute.org/policies and https://gnomad.broadinstitute.org/data#api, then (2) create the file - Network accessline 20
the user to check the terms at https://gnomad.broadinstitute.org/policies - Network accessline 21
and https://gnomad.broadinstitute.org/data#api, then (2) create the file - Network accessline 72
Further documentation on the data: https://gnomad.broadinstitute.org/data#api - Network accessline 73
More general database documentation: https://gnomad.broadinstitute.org/help
packages/skills/skills/18_Genetics_Genomics/gnomad-database/references/citation.bib
- Network accessline 3
AUTHOR = {Karczewski, Konrad J. and Francioli, Laurent C. and Tiao, Grace and Cummings, Beryl B. and Alföldi, Jessica and Wang, Qingbo and Collins, Ryan L. and Laricchia, Kristen M. and Ganna, Andrea and Birnbaum, Daniel P. and Gauthier, La - Network accessline 4
URL = {https://doi.org/10.1038/s41586-020-2308-7},
packages/skills/skills/18_Genetics_Genomics/gnomad-database/scripts/get_gene_constraint.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 36
CLIENT = http_client.HttpClient("https://gnomad.broadinstitute.org", qps=0.1666) - Network accessline 44
url = "https://gnomad.broadinstitute.org/api"
packages/skills/skills/18_Genetics_Genomics/gnomad-database/scripts/get_variant_frequency.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 32
CLIENT = http_client.HttpClient("https://gnomad.broadinstitute.org", qps=0.1666) - Network accessline 37
url = "https://gnomad.broadinstitute.org/api" - Network accessline 77
url = "https://gnomad.broadinstitute.org/api"
packages/skills/skills/18_Genetics_Genomics/gnomad-database/scripts/search_variants.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 32
CLIENT = http_client.HttpClient("https://gnomad.broadinstitute.org", qps=0.1666) - Network accessline 42
url = "https://gnomad.broadinstitute.org/api" - Network accessline 118
url = "https://gnomad.broadinstitute.org/api"
packages/skills/skills/19_Pharmacology/chembl-database/SKILL.md
- Network accessline 16
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://chembl.gitbook.io/chembl-interface-documentation/about, then (2) - Network accessline 17
the user to check the terms at https://chembl.gitbook.io/chembl-interface-documentation/about, then (2) create the file recording the notification text and timestamp. - Network accessline 18
https://chembl.gitbook.io/chembl-interface-documentation/about, then (2)
packages/skills/skills/19_Pharmacology/chembl-database/references/api_endpoints.md
- Network accessline 3
Base URL: `https://www.ebi.ac.uk/chembl/api/data`
packages/skills/skills/19_Pharmacology/chembl-database/references/citation.bib
- Network accessline 1
@ARTICLE{Zdrazil2024, ABSTRACT = {ChEMBL (https://www.ebi.ac.uk/chembl/) is a manually curated, high-quality, large-scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like properties, previously described - Network accessline 2
ABSTRACT = {ChEMBL (https://www.ebi.ac.uk/chembl/) is a manually curated, high-quality, large-scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like properties, previously described in the 2012, 2014, 2017 - Network accessline 3
AUTHOR = {Zdrazil, Barbara and Felix, Eloy and Hunter, Fiona and Manners, Emma J and Blackshaw, James and Corbett, Sybilla and de Veij, Marleen and Ioannidis, Harris and Lopez, David Mendez and Mosquera, Juan F and Magarinos, Maria Paula an - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkad1004}, - Network accessline 5
DATE = {2024-01}, DOI = {10.1093/nar/gkad1004}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1180/55040046/gkad1004.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkad1004}, EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1180/55040046/gkad1004.pdf}, ISSN = {0305-1048}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/52/D1/D1180/55040046/gkad1004.pdf}, - Network accessline 16
@ARTICLE{Davies2015, ABSTRACT = {ChEMBL is now a well-established resource in the fields of drug discovery and medicinal chemistry research. The ChEMBL database curates and stores standardized bioactivity, molecule, target and drug data e - Network accessline 17
ABSTRACT = {ChEMBL is now a well-established resource in the fields of drug discovery and medicinal chemistry research. The ChEMBL database curates and stores standardized bioactivity, molecule, target and drug data extracted from multiple - Network accessline 18
AUTHOR = {Davies, Mark and Nowotka, Michał and Papadatos, George and Dedman, Nathan and Gaulton, Anna and Atkinson, Francis and Bellis, Louisa and Overington, John P.}, URL = {https://doi.org/10.1093/nar/gkv352}, DATE = {2015-07}, - Network accessline 19
URL = {https://doi.org/10.1093/nar/gkv352}, - Network accessline 20
DATE = {2015-07}, DOI = {10.1093/nar/gkv352}, EPRINT = {https://academic.oup.com/nar/article-pdf/43/W1/W612/17435802/gkv352.pdf}, - Network accessline 21
DOI = {10.1093/nar/gkv352}, EPRINT = {https://academic.oup.com/nar/article-pdf/43/W1/W612/17435802/gkv352.pdf}, ISSN = {0305-1048}, - Network accessline 22
EPRINT = {https://academic.oup.com/nar/article-pdf/43/W1/W612/17435802/gkv352.pdf},
packages/skills/skills/19_Pharmacology/chembl-database/scripts/chembl_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 40
BASE_URL = "https://www.ebi.ac.uk/chembl/api/data" - Network accessline 117
data["_license_notice"] = ( "Data from the ChEMBL Database. Please review the licensing terms at" " https://www.ebi.ac.uk/chembl/" - Network accessline 118
"Data from the ChEMBL Database. Please review the licensing terms at" " https://www.ebi.ac.uk/chembl/" ) - Network accessline 119
" https://www.ebi.ac.uk/chembl/"
packages/skills/skills/19_Pharmacology/clinical-trials-database/SKILL.md
- Network accessline 17
2. **User Notification**: If .licenses/clinical_trials_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://clinicaltrials.gov/, then (2) - Network accessline 18
does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://clinicaltrials.gov/, then (2) create the file recording the notification text and timestamp. - Network accessline 19
notify the user to check the terms at https://clinicaltrials.gov/, then (2)
packages/skills/skills/19_Pharmacology/clinical-trials-database/scripts/clinical_trials_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 36
BASE_URL = "https://clinicaltrials.gov/api/v2"
packages/skills/skills/19_Pharmacology/openfda-database/SKILL.md
- Network accessline 17
2. **User Notification**: If .licenses/openfda_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://open.fda.gov/apis/ and - Network accessline 18
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://open.fda.gov/apis/ and https://open.fda.gov/license, then (2) create the file recording the - Network accessline 19
the user to check the terms at https://open.fda.gov/apis/ and - Network accessline 20
https://open.fda.gov/license, then (2) create the file recording the - Access to secretsline 24
[Credential-related source omitted] - Network accessline 25
from 1,000 to 120,000. The skill works without it, but an agent can easily exhaust the keyless limit in a single session. You can register for a free key at https://open.fda.gov/apis/authentication/. You **MUST** use the safe - Network accessline 26
exhaust the keyless limit in a single session. You can register for a free key at https://open.fda.gov/apis/authentication/. You **MUST** use the safe credentials protocol in the `credentials` skill to check for and request - Network accessline 27
key at https://open.fda.gov/apis/authentication/. You **MUST** use the safe - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 96
[Credential-related source omitted] - Network accessline 132
- `--max_pages`: Maximum pages to fetch (default 10).
packages/skills/skills/19_Pharmacology/openfda-database/references/api_endpoints.md
packages/skills/skills/19_Pharmacology/openfda-database/references/citation.bib
- Network accessline 2
ABSTRACT = {Objective The objective of openFDA is to facilitate access and use of big important Food and Drug Administration public datasets by developers, researchers, and the public through harmonization of data across disparate FDA datas - Network accessline 3
AUTHOR = {Kass-Hout, Taha A and Xu, Zhiheng and Mohebbi, Matthew and Nelsen, Hans and Baker, Adam and Levine, Jonathan and Johanson, Elaine and Bright, Roselie A}, URL = {https://doi.org/10.1093/jamia/ocv153}, DATE = {2016-05}, - Network accessline 4
URL = {https://doi.org/10.1093/jamia/ocv153}, - Network accessline 5
DATE = {2016-05}, DOI = {10.1093/jamia/ocv153}, EPRINT = {https://academic.oup.com/jamia/article-pdf/23/3/596/34147863/ocv153.pdf}, - Network accessline 6
DOI = {10.1093/jamia/ocv153}, EPRINT = {https://academic.oup.com/jamia/article-pdf/23/3/596/34147863/ocv153.pdf}, ISSN = {1067-5027}, - Network accessline 7
EPRINT = {https://academic.oup.com/jamia/article-pdf/23/3/596/34147863/ocv153.pdf},
packages/skills/skills/19_Pharmacology/openfda-database/scripts/openfda_query.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 41
BASE_URL = "https://api.fda.gov" - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 81
[Credential-related source omitted] - Network accessline 83
print( "WARNING: No API key provided. This API has much lower rate limits" " without a key. Get one at https://open.fda.gov/apis/authentication/" - Network accessline 84
"WARNING: No API key provided. This API has much lower rate limits" " without a key. Get one at https://open.fda.gov/apis/authentication/" " and pass via --api_key or the FDA_API_KEY environment variable.", - Network accessline 85
" without a key. Get one at https://open.fda.gov/apis/authentication/" - Access to secretsline 86
[Credential-related source omitted] - Network accessline 97
data["_license_notice"] = ( "Data provided by openFDA. Please review the licensing terms at" " https://open.fda.gov/license/" - Network accessline 98
"Data provided by openFDA. Please review the licensing terms at" " https://open.fda.gov/license/" ) - Network accessline 99
" https://open.fda.gov/license/" - Access to secretsline 146
[Credential-related source omitted] - Access to secretsline 158
[Credential-related source omitted] - Access to secretsline 166
[Credential-related source omitted] - Access to secretsline 168
[Credential-related source omitted] - Network accessline 194
" limit. Without an API key the limit is 240 requests/min and" " 1,000/day. With a free API key the daily limit increases to" " 120,000. Register at: https://open.fda.gov/apis/authentication/" - Network accessline 195
" 1,000/day. With a free API key the daily limit increases to" " 120,000. Register at: https://open.fda.gov/apis/authentication/" ), - Network accessline 196
" 120,000. Register at: https://open.fda.gov/apis/authentication/" - Access to secretsline 225
[Credential-related source omitted] - Access to secretsline 231
[Credential-related source omitted] - Access to secretsline 240
[Credential-related source omitted] - Access to secretsline 270
[Credential-related source omitted] - Access to secretsline 278
[Credential-related source omitted] - Access to secretsline 313
[Credential-related source omitted] - Access to secretsline 339
[Credential-related source omitted] - Access to secretsline 383
[Credential-related source omitted] - Access to secretsline 432
[Credential-related source omitted] - Access to secretsline 435
[Credential-related source omitted] - Network accessline 476
type=int, default=10, help="Max pages to fetch (default 10)", - Network accessline 477
default=10, help="Max pages to fetch (default 10)", ) - Network accessline 478
help="Max pages to fetch (default 10)", - Access to secretsline 494
[Credential-related source omitted]
packages/skills/skills/19_Pharmacology/opentargets-database/SKILL.md
- Network accessline 23
not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://platform-docs.opentargets.org/licence, then (2) create the file - Network accessline 24
notify the user to check the terms at https://platform-docs.opentargets.org/licence, then (2) create the file recording the notification text and timestamp. - Network accessline 25
https://platform-docs.opentargets.org/licence, then (2) create the file - Network accessline 40
Always use the provided Python script `scripts/query_opentargets.py` to quickly query the database. It handles API communication, retries, formatting, and automatically truncates overly large responses. NEVER write your own curl or - Network accessline 41
query the database. It handles API communication, retries, formatting, and automatically truncates overly large responses. NEVER write your own curl or similar requests. - Network accessline 42
automatically truncates overly large responses. NEVER write your own curl or
packages/skills/skills/19_Pharmacology/opentargets-database/references/citation.bib
- Network accessline 1
@ARTICLE{Buniello2025, ABSTRACT = {The Open Targets Platform (https://platform.opentargets.org) is a unique, open-source, publicly-available knowledge base providing data and tooling for systematic drug target identification, annotation, - Network accessline 2
ABSTRACT = {The Open Targets Platform (https://platform.opentargets.org) is a unique, open-source, publicly-available knowledge base providing data and tooling for systematic drug target identification, annotation, and prioritisation. Since - Network accessline 3
AUTHOR = {Buniello, Annalisa and Suveges, Daniel and Cruz-Castillo, Carlos and Llinares, Manuel Bernal and Cornu, Helena and Lopez, Irene and Tsukanov, Kirill and Roldán-Romero, Juan María and Mehta, Chintan and Fumis, Luca and McNeill, Gra - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkae1128}, - Network accessline 5
DATE = {2025-01}, DOI = {10.1093/nar/gkae1128}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1467/60967175/gkae1128.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkae1128}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1467/60967175/gkae1128.pdf}, ISSN = {1362-4962}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1467/60967175/gkae1128.pdf},
packages/skills/skills/19_Pharmacology/opentargets-database/scripts/query_opentargets.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 37
BASE_URL = "https://api.platform.opentargets.org/api/v4/graphql"
packages/skills/skills/19_Pharmacology/pubchem-database/SKILL.md
- Network accessline 16
already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://pubchem.ncbi.nlm.nih.gov/docs/citation-guidelines and - Network accessline 17
the user to check the terms at https://pubchem.ncbi.nlm.nih.gov/docs/citation-guidelines and https://pubchem.ncbi.nlm.nih.gov/docs/pug-rest, then (2) create the file - Network accessline 18
https://pubchem.ncbi.nlm.nih.gov/docs/citation-guidelines and - Network accessline 19
https://pubchem.ncbi.nlm.nih.gov/docs/pug-rest, then (2) create the file
packages/skills/skills/19_Pharmacology/pubchem-database/references/citation.bib
- Network accessline 1
@ARTICLE{Kim2025, ABSTRACT = {PubChem (https://pubchem.ncbi.nlm.nih.gov) is a large and highly-integrated public chemical database resource at NIH. In the past two years, significant updates were made to PubChem. With additions from over - Network accessline 2
ABSTRACT = {PubChem (https://pubchem.ncbi.nlm.nih.gov) is a large and highly-integrated public chemical database resource at NIH. In the past two years, significant updates were made to PubChem. With additions from over 130 new sources, Pub - Network accessline 3
AUTHOR = {Kim, Sunghwan and Chen, Jie and Cheng, Tiejun and Gindulyte, Asta and He, Jia and He, Siqian and Li, Qingliang and Shoemaker, Benjamin A and Thiessen, Paul A and Yu, Bo and Zaslavsky, Leonid and Zhang, Jian and Bolton, Evan E}, - Network accessline 4
URL = {https://doi.org/10.1093/nar/gkae1059}, - Network accessline 5
DATE = {2025-01}, DOI = {10.1093/nar/gkae1059}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1516/60743708/gkae1059.pdf}, - Network accessline 6
DOI = {10.1093/nar/gkae1059}, EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1516/60743708/gkae1059.pdf}, ISSN = {1362-4962}, - Network accessline 7
EPRINT = {https://academic.oup.com/nar/article-pdf/53/D1/D1516/60743708/gkae1059.pdf},
packages/skills/skills/19_Pharmacology/pubchem-database/references/endpoints.md
- Network accessline 8
**Base URL:** `https://pubchem.ncbi.nlm.nih.gov/rest/pug` - Network accessline 46
* **Properties by CID (JSON)**: `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/2244/property/MolecularWeight,MolecularFormula/JSON` - Network accessline 47
* **Mass Range Search (JSON)**: `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/molecular_weight/range/400.0/400.05/cids/JSON` - Network accessline 48
* **Patents by SID (JSON)**: `https://pubchem.ncbi.nlm.nih.gov/rest/pug/substance/sid/137349406/xrefs/PatentID/JSON` - Network accessline 57
**Base URL:** `https://pubchem.ncbi.nlm.nih.gov/rest/pug_view` - Network accessline 59
The standard structure for retrieving specific sections: `https://pubchem.ncbi.nlm.nih.gov/rest/pug_view/data/compound/<cid>/JSON?heading=<Section+Heading>` - Network accessline 60
`https://pubchem.ncbi.nlm.nih.gov/rest/pug_view/data/compound/<cid>/JSON?heading=<Section+Heading>`
packages/skills/skills/19_Pharmacology/pubchem-database/scripts/pubchem_api.py
- Executable scriptline 1
Executable file - Network accessline 5
# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 6
# # http://www.apache.org/licenses/LICENSE-2.0 # - Network accessline 7
# http://www.apache.org/licenses/LICENSE-2.0 - Network accessline 36
PUBCHEM_BASE_URL = "https://pubchem.ncbi.nlm.nih.gov/rest" - Network accessline 42
try: resp = _CLIENT.fetch(url) - Network accessline 43
resp = _CLIENT.fetch(url)
packages/skills/skills/20_Infrastructure/uv/SKILL.md
- Network accessline 24
Python environment used for running the Science Skills, and that you need to install it now. (b) Install `uv`: `curl -LsSf https://astral.sh/uv/install.sh | sh` - Network accessline 25
need to install it now. (b) Install `uv`: `curl -LsSf https://astral.sh/uv/install.sh | sh` 4. Add `uv` to PATH and verify (run as a single command): `export - Dangerous shell operationline 26
(b) Install `uv`: `curl -LsSf https://astral.sh/uv/install.sh | sh` - Network accessline 26
(b) Install `uv`: `curl -LsSf https://astral.sh/uv/install.sh | sh`
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/SKILL.md
- Network accessline 15
This skill encodes practical knowledge of the [SpikeInterface](https://spikeinterface.readthedocs.io) Python framework — a unified API for extracellular electrophysiology spike sorting. - Network accessline 215
# Development install from source git clone https://github.com/SpikeInterface/spikeinterface.git - Network accessline 216
git clone https://github.com/SpikeInterface/spikeinterface.git
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/core/datasets.md
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/curation/auto_merge_presets.md
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/curation/unitrefine.md
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/exporters/export_to_ibl_gui.md
- Network accessline 6
Exports a `SortingAnalyzer` to the format required by the IBL alignment GUI (`https://github.com/int-brain-lab/iblapps/wiki`). Source: `spikeinterface/exporters/to_ibl.py`.
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/preprocessing/motion_correction.md
- Network accessline 89
| --- | --- | | `dredge` | "Official Dredge preset". detect=`locally_exclusive` (neg, thr=8.0, sweep=0.8 ms, radius=80.0), localize=`monopolar_triangulation`, estimate=`dredge_ap` (nonrigid, `win_shape="gaussian"`, `win_step_um=400`, `win_s - Network accessline 90
| `dredge` | "Official Dredge preset". detect=`locally_exclusive` (neg, thr=8.0, sweep=0.8 ms, radius=80.0), localize=`monopolar_triangulation`, estimate=`dredge_ap` (nonrigid, `win_shape="gaussian"`, `win_step_um=400`, `win_scale_um=400`), - Network accessline 91
| `medicine` | "Medicine method: https://jazlab.github.io/medicine/". detect=`locally_exclusive`, localize=`monopolar_triangulation`, estimate=`medicine`, interpolate=defaults. |
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/archived_sorters.md
- Network accessline 15
`requires_binary_data = True`. `sorter_description`: "Klusta is a density-based spike sorter that uses a masked EM approach for clustering. See https://doi.org/10.1038/nn.4268". - Network accessline 16
`sorter_description`: "Klusta is a density-based spike sorter that uses a masked EM approach for clustering. See https://doi.org/10.1038/nn.4268". `installation_mesg`: `pip install Cython h5py tqdm` then `pip install click klusta klustakwik - Network accessline 17
clustering. See https://doi.org/10.1038/nn.4268". - Network accessline 43
`sorter_description`: "YASS is a deconvolution and neural network based spike sorting algorithm designed for recordings with no drift (such as retinal recordings). See https://www.biorxiv.org/content/10.1101/2020.03.18.997924v1". - Network accessline 44
designed for recordings with no drift (such as retinal recordings). See https://www.biorxiv.org/content/10.1101/2020.03.18.997924v1". `installation_mesg`: `pip install yass-algorithm`. - Network accessline 45
https://www.biorxiv.org/content/10.1101/2020.03.18.997924v1".
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/external_kilosort_family_a.md
- Network accessline 15
overridden — this is an inconsistency in the source), `handle_multi_segment = False`. `sorter_description`: "Kilosort is a GPU-accelerated and efficient template-matching spike sorter. See https://papers.nips.cc/paper/6326-fast-and-accurate - Network accessline 16
`sorter_description`: "Kilosort is a GPU-accelerated and efficient template-matching spike sorter. See https://papers.nips.cc/paper/6326-fast-and-accurate-spike-sorting-of-high-channel-count-probes-with-kilosort". `installation_mesg`: clone - Network accessline 17
sorter. See https://papers.nips.cc/paper/6326-fast-and-accurate-spike-sorting-of-high-channel-count-probes-with-kilosort". - Network accessline 18
`installation_mesg`: clone https://github.com/cortex-lab/KiloSort and set `KILOSORT_PATH` or - Network accessline 72
`sorter_description`: "Kilosort2 is a GPU-accelerated and efficient template-matching spike sorter. On top of its predecessor Kilosort, it implements a drift-correction strategy. See https://github.com/MouseLand/Kilosort2". - Network accessline 73
sorter. On top of its predecessor Kilosort, it implements a drift-correction strategy. See https://github.com/MouseLand/Kilosort2". `installation_mesg`: clone https://github.com/MouseLand/Kilosort2 and set `KILOSORT2_PATH` or - Network accessline 74
https://github.com/MouseLand/Kilosort2". - Network accessline 75
`installation_mesg`: clone https://github.com/MouseLand/Kilosort2 and set `KILOSORT2_PATH` or - Network accessline 115
`sorter_description`: "Kilosort2_5 is a GPU-accelerated ... uses sub-pixel registration for drift correction. Expected to work on Neuropixels 1.0/2.0 and probes with vertical pitch <=40um. See https://github.com/MouseLand/Kilosort". - Network accessline 116
drift correction. Expected to work on Neuropixels 1.0/2.0 and probes with vertical pitch <=40um. See https://github.com/MouseLand/Kilosort". `installation_mesg`: clone https://github.com/MouseLand/Kilosort and set `KILOSORT2_5_PATH` or - Network accessline 117
See https://github.com/MouseLand/Kilosort". - Network accessline 118
`installation_mesg`: clone https://github.com/MouseLand/Kilosort and set `KILOSORT2_5_PATH` or
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/external_kilosort_family_b.md
- Network accessline 12
`compiled_name: str = "ks3_compiled"`, `requires_locations = False`, `handle_multi_segment = False`. `sorter_description`: "Kilosort3 is a GPU-accelerated ... See https://github.com/MouseLand/Kilosort". - Network accessline 13
`handle_multi_segment = False`. `sorter_description`: "Kilosort3 is a GPU-accelerated ... See https://github.com/MouseLand/Kilosort". `installation_mesg`: clone https://github.com/MouseLand/Kilosort and set `KILOSORT3_PATH` or - Network accessline 14
`sorter_description`: "Kilosort3 is a GPU-accelerated ... See https://github.com/MouseLand/Kilosort". - Network accessline 15
`installation_mesg`: clone https://github.com/MouseLand/Kilosort and set `KILOSORT3_PATH` or - Network accessline 56
`handle_multi_segment = False`. `sorter_description`: "Kilosort4 is a Python package for spike sorting on GPUs with template matching. ... For more information see https://github.com/MouseLand/Kilosort". - Network accessline 57
`sorter_description`: "Kilosort4 is a Python package for spike sorting on GPUs with template matching. ... For more information see https://github.com/MouseLand/Kilosort". `installation_mesg`: `pip install kilosort --upgrade`. - Network accessline 58
matching. ... For more information see https://github.com/MouseLand/Kilosort". - Network accessline 92
`sorter_description`: "pykilosort is a port of kilosort to python". `installation_mesg`: `pip install cupy` + clone https://github.com/MouseLand/pykilosort + `python setup.py install`. - Network accessline 94
https://github.com/MouseLand/pykilosort + `python setup.py install`.
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/external_mountainsort_spykingcircus.md
- Network accessline 13
`sorter_description`: "Mountainsort4 is a fully automatic density-based spike sorter using the isosplit clustering method and automatic curation procedures. ... See https://doi.org/10.1016/j.neuron.2017.08.030". - Network accessline 14
isosplit clustering method and automatic curation procedures. ... See https://doi.org/10.1016/j.neuron.2017.08.030". `installation_mesg`: `pip install mountainsort4`. - Network accessline 15
https://doi.org/10.1016/j.neuron.2017.08.030". - Network accessline 42
`compatible_with_parallel = {"loky": False, "multiprocessing": False, "threading": False}`. `sorter_description`: "MountainSort5 uses Isosplit clustering. It is an updated version of MountainSort4. See https://doi.org/10.1016/j.neuron.2017. - Network accessline 43
`sorter_description`: "MountainSort5 uses Isosplit clustering. It is an updated version of MountainSort4. See https://doi.org/10.1016/j.neuron.2017.08.030". `installation_mesg`: `pip install mountainsort5`. - Network accessline 44
MountainSort4. See https://doi.org/10.1016/j.neuron.2017.08.030". - Network accessline 82
`handle_multi_segment = False`. `sorter_description`: "Spyking Circus is a python-based template-matching spike sorter. ... See https://doi.org/10.7554/eLife.34518". - Network accessline 83
`sorter_description`: "Spyking Circus is a python-based template-matching spike sorter. ... See https://doi.org/10.7554/eLife.34518". `installation_mesg`: `pip install spyking-circus`; needs MPICH (ubuntu: - Network accessline 84
https://doi.org/10.7554/eLife.34518". - Dangerous shell operationline 86
`sudo apt install libmpich-dev mpich`). - Network accessline 111
`compatible_with_parallel = {"loky": True, "multiprocessing": False, "threading": False}`. `sorter_description`: "Tridesclous is a template-matching spike sorter with a real-time engine. See https://tridesclous.readthedocs.io". - Network accessline 112
`sorter_description`: "Tridesclous is a template-matching spike sorter with a real-time engine. See https://tridesclous.readthedocs.io". `installation_mesg`: `pip install tridesclous`. - Network accessline 113
See https://tridesclous.readthedocs.io".
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/external_other_a.md
- Network accessline 12
`handle_multi_segment = False`. `sorter_description`: "Combinato is a complete data-analysis framework for spike sorting in noisy recordings ... See https://doi:10.1371/journal.pone.0166598". - Network accessline 13
`sorter_description`: "Combinato is a complete data-analysis framework for spike sorting in noisy recordings ... See https://doi:10.1371/journal.pone.0166598". `installation_mesg`: clone https://github.com/jniediek/combinato and set `COMBIN - Network accessline 14
noisy recordings ... See https://doi:10.1371/journal.pone.0166598". - Network accessline 15
`installation_mesg`: clone https://github.com/jniediek/combinato and set `COMBINATO_PATH` or - Network accessline 48
`requires_locations = False`, `handle_multi_segment = False`. `sorter_description`: "HDsort is a template-matching spike sorter designed for high density micro-electrode arrays. See https://doi.org/10.1152/jn.00803.2017". - Network accessline 49
`sorter_description`: "HDsort is a template-matching spike sorter designed for high density micro-electrode arrays. See https://doi.org/10.1152/jn.00803.2017". `installation_mesg`: clone https://git.bsse.ethz.ch/hima_public/HDsort.git and s - Network accessline 50
micro-electrode arrays. See https://doi.org/10.1152/jn.00803.2017". - Network accessline 51
`installation_mesg`: clone https://git.bsse.ethz.ch/hima_public/HDsort.git and set - Network accessline 81
`compatible_with_parallel = {"loky": True, "multiprocessing": True, "threading": False}`. `sorter_description`: "HerdingSpikes is a density-based spike sorter designed for large-scale high-density recordings ... See https://www.sciencedirec - Network accessline 82
`sorter_description`: "HerdingSpikes is a density-based spike sorter designed for large-scale high-density recordings ... See https://www.sciencedirect.com/science/article/pii/S221112471730236X". `installation_mesg`: `pip install herdingspi - Network accessline 83
high-density recordings ... See https://www.sciencedirect.com/science/article/pii/S221112471730236X". - Network accessline 84
`installation_mesg`: `pip install herdingspikes`. More info at https://github.com/mhhennig/hs2. - Network accessline 133
"IronClust is a density-based spike sorter designed for high-density probes (e.g. Neuropixels). It uses features and spike location estimates for clustering and performs drift correction. See https://doi.org/10.1101/101030". - Network accessline 134
It uses features and spike location estimates for clustering and performs drift correction. See https://doi.org/10.1101/101030". `installation_mesg`: clone https://github.com/flatironinstitute/ironclust and set - Network accessline 135
See https://doi.org/10.1101/101030". - Network accessline 136
`installation_mesg`: clone https://github.com/flatironinstitute/ironclust and set
packages/skills/skills/21_Electrophysiology/spikeinterface-skill/references/sorters/external_other_b.md
- Network accessline 14
detection of action potentials within 7.5ms±1.5ms after the waveform trough while the recording remains ongoing. ... See https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0312438". - Network accessline 15
remains ongoing. ... See https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0312438". `installation_mesg`: `pip install git+https://github.com/braingeneers/braindance#egg=braindance[rt-sort]`, - Network accessline 16
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0312438". - Network accessline 17
`installation_mesg`: `pip install git+https://github.com/braingeneers/braindance#egg=braindance[rt-sort]`, - Network accessline 79
`sorter_description`: "WaveClus combines a wavelet-based feature extraction and paramagnetic clustering with a template-matching approach. It is mainly designed for monotrodes and low-channel count probes. See https://doi.org/10.1152/jn.003 - Network accessline 80
clustering with a template-matching approach. It is mainly designed for monotrodes and low-channel count probes. See https://doi.org/10.1152/jn.00339.2018". `installation_mesg`: clone https://github.com/csn-le/wave_clus and provide the path - Network accessline 81
count probes. See https://doi.org/10.1152/jn.00339.2018". - Network accessline 82
`installation_mesg`: clone https://github.com/csn-le/wave_clus and provide the path via - Network accessline 122
`compiled_name: str = "waveclus_snippets_compiled"`, `requires_locations = False`. `sorter_description`: same wording as waveclus. `installation_mesg`: clone https://github.com/csn-le/wave_clus and set `WAVECLUS_PATH` or call - Network accessline 123
`sorter_description`: same wording as waveclus. `installation_mesg`: clone https://github.com/csn-le/wave_clus and set `WAVECLUS_PATH` or call `WaveClusSnippetsSorter.set_waveclus_path()`. - Network accessline 124
https://github.com/csn-le/wave_clus and set `WAVECLUS_PATH` or call
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.
No combined signals at this commit.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md packages/backend-core/plugins/superpowers/6.2.0/skills/brainstorming/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.
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