#599 by GitHub stars
PKU-DAIR/AutoSci
Karpathy's LLM-Wiki vision, fully realized — wiki-centric full-lifecycle AI research platform powered by Claude Code
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
i18n/en/skills/ask/SKILL.md
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i18n/en/skills/check/SKILL.md
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i18n/en/skills/daily-arxiv/SKILL.md
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i18n/en/skills/discover/SKILL.md
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i18n/en/skills/edit/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-design/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-eval/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-pilot-eval/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-pilot-run/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-run/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/exp-status/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/hiera-experiment/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/ideate/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/ingest/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/init/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/novelty/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/paper-compile/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/paper-draft/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/paper-plan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/poster/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/prefill/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/rebuttal/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/refine/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/research/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/reset/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/review/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/setup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/survey/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/en/skills/visualize/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/ask/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/check/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/daily-arxiv/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/discover/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/edit/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/exp-design/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/exp-eval/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/exp-pilot-eval/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/exp-pilot-run/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/exp-run/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/exp-status/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/hiera-experiment/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/ideate/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/ingest/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/init/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/novelty/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/paper-compile/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/paper-draft/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/paper-plan/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/poster/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/prefill/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/rebuttal/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/refine/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
Diff text is unavailable under the recorded licenses. Line counts and the GitHub link remain available.
Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
No earlier version was observed for comparison.
i18n/zh/skills/research/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/reset/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/review/SKILL.md
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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i18n/zh/skills/setup/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
Diff text is unavailable under the recorded licenses. Line counts and the GitHub link remain available.
Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/survey/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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f676a037d498 → 3c3922f02a97
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → f676a037d498
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i18n/zh/skills/visualize/SKILL.md
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View on GitHubAdd to my skills
Verified commit 3c3922f02a97c347f66b91e1ded2371c963da538
git clone --filter=blob:none --no-checkout https://github.com/PKU-DAIR/AutoSci.git .hotskills/pku-dair-autosci && git -C .hotskills/pku-dair-autosci checkout --detach 3c3922f02a97c347f66b91e1ded2371c963da538
# Copy each selected skill directory from .hotskills/pku-dair-autosci into .claude/skills/<skill-name>/1.7kGitHub stars
9stars in 7 days
58skills in this repository
2commits in 30 days
Heat
5.0- Star growth, last 7 daysAhead of 74% of tracked repositories
- Star growth, last 24 hoursAhead of 71% of tracked repositories
- Rank movement, last 7 daysAhead of 12% of tracked repositories
- Commits, last 30 daysAhead of 59% of tracked repositories
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekAhead of 0% of tracked repositories
Heat never changes the order by stars, and sponsorship never touches it. How heat works
Stars over time
Individual skills in this repository
- ask
i18n/en/skills/ask - check
i18n/en/skills/check - daily-arxiv
i18n/en/skills/daily-arxiv - discover
i18n/en/skills/discover - edit
i18n/en/skills/edit - exp-design
i18n/en/skills/exp-design - exp-eval
i18n/en/skills/exp-eval - exp-pilot-eval
i18n/en/skills/exp-pilot-eval - exp-pilot-run
i18n/en/skills/exp-pilot-run - exp-run
i18n/en/skills/exp-run - exp-status
i18n/en/skills/exp-status - hiera-experiment
i18n/en/skills/hiera-experiment - ideate
i18n/en/skills/ideate - ingest
i18n/en/skills/ingest - init
i18n/en/skills/init - novelty
i18n/en/skills/novelty - paper-compile
i18n/en/skills/paper-compile - paper-draft
i18n/en/skills/paper-draft - paper-plan
i18n/en/skills/paper-plan - poster
i18n/en/skills/poster - prefill
i18n/en/skills/prefill - rebuttal
i18n/en/skills/rebuttal - refine
i18n/en/skills/refine - research
i18n/en/skills/research - reset
i18n/en/skills/reset - review
i18n/en/skills/review - setup
i18n/en/skills/setup - survey
i18n/en/skills/survey - visualize
i18n/en/skills/visualize - ask
i18n/zh/skills/ask - check
i18n/zh/skills/check - daily-arxiv
i18n/zh/skills/daily-arxiv - discover
i18n/zh/skills/discover - edit
i18n/zh/skills/edit - exp-design
i18n/zh/skills/exp-design - exp-eval
i18n/zh/skills/exp-eval - exp-pilot-eval
i18n/zh/skills/exp-pilot-eval - exp-pilot-run
i18n/zh/skills/exp-pilot-run - exp-run
i18n/zh/skills/exp-run - exp-status
i18n/zh/skills/exp-status - hiera-experiment
i18n/zh/skills/hiera-experiment - ideate
i18n/zh/skills/ideate - ingest
i18n/zh/skills/ingest - init
i18n/zh/skills/init - novelty
i18n/zh/skills/novelty - paper-compile
i18n/zh/skills/paper-compile - paper-draft
i18n/zh/skills/paper-draft - paper-plan
i18n/zh/skills/paper-plan - poster
i18n/zh/skills/poster - prefill
i18n/zh/skills/prefill - rebuttal
i18n/zh/skills/rebuttal - refine
i18n/zh/skills/refine - research
i18n/zh/skills/research - reset
i18n/zh/skills/reset - review
i18n/zh/skills/review - setup
i18n/zh/skills/setup - survey
i18n/zh/skills/survey - visualize
i18n/zh/skills/visualize
How it works
When your agent uses it
Ask the wiki a question, retrieve and synthesize relevant pages, optionally crystallize the answer back into the wiki
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
2,695 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /ask
> Ask a question to the wiki knowledge base. The LLM reads context_brief.md for global context,
> retrieves relevant pages, synthesizes an answer with citations. Good answers can be
> crystallized back into the wiki — written to outputs/, as new concept pages, or appended
> to an existing idea/method/output note — so exploration compounds like ingestion does.
## Inputs
- `question`: natural-language question (e.g. "What is the core difference between LoRA and Adapter?")
- `--crystallize` (optional): if specified, crystallize the answer back into the wiki (default: answer only, no write)
- `--format` (optional): output format, default `markdown`, options: `table` / `timeline` / `bullets`
## OutputsWhen your agent uses it
Scan the full wiki to detect health issues and produce a tiered fix-recommendation report (covers all entity types in runtime/schema/entities.yaml + graph consistency)
What it loads into context
Frontmatter
34 tokensAlways available to the agent
SKILL.md
2,303 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /check
> Scans the full wiki to detect structural, link, field, and graph health issues, and generates a tiered fix-recommendation report.
> Covers every entity type declared in `runtime/schema/entities.yaml` (papers, concepts, topics, people, ideas, experiments, methods, Summary, foundations), plus graph edge / citation consistency. Highlights include: idea novelty-score plausibility, idea failure-reason completeness, experiment `linked_idea` validity.
## Inputs
- Full wiki directory (default `wiki/`)
- Optional: `--json` flag (output JSON format via `tools/lint.py`)
- Optional: `--fix` flag (auto-fix deterministic issues)
- Optional: `--fix --dry-run` (preview fixes without applying them)
- Optional: `--suggest` flag (show recommendations for issues that cannot be auto-fixed)
## OutputsWhen your agent uses it
Run or manage the daily arXiv recommendation feed. Use for one-off fresh-paper recommendations, scheduled GitHub Actions setup/status/disable, email digests, and explicit high-confidence auto-ingest through /ingest.
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,627 tokensWhen the skill is activated
Reference documents
1,781 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Commands
- Inputs
- Setup Workflow
- Run Workflow
- Wiki Interaction
- Relationships
Scripts executed separately
../../../../tools/daily_arxiv.py
Files
SKILL.mdcore6,582 bytesSKILL.mdcore6,582 bytesSKILL.mdcore6,582 bytesSKILL.mdcore6,582 bytesreferences/automation-scaffold.mddoc4,089 bytesreferences/recommendation-and-ingest-policy.mddoc3,198 bytes../../../../tools/daily_arxiv.pyruns59,677 bytes
Read SKILL.md
# /daily-arxiv
> Run or manage the daily paper recommendation feed. Bare `/daily-arxiv` means "run today's recommendation pass now"; GitHub Actions is only the unattended scheduler for the same pipeline.
Load references only when needed:
- `references/recommendation-and-ingest-policy.md` — evidence, LLM decision schema, confidence gate, and auto-ingest guardrails
- `references/automation-scaffold.md` — GitHub Actions setup/status behavior, secrets, artifacts, and failure modes
## Commands
- `/daily-arxiv`: run a one-off recommendation pass now. If `config/daily-arxiv.yml` is missing, infer defaults from the wiki and continue.
- `/daily-arxiv setup`: create or repair `config/daily-arxiv.yml` from `config/daily-arxiv.yml.example`; ensure `.github/workflows/daily-arxiv.yml` exists and that its `daily-arxiv:` job's `env:` block exposes both `SEMANTIC_SCHOLAR_API_KEY` and `DEEPXIV_TOKEN` — **add the missing lines automatically** rather than asking the user to hand-edit YAML (without these exposures the prepare step rate-limits out, identical symptom to never setting the secrets); and explain required secrets. See *Setup Workflow* below for the exact patch procedure.
- `/daily-arxiv status`: inspect config, workflow presence, schedule, mode, API/e-mail secret availability, and recent artifacts when available.When your agent uses it
Build a ranked shortlist of candidate papers (anchor-driven, topic-driven, or derived from current wiki state) that the user — or an upstream skill — may decide to feed into `/ingest`. Use whenever the user asks "what should I read next", "find papers similar to this one", "recommend related work", "what's around this topic", or whenever `/ingest` is invoked with `--discover`. Does not ingest; only proposes.
What it loads into context
Frontmatter
142 tokensAlways available to the agent
SKILL.md
2,998 tokensWhen the skill is activated
Reference documents
3,081 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Internal Callers
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/discover.py../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/init_discovery.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /discover
> Produce a ranked shortlist of paper candidates from one of four seed modes. Surface them to the user (or to the calling skill) with rationales. Never auto-ingest — `/discover` is a proposal stage, `/ingest` is the action stage.
Use these local references on demand:
- `references/seed-modes.md` — when to pick anchor / topic / wiki / venue mode and how to translate the user's phrasing into one
- `references/ranking-signals.md` — what `tools/discover.py` scores on and why discovery does **not** share `/init`'s survey preference
- `references/wiki-dedup.md` — how candidates are filtered against `wiki/papers/` and what to do with matches
## Inputs
- `--anchor <id>` (repeatable): one or more anchor paper IDs (arXiv IDs preferred; S2 paperIds also accepted). Drives the **anchor mode** — the primary use case, including the post-`/ingest` "what to read next" flow.
- `--negative <id>` (repeatable, optional): IDs to push recommendations away from. Only meaningful with `--anchor`.edit
When your agent uses it
Add or remove raw sources, or update wiki content, per user request
What it loads into context
Frontmatter
28 tokensAlways available to the agent
SKILL.md
429 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
- Trigger
- Inputs
- Outputs
- Steps
- Constraints
Files
SKILL.mdcore1,761 bytes
Read SKILL.md
# /edit
> Add or remove raw sources, or update wiki content, per user request.
## Trigger
User manual: `/edit <user request>`
## Inputs
User request, for example:
- "Download this paper to raw/papers/"
- "Delete raw/papers/xxx.pdf"
- "Update the SOTA tracker in topics/efficient-llm-adaptation"When your agent uses it
Idea-driven experiment design with iterative ablation — method candidate generation (direct / hybrid / cross-idea combination) → benchmark selection → iterative ablation (non-linear: ablation can trigger method simplification and re-planning) → sensitivity analysis → main experiment → optional generalization → deep analysis of intermediate quantities. Use when designing a full experiment suite for an idea after pilot evaluation.
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
5,852 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /exp-design
> Design a complete, non-linear experiment suite for an idea.
> This skill supports method candidate generation, iterative ablation with method simplification, sensitivity analysis, and deep analysis of intermediate quantities.
> The ablation loop is the core non-linear feature: ablation results classify factors as essential/contributing/marginal/harmful, and marginal/harmful factors trigger method simplification and re-planning (capped at 2 iterations).
## Inputs
- `idea-slug`: the idea to design experiments for (reads from `wiki/ideas/{slug}.md`)
## Outputs
- Experiment wiki pages: `wiki/experiments/{exp-slug}.md` — one per experiment block (ablation, sensitivity, main, generalization, analysis), each with `status: planned` and `linked_idea` set
- Master design document: `experiments/designs/{slug}-master.md` — detailed specs for all experiment blocksWhen your agent uses it
Experiment verdict gate — Review LLM independently judges results → 4 verdict paths → auto-update the linked idea's status / failure_reason and graph edges
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
3,539 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytesSKILL.mdcore14,543 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-eval
> Convert completed experiment results into wiki knowledge updates.
> Review LLM acts as an impartial judge (following cross-model-review), independently evaluating how experimental results affect the linked idea's hypothesis.
> Four verdict paths: supported → idea validated / partially_supported → supplementary experiments /
> not_supported → idea failed / inconclusive → debug.
> Auto-updates the linked idea's `status`, `failure_reason`, and graph edges.
## Inputs
- `experiment`: slug from `wiki/experiments/` (status must be `completed`)
- `--auto` (optional): automatic mode — do not pause for user confirmation before wiki updates (used when called by /research)
## OutputsWhen your agent uses it
Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
1,979 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore7,829 bytesSKILL.mdcore7,829 bytesSKILL.mdcore7,829 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-pilot-eval
> Evaluate pilot experiment results and update the linked idea page.
> Reads pilot results from `experiments/pilot/code/{slug}/results/`, applies verdict logic (pass/fail/inconclusive), and updates the idea's `pilot_result`, `failure_reason`, and `status` fields.
> Called by `/ideate` Phase 5 after `/exp-pilot-run` completes.
## Inputs
- `idea-slug`: slug of the idea whose pilot was just run
- `--auto` (optional): automatic mode, no pause for user confirmation (used when called by `/research`)
## Outputs
- `wiki/ideas/{slug}.md` — updated `pilot_result` (always), `failure_reason` (if failed), `status` (if failed → `failed`)When your agent uses it
Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
3,584 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/remote.py../../../../tools/remote.py
Files
SKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytesSKILL.mdcore15,288 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/remote.pyruns29,286 bytes
Read SKILL.md
# /exp-pilot-run
> Execute a pilot experiment described by a Pilot Spec YAML file.
> Reads the spec from `experiments/pilot/{slug}.yaml`, writes pilot code, runs the experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), and returns raw results to the caller.
>**No matter which operating mode is adopted, before the experimental code is ready for deployment and operation, confirmation shall be obtained from users. Users need to manually check relevant information including codes and experimental configurations(Such as dataset paths, interface parameter selection, API configuration and so on). The operation can only be launched after confirmation. Otherwise, revisions shall be made repeatedly until users approve the execution.**
> Supports **local** (direct GPU) and **remote** (SSH deployment via `tools/remote.py`) modes.
> Does NOT modify any wiki pages. Does NOT judge pass/fail — results are evaluated by `/exp-pilot-eval`.
## Inputs
- `idea-slug`: slug used to locate `experiments/pilot/{slug}.yaml`
- `--env local|remote` (optional, default `local`): deployment environment
- `local`: run directly on local GPU
- `remote`: deploy to remote machine via SSH (requires `config/server.yaml`)When your agent uses it
Full experiment execution pipeline — prepare code → deploy(Confirm with the user before operation and ask the applicant to conduct manual inspection) → monitor → collect results, supporting three run modes
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
4,807 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/remote.py../../../../tools/remote.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /exp-run
> Execute an experiment that has been planned in wiki/experiments/.
> **No matter which operation mode it is, before preparing the experimental codes and deploying them for operation, confirmation shall be obtained from users. Users need to manually check relevant information such as codes and experimental configurations(Dataset paths, interface parameter selection, API configuration, etc.). The operation can only be launched after confirmation; otherwise, revisions shall be made repeatedly until users approve the execution.**
> **Three run modes** for different scenarios:
> - **Default (deploy)**: Phase 1-2 only — deploy and return immediately. Best for experiments that take hours or days.
> - **`--collect`**: Phase 3-4 only — check whether a deployed experiment has finished; collect results if so (`--check` is an alias).
> - **`--full`**: All four phases end-to-end. Best for short local experiments that finish in minutes.
>
> Recommended flow: `/exp-run <slug>` to deploy → `/exp-status` to monitor → `/exp-run <slug> --collect` to collect.
## Inputs
- `experiment`: slug from wiki/experiments/When your agent uses it
View the status of all running experiments; optionally auto-collect completed experiments and advance the pipeline
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
2,399 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/remote.py../../../../tools/remote.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,637 bytesSKILL.mdcore9,637 bytesSKILL.mdcore9,637 bytesSKILL.mdcore9,637 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-status
> Unified experiment status monitoring entry point.
> Scans all `running` experiments, performs a live status check on each (screen session / SSH),
> and outputs a status table (alive / anomaly / completed) to guide the user's next actions.
>
> When used with `/research --auto`, acts as a periodic checker scheduled by CronCreate:
> when all experiments in a pipeline are completed, automatically triggers `/research --start-from stage4`.
## Inputs
- No arguments (default): check all `running` experiments, print status table
- `--pipeline <slug>` (optional): check only experiments belonging to the specified pipeline; additionally print overall pipeline progress
- `--collect-ready` (optional): auto-call `/exp-run --collect` for all experiments whose session has already endedWhen your agent uses it
Run the optional Hiera-style iterative candidate search for an existing AutoSci experiment while keeping wiki knowledge and the default experiment workflow unchanged
What it loads into context
Frontmatter
79 tokensAlways available to the agent
SKILL.md
4,120 tokensWhen the skill is activated
Reference documents
6,698 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose and activation boundary
- State model and command ownership
- User interaction protocol
- Stage rules
- Contract and command invariants
- Local and remote execution
- Failure, idempotency, and safety
- Required result after each action
Files
README.mddoc20,867 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesSKILL.mdcore19,708 bytesreferences/interface.mddoc8,848 bytes
Read SKILL.md
# /hiera-experiment
## Purpose and activation boundary
Use this skill only after the user explicitly selects the optional Hiera path for an existing AutoSci experiment. Hiera is an isolated search sidecar:
- It reads the linked wiki experiment/design and runtime contract as inputs.
- It stores all Hiera state below runs/hiera/<experiment>/<run-id>/.
- It searches immutable candidate snapshots and records evidence in the sidecar ledger.
- It never creates wiki entities, changes wiki schema or experiment status, rewrites wiki/log.md, or writes search results back to the wiki.
- It does not replace /exp-design, /exp-run, /exp-eval, or /research. A confirmatory result must return to the normal, user-gated workflow.
Before creating or changing a run, read:
When your agent uses it
Multi-phase research idea generation pipeline: landscape scan → dual-model brainstorm → filter & validation → write to wiki → pilot
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
7,420 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /ideate
> Generates high-quality research ideas through a 5-phase pipeline, grounded in the wiki knowledge base and external search.
> Phase 1 scans the research landscape (wiki + WebSearch + S2), Phase 2 runs a dual-model brainstorm (Claude + Review LLM independently),
> Phase 3 applies first-pass filter + deep validation (feasibility, novelty, review), Phase 4 writes ideas to the wiki (including eliminated ideas, with failure reasons recorded as anti-repetition memory),
> Phase 5 runs pilot experiments on surviving ideas (idea pages already exist) and updates results.
## Inputs
- `direction` (optional): research direction, keywords, or specific problem description. If omitted, automatically selects the most valuable direction from open_questions.md.
- `--max-ideas N` (optional, default 3): maximum number of ideas to write to the wiki
- `--skip-validation`: skip Phase 3 Step 2 deep validation (skip /novelty and /review; fast mode: first-pass filter only)
- `--skip-pilot`: skip Phase 5 pilot experiments (fast mode: Phase 1–4 only)
- `--auto`: fully automatic mode, no pause for user confirmation (used when called by /research)When your agent uses it
Ingest a paper into the wiki — creates pages (papers + concepts + methods + people) and builds all cross-references and graph edges. Trigger whenever the user says "ingest", "add this paper", drops a `.pdf` / `.tex` / arXiv URL, or asks to fold a paper into the knowledge base.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
5,345 tokensWhen the skill is activated
Reference documents
6,002 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/discover.py../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/init_discovery.py../../../../tools/prepare_paper_source.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py
Files
SKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesSKILL.mdcore21,014 bytesreferences/cross-references.mddoc6,866 bytesreferences/dedup-policy.mddoc5,943 bytesreferences/error-handling.mddoc3,984 bytesreferences/init-mode.mddoc5,302 bytesreferences/pdf-preprocessing.mddoc4,007 bytes../../../../tools/discover.pyruns48,434 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/init_discovery.pyruns66,555 bytes../../../../tools/prepare_paper_source.pyruns27,298 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/serve.pyruns43,512 bytes../../../../tools/visualize.pyruns25,232 bytes
Read SKILL.md
# /ingest
Turn one paper into a fully wired set of wiki pages. Emit well-formed entities and correct cross-references; leave semantic audits (backlink symmetry, dangling nodes, field-value policing) for `/check`.
Use these local references on demand:
- `references/pdf-preprocessing.md` — arXiv-ID recovery, tex fetching, prepare-paper handoff for direct PDF drops
- `references/dedup-policy.md` — merge-vs-create decision rule for concepts and methods, and the line that separates `/ingest` shape checks from `/check` semantic audits
- `references/cross-references.md` — forward/reverse link matrix and paper-to-paper edge-type selection
- `references/init-mode.md` — manifest-driven handoff from `/init` and parallel-safety conventions
- `references/error-handling.md` — source parse, API, and slug-collision fallbacks
Open `runtime/schema/entities.yaml` for frontmatter field definitions and `runtime/templates/{kind}.md.tmpl` for body section structure. For `index.md`, `log.md`, and `graph/` shapes, see `runtime/schema/conventions.yaml` and `runtime/schema/edges.yaml`.
When your agent uses it
Bootstrap ΩmegaWiki from user sources plus optional discovery, then ingest the final paper set in parallel
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
4,365 tokensWhen the skill is activated
Reference documents
2,172 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/backfill_citations.py../../../../tools/init_discovery.py../../../../tools/lint.py../../../../tools/prepare_paper_source.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py
Files
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Read SKILL.md
# /init
> Build a wiki from `raw/` with deterministic source preparation, planner-guided discovery, provisional notes/web scaffolding, and parallel `/ingest` fan-out/fan-in.
Use these local references on demand:
- `references/prepare-and-discovery.md` — prepare flow, final selection, fetch, and source-manifest rules
- `references/planner-policy.md` — planner behavior and LLM trim expectations
- `references/parallel-ingest.md` — worktree isolation, subagent prompt contract, merge, and cleanup
## Inputs
- `topic` (optional): research direction keywords; omit when `raw/` already defines the seed set
- `--no-introduction` (optional): disable external discovery; use only when the user explicitly requests itWhen your agent uses it
Multi-source novelty verification — WebSearch + Semantic Scholar + wiki + Review LLM cross-verify — outputs novelty score and recommendations. Optionally writes the score back to an idea page with --write.
What it loads into context
Frontmatter
65 tokensAlways available to the agent
SKILL.md
2,729 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore10,927 bytesSKILL.mdcore10,927 bytesSKILL.mdcore10,927 bytesSKILL.mdcore10,927 bytesSKILL.mdcore10,927 bytesSKILL.mdcore10,927 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /novelty
> Verify the novelty of a research idea or method using multiple sources. Searches WebSearch,
> Semantic Scholar, existing wiki work, and arXiv recent preprints, then Review LLM cross-verifies.
> Outputs a novelty score (1-5), closest prior work, differentiation points, and next-step recommendations.
> Can be used standalone or called by /ideate Phase 4.
## Inputs
- `target`: one of the following:
- free-text description of the idea (a paragraph or a few sentences)
- slug of an ideas/ page in the wiki (e.g. `sparse-lora-for-edge-devices`)
- paper title or arXiv URL (check novelty of that paper's method)
- `--quick`: fast mode, skip Review LLM cross-verify (Step 3), search onlyWhen your agent uses it
LaTeX compile → PDF — latexmk compile + auto-fix + page count/anonymity/font/[UNCONFIRMED] checks + submission checklist
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
2,441 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytesSKILL.mdcore9,473 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-compile
> Compile a LaTeX paper to PDF, auto-fix common errors, and verify submission requirements.
> Input: the paper/ directory generated by /paper-draft. Run latexmk compilation,
> parse errors and attempt auto-fix (missing packages, undefined references, figure paths).
> Verify page limit, anonymous compliance, font embedding, and clearance of [UNCONFIRMED] markers.
> Generate a submission checklist.
## Inputs
- `paper_dir` (optional, default `paper/`): LaTeX project directory containing `main.tex`
- `--fix` (optional): enable auto-fix mode (automatically install missing packages, correct paths)
- `--checklist` (optional): generate a detailed submission checklist (check only, no compilation)
When your agent uses it
Draft a LaTeX paper from PAPER_PLAN — write each section from wiki sources + generate figures/tables + BibTeX verification + de-AI polish
What it loads into context
Frontmatter
55 tokensAlways available to the agent
SKILL.md
3,500 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore14,066 bytesSKILL.mdcore14,066 bytesSKILL.mdcore14,066 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-draft
> Draft a complete LaTeX paper from the PAPER_PLAN.md generated by /paper-plan.
> Write section by section: each section draws material from wiki ideas/methods/experiments/papers/concepts,
> generates LaTeX + figures + tables. BibTeX is fetched from DBLP/CrossRef (following citation-verification).
> Apply de-AI polish after completion (following academic-writing).
> Optional per-section Review LLM review. Output a compilable paper/ directory.
## Inputs
- `plan`: path to PAPER_PLAN.md (e.g. `wiki/outputs/paper-plan-sparse-lora-2026-04-08.md`)
- `--review` (optional): enable per-section Review LLM review
- `--sections` (optional): write only specified sections (e.g. `--sections 3,4` writes only Method + Experiments); used for incremental writing
When your agent uses it
Compile a paper outline from the idea graph — evidence map → narrative structure → section plan + figure plan + citation plan, Review LLM review mandatory
What it loads into context
Frontmatter
69 tokensAlways available to the agent
SKILL.md
4,171 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-plan
> Compile a paper outline from the wiki's idea graph.
> Input target ideas (status: validated or in-progress with succeeded experiments), specify the target venue,
> compile an evidence map from the wiki → determine narrative structure → generate a section outline + figure plan + citation plan.
> Review LLM review is a mandatory step (acting as area chair to assess outline persuasiveness).
> Output PAPER_PLAN.md to wiki/outputs/.
>
> Key distinction: the outline is idea-graph-driven — each section exists because it supports an idea (or its evidence/methods),
> not because paper convention requires that section.
## Inputs
- `ideas`: list of target idea slugs (space-separated)When your agent uses it
Generate an academic poster from a drafted paper — distill sections into a single-page HTML poster with figures and inter-section transitions
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
12,248 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/rasterize_latex.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py
Files
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Read SKILL.md
# /poster
> Generate an academic HTML poster from a drafted paper. Reads `paper/main.tex`,
> section files, and figures; builds a PaperX-compatible `dag.json` intermediate;
> distills each section into a 2–5 sentence summary; selects representative figures;
> renders into a self-contained HTML poster with a 3-column auto-fit layout.
## Inputs
### Common
- `paper_dir` (optional, default `paper/`): LaTeX project directory containing `main.tex` and `sections/`
- `--review` (optional): cross-model Review LLM critique of the generated poster content
- `--anonymous` (optional): force authors to "Anonymous" regardless of `\author{}` content, the `paper/.author_display.txt` cache, or `--authors`When your agent uses it
Seed wiki/foundations/ with domain background knowledge so subsequent /ingest does not create duplicate concept pages for textbook material
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,609 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
- Trigger
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/fetch_wikipedia.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore6,378 bytesSKILL.mdcore6,378 bytesSKILL.mdcore6,378 bytesSKILL.mdcore6,378 bytesfoundations-catalog.yamlasset3,448 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/fetch_wikipedia.pyruns4,556 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /prefill
> Sediments foundational background (seminal methods, common practice, standard architectures) into `wiki/foundations/` as **terminal** pages.
> Foundations are single-direction by design: other pages link to them, foundations write no reverse links.
## Trigger
Manual: `/prefill [domain]` or `/prefill --add "concept name"`.
## Inputs
- `domain` *(positional, optional)*: research domain — one of `general`, `NLP`, `CV`, `ML Systems`, `Robotics`. If omitted, infer from `wiki/topics/` tags; if `wiki/topics/` is empty, prompt the user.
- `--add "<concept>"`: skip the catalog and seed exactly one foundation by name.
When your agent uses it
Parse review comments → atomize concerns (Rvx-Cy) → map to wiki ideas/methods → check evidence → Review LLM stress-test → generate rebuttal
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
3,964 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytesSKILL.mdcore16,225 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /rebuttal
> Parse review comments, atomize each concern (Rvx-Cy numbering) and map it to a wiki idea or method,
> check whether evidence is sufficient (tracing back to wiki experiments),
> simulate reviewer follow-up questions with Review LLM (stress-test, scored 1-5), and generate
> a formal plain-text rebuttal and a rich-text rebuttal.
> Safety checks ensure no fabrication, no overpromise, full coverage.
## Inputs
- `review`: source of review comments, one of:
- file path (e.g. `raw/reviews/reviewer1.txt`, `raw/reviews/meta-review.md`)
- multiple file paths (comma-separated: `raw/reviews/R1.txt,raw/reviews/R2.txt,raw/reviews/R3.txt`)
- directly pasted review textWhen your agent uses it
General-purpose multi-round iterative improvement — repeatedly calls /review on any research artifact, parses feedback, applies fixes, updates wiki, until the target score is reached
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
2,442 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /refine
> General-purpose multi-round iterative improvement loop for any research artifact
> (idea, proposal, experiment plan, paper draft).
> Each round calls /review for structured feedback → parses actionable items → Claude fixes the artifact →
> updates wiki entities → re-reviews, until the score reaches the target or the maximum rounds are exhausted.
> Outputs an improvement history and the final review score.
## Inputs
- `artifact`: the artifact to improve, one of:
- slug of a wiki page (searched in ideas/experiments/methods/outputs/)
- file path (e.g. `wiki/outputs/paper-draft-v1.md`)
- `--max-rounds N` (optional, default 4): maximum iteration roundsWhen your agent uses it
End-to-end research orchestrator — idea discovery → experiment design → execution → verdict → paper writing, with human gates and session-resumable state
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
5,747 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
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Read SKILL.md
# /research
> End-to-end research orchestrator that composes all skills into a complete research workflow.
> Stage 0 (Bootstrap) + 5 Stages + 2 Human Gates, covering the full pipeline from empty wiki to paper submission.
> **Zero-friction entry**: if the wiki is cold, research pauses at Stage 0 and requires explicit bootstrap via `/init` / `$init` before continuing.
> Every Gate and Stage saves progress to `wiki/outputs/pipeline-progress.md`, supporting cross-session recovery.
>
> **Stage 3 is non-blocking**: experiments are deployed and control returns immediately (`--auto` mode automatically sets up a CronCreate to monitor every 30 minutes).
> When all experiments finish, Stage 4 is triggered automatically. Use `/exp-status` at any time to check progress.
>
> `--auto` mode skips manual confirmation (automatically selects the top-1 idea). `--skip-paper` runs the research without writing a paper.
## Inputs
When your agent uses it
Reset wiki state to a clean scaffold by scope (wiki / raw / log / checkpoints / all). Useful during development or carefree restarts after a botched setup.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
1,089 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
- Trigger
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/reset_wiki.py
Files
SKILL.mdcore4,150 bytesSKILL.mdcore4,150 bytesSKILL.mdcore4,150 bytesSKILL.mdcore4,150 bytesSKILL.mdcore4,150 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/reset_wiki.pyruns6,410 bytes
Read SKILL.md
# /reset
> Resets the wiki to a clean scaffold by scope. Designed for development iteration and recovery after a failed setup — not a routine operation.
## Trigger
Manual: `/reset --scope wiki` / `--scope raw` / `--scope log` / `--scope checkpoints` / `--scope all`. Multiple scopes may be combined comma-separated: `--scope wiki,log`.
## Inputs
- `--scope` *(required)*: one of
- `wiki` — delete every `*.md` under `wiki/<entity>/` and `wiki/outputs/`, plus `wiki/index.md`, `wiki/log.md`, and `wiki/graph/` files. Preserves `.gitkeep` and `wiki/CLAUDE.md`.
- `raw` — delete every entry under `raw/papers/`, `raw/discovered/`, `raw/tmp/`, `raw/notes/`, `raw/web/` (except `.gitkeep`).
- `log` — reset `wiki/log.md` to the empty header.When your agent uses it
General-purpose cross-model review — Review LLM independently reviews any research artifact, outputs structured scores, wiki entity mapping, and improvement suggestions
What it loads into context
Frontmatter
65 tokensAlways available to the agent
SKILL.md
3,056 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Files
SKILL.mdcore12,795 bytesSKILL.mdcore12,795 bytes
Read SKILL.md
# /review
> Review any research artifact (idea, proposal, experiment plan, paper draft, method) using cross-model review.
> Uses Review LLM as an independent reviewer. Outputs a structured score, actionable improvement suggestions,
> and a mapping to wiki entities (which ideas/methods need strengthening, which gaps are discovered).
> Supports three difficulty levels (standard / hard / adversarial) and four review focuses.
> Can be used standalone or called by /ideate, /refine, /exp-design.
## Inputs
- `artifact`: the artifact to review, one of:
- slug of a wiki page (e.g. `sparse-lora-for-edge-devices`, searched in ideas/experiments/methods/)
- file path (e.g. `wiki/outputs/paper-draft-v1.md`)
- free text (directly pasted proposal or idea description)When your agent uses it
Interactive API key configuration guide — checks current .env state and walks you through Semantic Scholar, DeepXiv, and Review LLM setup
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
2,384 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/_env.py
Files
SKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytesSKILL.mdcore9,171 bytes../../../../tools/_env.pyruns1,482 bytes
Read SKILL.md
# /setup
> Guides you through ΩmegaWiki's optional API key configuration.
> Reads your current `.env`, shows what is and isn't configured, and helps you
> set up each key with clear explanations of what it does and how to get it.
> Safe to re-run at any time — only updates keys you choose to configure.
## Inputs
- No arguments required
- Reads: `.env` (current configuration state)
- Reads: `config/setup-guide.md` (reference for what each key does)
## OutputsWhen your agent uses it
Generate a Related Work section for a paper from wiki knowledge — thematic grouping → narrative structure → LaTeX output, following citation-verification and academic-writing
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
2,419 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,704 bytesSKILL.mdcore9,704 bytesSKILL.mdcore9,704 bytesSKILL.mdcore9,704 bytesSKILL.mdcore9,704 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /survey
> Generate a Related Work section ready for direct use in a paper, based on existing wiki knowledge.
> Draw material from wiki/papers/, concepts/, topics/; group by research direction (not paper-by-paper listing).
> End each group with a statement of how it differs from this work. Citations follow citation-verification.md;
> writing follows academic-writing.md Related Work rules.
> Supports LaTeX and Markdown output formats.
## Inputs
- `query`: one of:
- research question description (free text, e.g. "parameter-efficient fine-tuning for LLMs")
- list of idea slugs (from wiki/ideas/, used to organize related work around specific ideas)
- path to PAPER_PLAN.md (extract Related Work section definition from it)When your agent uses it
Generate and update visualization artifacts — Obsidian graph config and Canvas knowledge maps. The interactive web graph view lives in the SPA at app/modules/graph.js (served by tools/serve.py).
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
2,966 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Color Palette
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/lint.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py
Files
SKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytesSKILL.mdcore11,322 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/serve.pyruns43,512 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes
Read SKILL.md
# /visualize
> Generate visualization artifacts for the OmegaWiki knowledge graph.
> Produces Obsidian graph config (color groups by entity type) and curated
> Canvas views with labeled typed edges. For interactive web exploration
> use the SPA Graph view (`tools/serve.py`, then `#/graph`).
## Inputs
- `--obsidian` (optional): Generate/update `.obsidian/graph.json` with entity-type color groups
- `--canvas` (optional): Generate Obsidian Canvas (`.canvas`) from graph data with labeled edges
- `--focus <node_id>` (optional): Center canvas on a specific node (e.g., `methods/my-method`)
- `--depth N` (optional): BFS depth for focused canvas (default: 2)
- `--types <list>` (optional): Filter nodes to these page types, comma-separated (e.g., `papers,concepts`)When your agent uses it
对 wiki 提问，综合检索相关页面后回答，好的回答可 crystallize 回 wiki
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
2,831 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore10,127 bytesSKILL.mdcore10,127 bytesSKILL.mdcore10,127 bytesSKILL.mdcore10,127 bytesSKILL.mdcore10,127 bytesSKILL.mdcore10,127 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /ask
> 对 wiki 知识库提问。LLM 读取 context_brief.md 获取全局上下文，检索相关页面，
> 综合回答并附带引用。好的回答可以 crystallize 回 wiki——写入 outputs/、创建新的
> concept 页面，或追加到已有的 idea/method/output 笔记上，让探索成果像 ingest 一样持续积累。
## Inputs
- `question`：自然语言问题（如 "LoRA 和 Adapter 的核心区别是什么？"）
- `--crystallize`（可选）：若指定，将回答 crystallize 回 wiki（默认仅回答不写入）
- `--format`（可选）：输出格式，默认 `markdown`，可选 `table` / `timeline` / `bullets`
## Outputs
When your agent uses it
扫描全 wiki 发现健康问题，生成分级修复建议报告（覆盖 runtime/schema/entities.yaml 中全部 entity 类型 + graph 一致性）
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
2,464 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/lint.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore8,890 bytesSKILL.mdcore8,890 bytesSKILL.mdcore8,890 bytesSKILL.mdcore8,890 bytesSKILL.mdcore8,890 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /check
> 扫描全 wiki，发现结构、链接、字段、graph 的健康问题，生成分级修复建议。
> 覆盖 `runtime/schema/entities.yaml` 中声明的所有 entity 类型（papers, concepts, topics, people, ideas, experiments, methods, Summary, foundations），以及 graph edge / citation 一致性。重点检查包括：idea novelty-score 合理性、idea 失败原因完整性、experiment `linked_idea` 有效性。
## Inputs
- 全 wiki 目录（默认 `wiki/`）
- 可选：`--json` 标志（通过 tools/lint.py 输出 JSON 格式）
- 可选：`--fix` 标志（自动修复确定性问题）
- 可选：`--fix --dry-run`（预览修复但不执行）
- 可选：`--suggest` 标志（显示非自动修复问题的建议）
## OutputsWhen your agent uses it
运行或管理每日 arXiv 推荐 feed。用于手动获取新论文推荐、配置/检查/停用 GitHub Actions 定时任务、邮件 digest，以及显式高置信 auto-ingest。
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,582 tokensWhen the skill is activated
Reference documents
1,650 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Commands
- Inputs
- Setup Workflow
- Run Workflow
- Wiki Interaction
- Relationships
Scripts executed separately
../../../../tools/daily_arxiv.py
Files
SKILL.mdcore5,819 bytesSKILL.mdcore5,819 bytesSKILL.mdcore5,819 bytesSKILL.mdcore5,819 bytesreferences/automation-scaffold.mddoc2,937 bytesreferences/recommendation-and-ingest-policy.mddoc3,229 bytes../../../../tools/daily_arxiv.pyruns59,677 bytes
Read SKILL.md
# /daily-arxiv
> 运行或管理每日论文推荐 feed。裸 `/daily-arxiv` 表示“现在跑一次今天的推荐”；GitHub Actions 只是同一条 pipeline 的无人值守调度器。
按需读取 reference：
- `references/recommendation-and-ingest-policy.md` — evidence、LLM 决策 schema、置信度门控和 auto-ingest 约束
- `references/automation-scaffold.md` — GitHub Actions setup/status、secrets、artifacts 与失败行为
## Commands
- `/daily-arxiv`：现在跑一次推荐。如果缺少 `config/daily-arxiv.yml`，从 wiki 推断默认值后继续。
- `/daily-arxiv setup`：从 `config/daily-arxiv.yml.example` 创建或修复配置，检查 `.github/workflows/daily-arxiv.yml`，并说明需要的 secrets。
- `/daily-arxiv status`：检查 config、workflow、schedule、mode、API/e-mail secrets 可用性，以及最近 artifacts。When your agent uses it
基于 anchor 论文、topic 关键词或当前 wiki 状态，产出一份排好序的候选论文 shortlist，供用户或上游 skill 决定是否进一步 `/ingest`。当用户问 "接下来该读什么"、"找和这篇相似的论文"、"推荐相关工作"、"这个方向周围有什么" 时触发；`/ingest --discover` 也会内部调用本 skill。本身不 ingest，只提出候选。
What it loads into context
Frontmatter
157 tokensAlways available to the agent
SKILL.md
3,260 tokensWhen the skill is activated
Reference documents
3,644 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Internal Callers
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/discover.py../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/init_discovery.py../../../../tools/research_wiki.py
Files
SKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesSKILL.mdcore11,773 bytesreferences/ranking-signals.mddoc7,476 bytesreferences/seed-modes.mddoc3,574 bytesreferences/wiki-dedup.mddoc2,494 bytes../../../../tools/discover.pyruns48,434 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/init_discovery.pyruns66,555 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /discover
> 从四种 seed 模式之一产出一份排好序的候选论文 shortlist，附带每条候选的 rationale，呈现给用户或调用方 skill。`/discover` 绝不自动 ingest —— 它只负责提出候选，实际动作由 `/ingest` 负责。
按需打开下列本地参考文件：
- `references/seed-modes.md` —— 如何把用户的措辞映射到 anchor / topic / wiki / venue 模式，以及四者的选择规则
- `references/ranking-signals.md` —— `tools/discover.py` 的打分依据，以及为什么 discovery 不共享 `/init` 的 survey 偏好
- `references/wiki-dedup.md` —— 候选如何被过滤掉已 ingest 的论文，以及 dedup 边界
## Inputs
- `--anchor <id>`（可重复）：一或多个 anchor 论文 ID（优先 arXiv ID，也接受 S2 paperId）。驱动 **anchor 模式** —— 主要使用场景，包括 `/ingest` 后的 "接下来该读什么"。
- `--negative <id>`（可重复，可选）：希望推开的论文 ID。只在配合 `--anchor` 时有意义。edit
When your agent uses it
根据用户要求增删 raw sources 或更新 wiki 内容
What it loads into context
Frontmatter
25 tokensAlways available to the agent
SKILL.md
445 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
- 触发
- 输入
- 输出
- 步骤
- 约束
Files
SKILL.mdcore1,541 bytes
Read SKILL.md
# /edit
> 根据用户要求增删 raw sources 或更新 wiki 内容。
## 触发
用户手动：`/edit <用户要求>`
## 输入
用户请求，例如：
- "把这篇论文下载到 raw/papers/"
- "删除 raw/papers/xxx.pdf"
- "更新 topics/efficient-llm-adaptation 的 SOTA tracker"When your agent uses it
基于idea的实验设计（含迭代消融） — 方法候选生成（直接实现/混合融合/跨idea结合） → 基准选择 → 迭代消融（非线性：消融可触发方法简化与重新规划）→ 敏感度分析 → 主实验 → 可选泛化实验 → 中间量深度分析。在预实验评估后为idea设计完整实验套件时使用。
What it loads into context
Frontmatter
108 tokensAlways available to the agent
SKILL.md
6,469 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore22,404 bytesSKILL.mdcore22,404 bytesSKILL.mdcore22,404 bytesSKILL.mdcore22,404 bytesSKILL.mdcore22,404 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-design
> 为idea设计完整、非线性的实验套件。
> 本skill支持方法候选生成、带方法简化的迭代消融、敏感度分析和中间量深度分析。
> 消融循环是非线性的核心：消融结果将各因子分类为必要/贡献/边际/有害，边际/有害因子触发方法简化和重新规划（上限2次迭代）。
## Inputs
- `idea-slug`：要为其设计实验的idea（从 `wiki/ideas/{slug}.md` 读取）
## Outputs
- 实验wiki页面：`wiki/experiments/{exp-slug}.md` — 每个实验块一个页面（ablation、sensitivity、main、generalization、analysis），每个页面 `status: planned`，`linked_idea` 已设置
- 主设计文档：`experiments/designs/{slug}-master.md` — 各实验块的详细specWhen your agent uses it
实验判决门：Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 linked idea 的 status / failure_reason 与 graph edges
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
3,735 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytesSKILL.mdcore13,920 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-eval
> 将已完成实验的结果转化为 wiki 知识更新。
> Review LLM 作为 impartial judge（遵循 cross-model-review），独立评估实验结果对 linked idea 的 hypothesis 的影响。
> 4 种判决路径：supported → idea validated / partially_supported → 补充实验 /
> not_supported → idea failed / inconclusive → debug。
> 自动更新 linked idea 的 `status`、`failure_reason` 与 graph edges。
## Inputs
- `experiment`：wiki/experiments/ 中的 slug（status 必须为 `completed`）
- `--auto`（可选）：自动模式，不暂停等待用户确认 wiki 更新（用于 /research 调用）
## OutputsWhen your agent uses it
预实验结果评估 — 读取预实验结果，应用成功标准，更新 idea 页面（pilot_result，失败时更新 failure_reason），生成 PILOT_VERDICT_REPORT。由 /ideate Phase 5 在 /exp-pilot-run 之后调用。
What it loads into context
Frontmatter
69 tokensAlways available to the agent
SKILL.md
2,146 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore7,642 bytesSKILL.mdcore7,642 bytesSKILL.mdcore7,642 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-pilot-eval
> 评估预实验结果并更新关联的 idea 页面。
> 从 `experiments/pilot/code/{slug}/results/` 读取预实验结果，应用判定逻辑（pass/fail/inconclusive），更新 idea 的 `pilot_result`、`failure_reason` 和 `status` 字段。
> 由 `/ideate` Phase 5 在 `/exp-pilot-run` 完成后调用。
## Inputs
- `idea-slug`：刚完成预实验的 idea 的 slug
- `--auto`（可选）：自动模式，不暂停等待用户确认（由 `/research` 调用时使用）
## Outputs
- `wiki/ideas/{slug}.md` — 更新 `pilot_result`（始终）、`failure_reason`（失败时）、`status`（失败时 → `failed`）When your agent uses it
预实验执行 — 读取 Pilot Spec YAML，撰写预实验代码，运行实验(运行前需向用户确认，申请用户手动检查)，返回结果。由 /ideate Phase 5 调用。不修改 wiki 页面，不判定 pass/fail。
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
3,843 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/remote.py../../../../tools/remote.py
Files
SKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytesSKILL.mdcore13,958 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/remote.pyruns29,286 bytes
Read SKILL.md
# /exp-pilot-run
> 执行由 Pilot Spec YAML 文件描述的预实验。
> 从 `experiments/pilot/{slug}.yaml` 读取 spec，撰写预实验代码，运行实验(运行前需向用户确认，申请用户手动检查)，返回原始结果给调用者。
> **不论是哪种运行模式，在准备好实验代码，准备部署运行前需向用户确认，申请用户手动检查代码、实验配置(如数据集路径，接口参数选择，API 配置等)相关信息，确认无误后运行，否则需执行修改直到用户确认执行**
> 支持 **local**（本地 GPU）和 **remote**（通过 `tools/remote.py` SSH 部署）两种模式。
> 不修改任何 wiki 页面。不判定 pass/fail — 结果由 `/exp-pilot-eval` 评估。
## Inputs
- `idea-slug`：用于定位 `experiments/pilot/{slug}.yaml` 的 slug
- `--env local|remote`（可选，默认 `local`）：部署环境
- `local`：在本地 GPU 直接运行
- `remote`：通过 SSH 部署到远程机器（需要 `config/server.yaml`）When your agent uses it
实验执行全流程：准备代码 → 部署运行(运行前需向用户确认，申请用户手动检查) → 监控状态 → 收集结果，支持三种运行模式
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
5,160 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/remote.py../../../../tools/remote.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytesSKILL.mdcore18,687 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-run
> 执行 wiki/experiments/ 中已规划的实验。
> **不论是哪种运行模式，在准备好实验代码，准备部署运行前需向用户确认，申请用户手动检查代码、实验配置(如数据集路径，接口参数选择，API 配置等)相关信息，确认无误后运行，否则需执行修改直到用户确认执行**
> **三种运行模式**，适应不同场景：
> - **默认（deploy）**：仅 Phase 1-2，部署后立即返回，适合需要数小时/天的实验。
> - **`--collect`**：仅 Phase 3-4，检查已部署实验是否完成，完成则收集结果（`--check` 为 alias）。
> - **`--full`**：完整 Phase 1-4，适合几分钟内即可完成的本地快速实验。
>
> 推荐流程：`/exp-run <slug>` 部署 → `/exp-status` 监控 → `/exp-run <slug> --collect` 收集。
## Inputs
- `experiment`：wiki/experiments/ 中的 slugWhen your agent uses it
查看所有运行中实验的状态，可选自动收集已完成实验并推进流水线
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
2,540 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/remote.py../../../../tools/remote.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,293 bytesSKILL.mdcore9,293 bytesSKILL.mdcore9,293 bytesSKILL.mdcore9,293 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/remote.pyruns29,286 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /exp-status
> 统一的实验状态监控入口。
> 扫描所有 `running` 实验，对每个实验执行实时状态检查（screen session / SSH），
> 输出状态表（alive / anomaly / completed），引导用户下一步操作。
>
> 与 `/research --auto` 配合时作为 CronCreate 调度的定期检查器：
> 当 pipeline 的所有实验都完成时，自动触发 `/research --start-from stage4`。
## Inputs
- 无参数（默认）：检查所有 `running` 实验，输出状态表
- `--pipeline <slug>`（可选）：只检查属于指定 pipeline 的实验，额外输出 pipeline 整体进度
- `--collect-ready`（可选）：对所有"session 已消失"的实验自动调用 `/exp-run --collect` 收集结果When your agent uses it
为已有 AutoSci 实验运行可选的 Hiera 风格迭代候选搜索，同时保持 wiki 知识库和默认实验 workflow 不变
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
4,448 tokensWhen the skill is activated
Reference documents
7,299 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 作用和启用边界
- 状态模型和命令职责
- 用户交互规则
- 各阶段规则
- Contract 和命令不变量
- 本地和远程执行
- 失败、幂等和安全
- 每次动作的固定报告格式
Files
README.mddoc19,199 bytesSKILL.mdcore18,381 bytesSKILL.mdcore18,381 bytesSKILL.mdcore18,381 bytesSKILL.mdcore18,381 bytesSKILL.mdcore18,381 bytesSKILL.mdcore18,381 bytesreferences/interface.mddoc8,367 bytes
Read SKILL.md
# /hiera-experiment
## 作用和启用边界
仅当用户明确选择已有 AutoSci 实验的 Hiera 可选路径时使用本 skill。Hiera 是隔离的搜索旁路：
- 只读读取关联的 wiki 实验/design 和 runtime contract。
- 将全部搜索状态放在 runs/hiera/<experiment>/<run-id>/ 下。
- 搜索不可变 candidate 快照，并把证据写入旁路 ledger。
- 不创建 wiki entity，不修改 wiki schema 或实验状态，不重写 wiki/log.md，也不把搜索结果写回 wiki。
- 不替代 /exp-design、/exp-run、/exp-eval 或 /research。要形成确认性结论，必须回到正常且带用户门控的 workflow。
创建或改变 run 前必须阅读：
When your agent uses it
多阶段研究 idea 生成管道：景观扫描 → 双模型脑暴 → 筛选与验证 → 写入 wiki → 预实验
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
7,590 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytesSKILL.mdcore26,916 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /ideate
> 基于 wiki 知识库和外部搜索，通过 5 阶段管道生成高质量研究 idea。
> Phase 1 扫描研究景观（wiki + WebSearch + S2），Phase 2 双模型脑暴（Claude + Review LLM 独立生成），
> Phase 3 初步筛选 + 深度验证（可行性、novelty、review），Phase 4 将 ideas 写入 wiki（包括被淘汰的 ideas，记录原因作为 anti-repetition 记忆），
> Phase 5 对幸存 ideas 进行预实验（idea 页面已存在）并更新结果。
## Inputs
- `direction`（可选）：研究方向、关键词或具体问题描述。若不指定，则从 open_questions.md 自动选择最有价值的方向。
- `--max-ideas N`（可选，默认 3）：最终写入 wiki 的 idea 数量上限
- `--skip-validation`：跳过 Phase 3 步骤 2 深度验证（跳过 /novelty 和 /review，快速模式仅做初步筛选）
- `--skip-pilot`：跳过 Phase 5 预实验（快速模式，仅做 Phase 1-4）
- `--auto`：全自动模式，不暂停等待用户确认（用于 /research 调用）When your agent uses it
把一篇论文 ingest 进 wiki —— 建立 papers + concepts + methods + people 页面，并完成所有双向交叉引用与 graph edge。当用户说 "ingest"、"加入这篇论文"、丢 `.pdf` / `.tex` / arXiv URL 或要求把论文折叠进知识库时触发。
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
5,861 tokensWhen the skill is activated
Reference documents
6,634 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/discover.py../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/init_discovery.py../../../../tools/prepare_paper_source.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py
Files
SKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesSKILL.mdcore20,816 bytesreferences/cross-references.mddoc6,430 bytesreferences/dedup-policy.mddoc5,515 bytesreferences/error-handling.mddoc3,601 bytesreferences/init-mode.mddoc4,966 bytesreferences/pdf-preprocessing.mddoc3,747 bytes../../../../tools/discover.pyruns48,434 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/init_discovery.pyruns66,555 bytes../../../../tools/prepare_paper_source.pyruns27,298 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/serve.pyruns43,512 bytes../../../../tools/visualize.pyruns25,232 bytes
Read SKILL.md
# /ingest
把一篇论文转化成一组正确链接的 wiki 页面。`/ingest` 的职责是写出 well-shaped 的实体与正确的双向链接；语义层面的审计（反向链接对称性、dangling node、字段取值合规）留给 `/check`。
按需打开下列本地参考文件：
- `references/pdf-preprocessing.md` —— 直接 PDF 输入时的 arXiv-ID 恢复、tex 抓取、prepare-paper 交接流程
- `references/dedup-policy.md` —— concept / method 的合并与新建决策规则，以及 `/ingest` 形状检查与 `/check` 语义审计的边界
- `references/cross-references.md` —— 正向/反向链接矩阵与 paper-to-paper edge 类型选择
- `references/init-mode.md` —— `/init` 的 manifest 交接与并行安全约束
- `references/error-handling.md` —— 来源解析、API 与 slug 冲突的 fallback
写 wiki 页面 frontmatter 字段去 `runtime/schema/entities.yaml`,正文章节顺序去 `runtime/templates/{kind}.md.tmpl`;`index.md`、`log.md`、`graph/` 形状去 `runtime/schema/conventions.yaml` 与 `runtime/schema/edges.yaml`。
When your agent uses it
基于用户素材与可选外部发现搭建 ΩmegaWiki，并用并行 `/ingest` 完成最终论文集的消化
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
4,968 tokensWhen the skill is activated
Reference documents
2,504 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/backfill_citations.py../../../../tools/init_discovery.py../../../../tools/lint.py../../../../tools/prepare_paper_source.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py
Files
SKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesSKILL.mdcore18,040 bytesreferences/parallel-ingest.mddoc3,314 bytesreferences/planner-policy.mddoc1,949 bytesreferences/prepare-and-discovery.mddoc4,174 bytes../../../../tools/backfill_citations.pyruns5,569 bytes../../../../tools/init_discovery.pyruns66,555 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/prepare_paper_source.pyruns27,298 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/serve.pyruns43,512 bytes../../../../tools/visualize.pyruns25,232 bytes
Read SKILL.md
# /init
> 从 `raw/` 搭建 wiki：先做确定性 prepare，再跑 planner-guided discovery；`raw/notes/` 与 `raw/web/` 可种下 provisional scaffold；论文消化仍走并行 `/ingest` fan-out / fan-in。
按需打开这些本地参考文件：
- `references/prepare-and-discovery.md` — prepare 流程、最终选择、fetch 与 source-manifest 规则
- `references/planner-policy.md` — planner 行为与 LLM 裁剪期望
- `references/parallel-ingest.md` — worktree 隔离、子代理 prompt 合同、merge 与清理
## Inputs
- `topic`（可选）：研究方向关键词；当 `raw/` 已定义 seed set 时可省略
- `--no-introduction`（可选）：禁用外部发现；仅在用户明确要求时使用When your agent uses it
多源 novelty 验证：WebSearch + Semantic Scholar + wiki + Review LLM cross-verify，输出 novelty 评分与建议。可选 --write，把分数写回 idea 页面。
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
2,919 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_deepxiv.py../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore10,335 bytesSKILL.mdcore10,335 bytesSKILL.mdcore10,335 bytesSKILL.mdcore10,335 bytes../../../../tools/fetch_deepxiv.pyruns11,695 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /novelty
> 对一个研究想法或方法进行多源 novelty 验证。搜索 WebSearch、Semantic Scholar、
> wiki 内已有工作和 arXiv 最新预印本，然后由 Review LLM 交叉验证，输出 novelty 评分（1-5）、
> 最相似已有工作、差异化要点和下一步建议。
> 可独立使用，也被 /ideate Phase 4 调用。
## Inputs
- `target`：以下之一：
- idea 的自由文本描述（一段话或几句话）
- wiki 中 ideas/ 页面的 slug（如 `sparse-lora-for-edge-devices`）
- 论文标题或 arXiv URL（检查该论文方法的 novelty）
- `--quick`：快速模式，跳过 Review LLM cross-verify（Step 3），仅做搜索When your agent uses it
LaTeX 编译 → PDF：latexmk 编译 + 自动修复 + 页数/匿名/字体/[UNCONFIRMED] 检查 + 提交清单
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
2,617 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytesSKILL.mdcore8,996 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-compile
> 编译 LaTeX 论文为 PDF，自动修复常见错误，验证提交要求。
> 输入 paper/ 目录（由 /paper-draft 生成），执行 latexmk 编译，
> 解析错误并尝试自动修复（缺失包、引用未定义、figure 路径），
> 验证页数限制、匿名合规、字体嵌入、[UNCONFIRMED] 标记清除。
> 生成提交清单。
## Inputs
- `paper_dir`（可选，默认 `paper/`）：LaTeX 项目目录，包含 `main.tex`
- `--fix`（可选）：启用自动修复模式（自动安装缺失包、修正路径）
- `--checklist`（可选）：生成详细提交清单（不编译，只检查）
When your agent uses it
从 PAPER_PLAN 起草 LaTeX 论文：逐 section 从 wiki 取材撰写 + 生成 figures/tables + BibTeX 验证 + de-AI polish
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
3,766 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore13,525 bytesSKILL.mdcore13,525 bytesSKILL.mdcore13,525 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-draft
> 从 /paper-plan 生成的 PAPER_PLAN.md 起草完整 LaTeX 论文。
> 逐 section 撰写：每个 section 从 wiki 读取 ideas/methods/experiments/papers/concepts 取材，
> 生成 LaTeX + figures + tables。BibTeX 从 DBLP/CrossRef 获取（遵循 citation-verification），
> 完成后执行 de-AI polish（遵循 academic-writing）。
> 可选逐 section Review LLM review。输出可编译的 paper/ 目录。
## Inputs
- `plan`：PAPER_PLAN.md 的路径（如 `wiki/outputs/paper-plan-sparse-lora-2026-04-08.md`）
- `--review`（可选）：启用逐 section Review LLM review
- `--sections`（可选）：只写指定 section（如 `--sections 3,4` 只写 Method + Experiments），用于增量撰写
When your agent uses it
从 idea graph 编译论文大纲：编译 evidence map → 叙事结构 → 章节计划 + figure plan + citation plan，Review LLM review 必选
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
4,414 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore16,026 bytesSKILL.mdcore16,026 bytesSKILL.mdcore16,026 bytesSKILL.mdcore16,026 bytesSKILL.mdcore16,026 bytesSKILL.mdcore16,026 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /paper-plan
> 从 wiki 的 idea graph 编译论文大纲。
> 输入 target ideas（status: validated 或 in_progress 且具备 succeeded 实验），指定目标会议/期刊，
> 从 wiki 编译 evidence map → 确定叙事结构 → 生成章节大纲 + figure plan + citation plan。
> Review LLM review 是必选步骤（作为 area chair 审查大纲说服力）。
> 输出 PAPER_PLAN.md 到 wiki/outputs/。
>
> 关键差异：大纲由 idea graph 驱动 — 每个 section 存在是因为它支撑某个 idea（或其证据/方法），
> 而非因为论文惯例要求有该 section。
## Inputs
- `ideas`：目标 idea 的 slug 列表（空格分隔）When your agent uses it
从已撰写的论文生成学术海报 —— 提炼章节为单页 HTML 海报,包含配图和段落间过渡
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
13,229 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/poster.py../../../../tools/rasterize_latex.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py../../../../tools/wiki2dag.py
Files
SKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytesSKILL.mdcore45,059 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/poster.pyruns49,003 bytes../../../../tools/rasterize_latex.pyruns10,025 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes../../../../tools/wiki2dag.pyruns44,105 bytes
Read SKILL.md
# /poster
> 从已撰写的论文生成学术 HTML 海报。读取 `paper/main.tex`、章节文件与图片;
> 构建 PaperX 兼容的 `dag.json` 中间格式;将每个章节提炼为 2–5 句话摘要;
> 选取代表性配图;渲染为自包含的 HTML 海报(三栏自适应布局)。
## Inputs
### 常用
- `paper_dir`(可选,默认 `paper/`):LaTeX 项目目录,需包含 `main.tex` 和 `sections/`
- `--review`(可选):调用 Review LLM 对生成的海报内容进行跨模型评审
- `--anonymous`(可选):强制将作者写为 "Anonymous",忽略 `\author{}`、`paper/.author_display.txt` 缓存以及 `--authors` flag
- `--no-figures`(可选):所有章节渲染为纯文本(适合文本密集型海报,或配图尚未准备好时)When your agent uses it
用领域基础知识填充 wiki/foundations/，避免后续 /ingest 为教科书材料创建重复的 concept 页面
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
1,721 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
- Trigger
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/fetch_wikipedia.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore6,099 bytesSKILL.mdcore6,099 bytesSKILL.mdcore6,099 bytesfoundations-catalog.yamlasset3,448 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/fetch_wikipedia.pyruns4,556 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /prefill
> 将领域基础知识（奠基性方法、common practice、标准架构）作为**终端**页面沉淀到 `wiki/foundations/`。
> Foundations 设计上**单向**：其他页面可以链接到 foundation，foundation 不写反向链接。
## Trigger
手动：`/prefill [domain]` 或 `/prefill --add "概念名"`。
## Inputs
- `domain`（位置参数，可选）：研究领域 — `general` / `NLP` / `CV` / `ML Systems` / `Robotics` 之一。未指定时从 `wiki/topics/` 标签推断；若 topics 为空则提示用户。
- `--add "<概念>"`：跳过 catalog，直接为单个概念建立 foundation。
When your agent uses it
解析审稿意见 → 原子化 concerns (Rvx-Cy) → 映射到 wiki ideas/methods → 检查 evidence → Review LLM stress-test → 生成 rebuttal
What it loads into context
Frontmatter
81 tokensAlways available to the agent
SKILL.md
4,303 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore15,480 bytesSKILL.mdcore15,480 bytesSKILL.mdcore15,480 bytesSKILL.mdcore15,480 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /rebuttal
> 解析审稿意见，将每条 concern 原子化（Rvx-Cy 编号）并映射到 wiki idea 或 method，
> 检查 evidence 是否充分（追溯到 wiki experiments），
> 用 Review LLM 模拟审稿人追问（stress-test，评分 1-5），生成正式版（纯文本）和富文本版 rebuttal。
> 安全检查确保 no fabrication, no overpromise, full coverage。
## Inputs
- `review`：审稿意见来源，以下之一：
- 文件路径（如 `raw/reviews/reviewer1.txt`、`raw/reviews/meta-review.md`）
- 多个文件路径（逗号分隔：`raw/reviews/R1.txt,raw/reviews/R2.txt,raw/reviews/R3.txt`）
- 直接粘贴的审稿文本
- `--paper-slug`（可选）：关联论文在 wiki/outputs/ 中的 slug，用于定位 PAPER_PLANWhen your agent uses it
通用多轮迭代改进：对任意研究制品反复调用 /review → 解析反馈 → 修复 → 更新 wiki，直到达标
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
2,666 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,512 bytesSKILL.mdcore9,512 bytesSKILL.mdcore9,512 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /refine
> 通用多轮迭代改进循环，适用于任何研究制品（idea、proposal、experiment plan、paper draft）。
> 每轮调用 /review 获取结构化反馈 → 解析 actionable items → Claude 修复制品 → 更新 wiki 实体 →
> 重新 /review，直到评分达到目标分数或达到最大轮次。
> 输出改进历史和最终 review 评分。
## Inputs
- `artifact`：要改进的制品，以下之一：
- wiki 页面的 slug（从 ideas/experiments/methods/outputs/ 中查找）
- 文件路径（如 `wiki/outputs/paper-draft-v1.md`）
- `--max-rounds N`（可选，默认 4）：最大迭代轮次
- `--target-score N`（可选，默认 8）：目标 review 评分（1-10），达到后停止When your agent uses it
端到端研究编排器：idea 发现 → 实验设计 → 执行 → 判决 → 论文撰写，带人工门控和状态恢复
What it loads into context
Frontmatter
106 tokensAlways available to the agent
SKILL.md
6,110 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytesSKILL.mdcore21,920 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /research
> 端到端研究编排器，将所有 skill 组合为完整的研究流程。
> Stage 0 (Bootstrap) + 5 个 Stage + 2 个 Human Gate，覆盖从空 wiki 到论文提交的全流程。
> **零摩擦入口**：wiki 处于冷启动时，`/research` 在 Stage 0 暂停，需显式运行 `/init` / `$init` 进行 Bootstrap 后再继续。
> 每个 Gate 和 Stage 保存进度到 `wiki/outputs/pipeline-progress.md`，支持跨 session 恢复。
>
> **Stage 3 为非阻塞设计**：实验部署后立即返回（`--auto` 模式自动设置 CronCreate 每 30 分钟监控），
> 实验全部完成后自动进入 Stage 4。可随时用 `/exp-status` 查看进度。
>
> `--auto` 模式跳过人工确认（自动选 top-1 idea），`--skip-paper` 只做研究不写论文。
## Inputs
When your agent uses it
按 scope 重置 wiki 到干净 scaffold（wiki / raw / log / checkpoints / all）。适用于开发迭代或 setup 失败后的无痛重启。
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
1,193 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
- Trigger
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/reset_wiki.py
Files
SKILL.mdcore4,010 bytesSKILL.mdcore4,010 bytesSKILL.mdcore4,010 bytesSKILL.mdcore4,010 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/reset_wiki.pyruns6,410 bytes
Read SKILL.md
# /reset
> 按 scope 重置 wiki 到干净 scaffold。设计目的是开发迭代和 setup 失败恢复 — 不是日常操作。
## Trigger
手动：`/reset --scope wiki` / `--scope raw` / `--scope log` / `--scope checkpoints` / `--scope all`。可用逗号组合多个 scope：`--scope wiki,log`。
## Inputs
- `--scope`（必填）：取值
- `wiki` — 删除 `wiki/<entity>/` 与 `wiki/outputs/` 下所有 `*.md`，同时删除 `wiki/index.md`、`wiki/log.md` 和 `wiki/graph/` 下的文件。保留 `.gitkeep` 和 `wiki/CLAUDE.md`。
- `raw` — 删除 `raw/papers/`、`raw/discovered/`、`raw/tmp/`、`raw/notes/`、`raw/web/` 下所有条目（保留 `.gitkeep`）。
- `log` — 重置 `wiki/log.md` 为空模板。When your agent uses it
通用跨模型审查：Review LLM 对任意研究制品进行独立评审，输出结构化评分、wiki 实体映射与改进建议
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
3,336 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Files
SKILL.mdcore12,386 bytesSKILL.mdcore12,386 bytes
Read SKILL.md
# /review
> 对任意研究制品（idea、proposal、experiment plan、paper draft、method）进行跨模型审查。
> 使用 Review LLM 作为独立审稿人，输出结构化评分、可操作的改进建议，以及与 wiki 实体的映射
> （哪些 ideas/methods 需要加强，哪些 gaps 被发现）。
> 支持三种难度级别（standard / hard / adversarial）和四种审查焦点。
> 可独立使用，也被 /ideate、/refine、/exp-design 调用。
## Inputs
- `artifact`：要审查的制品，以下之一：
- wiki 页面的 slug（如 `sparse-lora-for-edge-devices`，从 ideas/experiments/methods/ 中查找）
- 文件路径（如 `wiki/outputs/paper-draft-v1.md`）
- 自由文本（直接粘贴的 proposal 或 idea 描述）When your agent uses it
交互式 API key 配置引导 — 检测当前 .env 状态，逐步引导配置 Semantic Scholar、DeepXiv 和 Review LLM
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
2,480 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/_env.py
Files
SKILL.mdcore8,832 bytesSKILL.mdcore8,832 bytesSKILL.mdcore8,832 bytesSKILL.mdcore8,832 bytesSKILL.mdcore8,832 bytesSKILL.mdcore8,832 bytes../../../../tools/_env.pyruns1,482 bytes
Read SKILL.md
# /setup
> 引导你完成 ΩmegaWiki 的可选 API key 配置。
> 读取当前 `.env`，展示已配置和未配置的内容，并帮助你逐步设置每个 key，
> 包括清晰解释每个 key 的作用和获取方式。
> 可随时重新运行，只更新你选择配置的 key。
## Inputs
- 不需要任何参数
- 读取：`.env`（当前配置状态）
- 读取：`config/setup-guide.md`（每个 key 的参考说明）
## OutputsWhen your agent uses it
从 wiki 知识生成论文 Related Work 章节：主题分组 → 叙事结构 → LaTeX 输出，遵循 citation-verification 和 academic-writing
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
2,626 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py
Files
SKILL.mdcore9,325 bytesSKILL.mdcore9,325 bytesSKILL.mdcore9,325 bytesSKILL.mdcore9,325 bytesSKILL.mdcore9,325 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes
Read SKILL.md
# /survey
> 基于 wiki 已有知识，生成可直接用于论文的 Related Work 章节。
> 从 wiki/papers/、concepts/、topics/ 取材，按研究方向分组（非逐篇罗列），
> 每组以「与本文的区别」收尾。引用遵循 citation-verification.md，
> 写作遵循 academic-writing.md 的 Related Work 规则。
> 支持 LaTeX 和 Markdown 两种输出格式。
## Inputs
- `query`：以下之一：
- 研究问题描述（自由文本，如 "parameter-efficient fine-tuning for LLMs"）
- idea slugs 列表（从 wiki/ideas/ 中，用于围绕特定 ideas 组织相关工作）
- PAPER_PLAN.md 路径（从中提取 Related Work section 定义）When your agent uses it
生成并更新可视化产物 —— Obsidian 图谱配置与 Canvas 知识地图。交互式网页图谱视图位于 SPA 的 app/modules/graph.js（由 tools/serve.py 提供服务）。
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
3,212 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
- Inputs
- Outputs
- Wiki Interaction
- Workflow
- Color Palette
- Constraints
- Error Handling
- Dependencies
Scripts executed separately
../../../../tools/fetch_s2.py../../../../tools/lint.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/research_wiki.py../../../../tools/serve.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py../../../../tools/visualize.py
Files
SKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytesSKILL.mdcore10,922 bytes../../../../tools/fetch_s2.pyruns9,017 bytes../../../../tools/lint.pyruns47,617 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/research_wiki.pyruns107,828 bytes../../../../tools/serve.pyruns43,512 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes../../../../tools/visualize.pyruns25,232 bytes
Read SKILL.md
# /visualize
> 为 OmegaWiki 知识图谱生成可视化产物。
> 产出 Obsidian 图谱配置（按实体类型分色组）以及带类型标签边的精选 Canvas 视图。
> 交互式网页探索请使用 SPA 的 Graph 视图（先跑 `tools/serve.py`，然后访问 `#/graph`）。
## Inputs
- `--obsidian`（可选）：生成或更新 `.obsidian/graph.json`，按实体类型分色组
- `--canvas`（可选）：基于图谱数据生成 Obsidian Canvas（`.canvas`），边带类型标签
- `--focus <node_id>`（可选）：把 Canvas 聚焦到某个具体节点（例如 `methods/my-method`）
- `--depth N`（可选）：聚焦 Canvas 的 BFS 深度（默认：2）
- `--types <list>`（可选）：把节点过滤到这些 page type，逗号分隔（例如 `papers,concepts`）
- `--edge-types <list>`（可选）：把边过滤到这些语义类型，逗号分隔（例如 `builds_on,challenges`）Skills included
- edit
- edit
Repository facts
- License
- MIT
- Created
- Apr 9, 2026
- Last pushed
- Oct 30, 2026
- Forks
- 215
- Open issues
- 4
- 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 708 notes
i18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/ask/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/research_wiki.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/check/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/check/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/check/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedi18n/en/skills/check/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/lint.py:1Analysis incomplete: Referenced executable target unavailable; not analyzedtools/lint.py:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- 2 dangerous shell commandsin 2 files: paper-compile/SKILL.md:214 paper-compile/SKILL.md:214
- 436 network referencesin 19 files: tools/fetch_s2.py:25 tools/init_discovery.py:286 tools/discover.py:195 and 16 more
- 4 obfuscation signalsin 1 file: tools/poster.py:87
- No instruction overrides
- 482 executable scriptsin 18 files: tools/research_wiki.py:1 tools/fetch_s2.py:1 tools/poster.py:1 and 15 more
- 305 references to secretsin 18 files: tools/fetch_s2.py:21 tools/serve.py:137 tools/_env.py:3 and 15 more
- No requests to vote in Hot
Show all 1,229 signals by file
i18n/en/skills/daily-arxiv/SKILL.md
i18n/en/skills/daily-arxiv/references/automation-scaffold.md
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i18n/en/skills/discover/SKILL.md
- Network accessline 115
To ingest a candidate: /ingest https://arxiv.org/abs/<arxiv-id>
i18n/en/skills/ingest/SKILL.md
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- `source`: one of — arXiv URL (e.g. `https://arxiv.org/abs/2106.09685`), local `.tex`, local `.pdf`, or a `canonical_ingest_path` handed off by `/init` via `.checkpoints/init-sources.json`(see `references/init-mode.md`)
i18n/en/skills/init/references/planner-policy.md
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i18n/en/skills/paper-compile/SKILL.md
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- **latexmk not installed**: error; provide installation command (`sudo apt install texlive-full` or `brew install --cask mactex`)
i18n/en/skills/paper-plan/SKILL.md
i18n/en/skills/setup/SKILL.md
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**Guide to get it**: "Go to https://www.semanticscholar.org/product/api and click 'Get API Key'. It's free." - Access to secretsline 107
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} try: resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) - Network accessline 143
try: resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) resp.raise_for_status() - Network accessline 144
resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) - Network accessline 185
**Ask for**: 1. `LLM_BASE_URL` — e.g. `https://api.deepseek.com/v1` - Network accessline 186
1. `LLM_BASE_URL` — e.g. `https://api.deepseek.com/v1` - Access to secretsline 187
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**Validate format**: Base URL should start with `http://` or `https://` and end with `/v1` - Access to secretsline 219
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i18n/en/skills/survey/SKILL.md
i18n/en/skills/visualize/SKILL.md
i18n/zh/skills/daily-arxiv/SKILL.md
i18n/zh/skills/daily-arxiv/references/automation-scaffold.md
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i18n/zh/skills/discover/SKILL.md
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如需 ingest：/ingest https://arxiv.org/abs/<arxiv-id>
i18n/zh/skills/ingest/SKILL.md
i18n/zh/skills/init/SKILL.md
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i18n/zh/skills/init/references/planner-policy.md
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i18n/zh/skills/paper-compile/SKILL.md
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- **latexmk 未安装**：报错，提供安装命令（`sudo apt install texlive-full` 或 `brew install --cask mactex`）
i18n/zh/skills/setup/SKILL.md
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**引导获取**："访问 https://www.semanticscholar.org/product/api， - Access to secretsline 108
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} try: resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) - Network accessline 142
try: resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) resp.raise_for_status() - Network accessline 143
resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30) - Network accessline 182
**依次询问**： 1. `LLM_BASE_URL` — 例如 `https://api.deepseek.com/v1` - Network accessline 183
1. `LLM_BASE_URL` — 例如 `https://api.deepseek.com/v1` - Access to secretsline 184
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**格式校验**：Base URL 应以 `http://` 或 `https://` 开头，通常以 `/v1` 结尾。 - Access to secretsline 216
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i18n/zh/skills/visualize/SKILL.md
tools/_env.py
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tools/backfill_citations.py
tools/daily_arxiv.py
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if url: return url return f"https://arxiv.org/abs/{arxiv_id}" if arxiv_id else "" - Network accessline 403
if url: return url return f"https://arxiv.org/abs/{arxiv_id}" if arxiv_id else "" - Network accessline 405
return f"https://arxiv.org/abs/{arxiv_id}" if arxiv_id else "" - Network accessline 405
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} try: response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1271
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try: response = requests.post(url, headers=headers, json=body, timeout=timeout) if response.status_code >= 400 and body.get("response_format"): - Network accessline 1272
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response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1273
response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1274
if response.status_code >= 400 and body.get("response_format"): body.pop("response_format", None) response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1274
if response.status_code >= 400 and body.get("response_format"): body.pop("response_format", None) response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1275
body.pop("response_format", None) response = requests.post(url, headers=headers, json=body, timeout=timeout) response.raise_for_status() - Network accessline 1275
body.pop("response_format", None) response = requests.post(url, headers=headers, json=body, timeout=timeout) response.raise_for_status() - Network accessline 1276
response = requests.post(url, headers=headers, json=body, timeout=timeout) - Network accessline 1276
response = requests.post(url, headers=headers, json=body, timeout=timeout)
tools/discover.py
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} _PAPER_COPILOT_BASE_URL = ( "https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 195
} _PAPER_COPILOT_BASE_URL = ( "https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 195
} _PAPER_COPILOT_BASE_URL = ( "https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 195
} _PAPER_COPILOT_BASE_URL = ( "https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 196
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"https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 197
"https://raw.githubusercontent.com/papercopilot/paperlists/main" - Network accessline 215
for attempt in range(2): try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 215
for attempt in range(2): try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 215
for attempt in range(2): try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 215
for attempt in range(2): try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 216
try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 data = json.loads(resp.read().decode("utf-8")) - Network accessline 216
try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 data = json.loads(resp.read().decode("utf-8")) - Network accessline 216
try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 data = json.loads(resp.read().decode("utf-8")) - Network accessline 216
try: with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 data = json.loads(resp.read().decode("utf-8")) - Network accessline 217
with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 217
with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 217
with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 217
with urllib.request.urlopen(url, timeout=30) as resp: # noqa: S310 - Network accessline 248
return "" if text.lower().startswith("www."): text = f"https://{text}" - Network accessline 248
return "" if text.lower().startswith("www."): text = f"https://{text}" - Network accessline 248
return "" if text.lower().startswith("www."): text = f"https://{text}" - Network accessline 248
return "" if text.lower().startswith("www."): text = f"https://{text}" - Network accessline 249
if text.lower().startswith("www."): text = f"https://{text}" parsed = urllib.parse.urlparse(text) - Network accessline 249
if text.lower().startswith("www."): text = f"https://{text}" parsed = urllib.parse.urlparse(text) - Network accessline 249
if text.lower().startswith("www."): text = f"https://{text}" parsed = urllib.parse.urlparse(text) - Network accessline 249
if text.lower().startswith("www."): text = f"https://{text}" parsed = urllib.parse.urlparse(text) - Network accessline 250
text = f"https://{text}" parsed = urllib.parse.urlparse(text) if parsed.scheme not in {"http", "https"} or not parsed.netloc: - Network accessline 250
text = f"https://{text}" parsed = urllib.parse.urlparse(text) if parsed.scheme not in {"http", "https"} or not parsed.netloc: - Network accessline 250
text = f"https://{text}" parsed = urllib.parse.urlparse(text) if parsed.scheme not in {"http", "https"} or not parsed.netloc: - Network accessline 250
text = f"https://{text}" parsed = urllib.parse.urlparse(text) if parsed.scheme not in {"http", "https"} or not parsed.netloc:
tools/fetch_deepxiv.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 24
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted]
tools/fetch_s2.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Access to secretsline 21
[Credential-related source omitted] - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 25
BASE_URL = "https://api.semanticscholar.org/graph/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Network accessline 26
RECS_BASE_URL = "https://api.semanticscholar.org/recommendations/v1" - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 63
time.sleep(RATE_LIMIT_DELAY) for attempt in range(MAX_RETRIES): resp = requests.request( - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 64
for attempt in range(MAX_RETRIES): resp = requests.request( method, - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request( - Network accessline 65
resp = requests.request(
tools/fetch_wikipedia.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 28
API = "https://en.wikipedia.org/w/api.php" - Network accessline 28
API = "https://en.wikipedia.org/w/api.php" - Network accessline 29
REST_SUMMARY = "https://en.wikipedia.org/api/rest_v1/page/summary/" - Network accessline 29
REST_SUMMARY = "https://en.wikipedia.org/api/rest_v1/page/summary/" - Network accessline 30
USER_AGENT = "OmegaWiki-prefill/0.1 (https://github.com/skyllwt/OmegaWiki)" - Network accessline 30
USER_AGENT = "OmegaWiki-prefill/0.1 (https://github.com/skyllwt/OmegaWiki)" - Network accessline 33
def _get(url: str) -> dict: req = urllib.request.Request(url, headers={"User-Agent": USER_AGENT}) - Network accessline 33
def _get(url: str) -> dict: req = urllib.request.Request(url, headers={"User-Agent": USER_AGENT}) - Network accessline 34
req = urllib.request.Request(url, headers={"User-Agent": USER_AGENT}) - Network accessline 34
req = urllib.request.Request(url, headers={"User-Agent": USER_AGENT}) - Network accessline 35
try: with urllib.request.urlopen(req, timeout=15) as resp: return json.loads(resp.read().decode("utf-8")) - Network accessline 35
try: with urllib.request.urlopen(req, timeout=15) as resp: return json.loads(resp.read().decode("utf-8")) - Network accessline 36
with urllib.request.urlopen(req, timeout=15) as resp: - Network accessline 36
with urllib.request.urlopen(req, timeout=15) as resp:
tools/init_discovery.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 286
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 287
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 288
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1381
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Access to secretsline 1385
[Credential-related source omitted] - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1482
headers = {"User-Agent": "OmegaWiki-init-discovery/1.0"} try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1483
try: pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) pdf_resp.raise_for_status() - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1484
pdf_resp = requests.get(f"https://arxiv.org/pdf/{arxiv_id}", timeout=30, headers=headers) - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1488
"application/pdf" not in content_type and not pdf_resp.content.startswith(b"%PDF") ): raise requests.RequestException("empty pdf") - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1489
): raise requests.RequestException("empty pdf") _write_bytes(dest_pdf, pdf_resp.content) - Network accessline 1490
raise requests.RequestException("empty pdf") - Network accessline 1490
raise requests.RequestException("empty pdf") - Network accessline 1490
raise requests.RequestException("empty pdf") - Network accessline 1490
raise requests.RequestException("empty pdf") - Network accessline 1490
raise requests.RequestException("empty pdf") - Network accessline 1490
raise requests.RequestException("empty pdf")
tools/lint.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3
tools/poster.py
- Executable scriptline 1
Executable file - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Possible obfuscationline 87
outline_raw.replace("<U+FEFF>", "") - Possible obfuscationline 87
outline_raw.replace("<U+FEFF>", "") - Possible obfuscationline 96
html = html.replace("<U+FEFF>", "").replace("\r\n", "\n").replace("\r", "\n") - Possible obfuscationline 96
html = html.replace("<U+FEFF>", "").replace("\r\n", "\n").replace("\r", "\n") - Network accessline 588
" apt install microsoft-edge-stable\n" " apt install firefox (fallback, 1x only)\n" " Windows: https://www.google.com/chrome/ (recommended)\n" - Network accessline 588
" apt install microsoft-edge-stable\n" " apt install firefox (fallback, 1x only)\n" " Windows: https://www.google.com/chrome/ (recommended)\n" - Network accessline 589
" apt install firefox (fallback, 1x only)\n" " Windows: https://www.google.com/chrome/ (recommended)\n" " Microsoft Edge is preinstalled on Windows 10+\n" - Network accessline 589
" apt install firefox (fallback, 1x only)\n" " Windows: https://www.google.com/chrome/ (recommended)\n" " Microsoft Edge is preinstalled on Windows 10+\n" - Network accessline 590
" Windows: https://www.google.com/chrome/ (recommended)\n" - Network accessline 590
" Windows: https://www.google.com/chrome/ (recommended)\n" - Network accessline 591
" Microsoft Edge is preinstalled on Windows 10+\n" " https://www.mozilla.org/firefox/ (fallback, 1x only)" ) - Network accessline 591
" Microsoft Edge is preinstalled on Windows 10+\n" " https://www.mozilla.org/firefox/ (fallback, 1x only)" ) - Network accessline 592
" https://www.mozilla.org/firefox/ (fallback, 1x only)" - Network accessline 592
" https://www.mozilla.org/firefox/ (fallback, 1x only)"
tools/prepare_paper_source.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 193
headers = {"User-Agent": "OmegaWiki-prepare-paper-source/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 193
headers = {"User-Agent": "OmegaWiki-prepare-paper-source/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 193
headers = {"User-Agent": "OmegaWiki-prepare-paper-source/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 193
headers = {"User-Agent": "OmegaWiki-prepare-paper-source/1.0"} try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 194
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 194
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 194
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 194
try: src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) if src_resp.ok and src_resp.content: - Network accessline 195
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 195
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 195
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers) - Network accessline 195
src_resp = requests.get(f"https://arxiv.org/e-print/{arxiv_id}", timeout=30, headers=headers)
tools/rasterize_latex.py
tools/remote.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable
tools/research_wiki.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
Executable file; content unavailable - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
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tools/reset_wiki.py
tools/serve.py
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#!/usr/bin/env python3 - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 68
Smoke test: curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 69
curl http://127.0.0.1:8765/api/health -> {"status":"ok","phase":4} - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Network accessline 70
curl http://127.0.0.1:8765/api/stats -> entity counts (must match - Access to secretsline 137
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[Credential-related source omitted] - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1055
server.daemon_threads = True _ensure_watcher() base = f"http://{args.host}:{args.port}" - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1056
_ensure_watcher() base = f"http://{args.host}:{args.port}" print(f"OmegaWiki frontend serving at {base}") - Network accessline 1057
base = f"http://{args.host}:{args.port}" - Network accessline 1057
base = f"http://{args.host}:{args.port}" - Network accessline 1057
base = f"http://{args.host}:{args.port}" - Network accessline 1057
base = f"http://{args.host}:{args.port}" - Network accessline 1057
base = f"http://{args.host}:{args.port}" - Network accessline 1057
base = f"http://{args.host}:{args.port}"
tools/visualize.py
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1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 679
1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 679
1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 679
1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 679
1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 679
1. python3 tools/serve.py (starts the SPA on http://127.0.0.1:8765) - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph - Network accessline 680
2. Open http://127.0.0.1:8765/#/graph
tools/wiki2dag.py
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How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Declared and executed: 1 fact
- Contacts raw.githubusercontent.com, which SKILL.md, the README and the plugin manifest do not mentiontools/discover.py:197High confidence
Signal confidence: 499 facts
- Access to secrets in prose of the SKILL.md: a variable, placeholder or call, not a stored valuedaily-arxiv/SKILL.md:18Low confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuedaily-arxiv/SKILL.md:44Low confidence
- Access to secrets in prose of the SKILL.mddaily-arxiv/SKILL.md:53Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:24Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:25Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:35Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:38Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:39Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:42Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valuedaily-arxiv/references/automation-scaffold.md:68Low confidence
- Network access in code of the SKILL.mddiscover/SKILL.md:115High confidence
- Network access in prose of the SKILL.mdingest/SKILL.md:22Low confidence
- Access to secrets in prose of documentationinit/references/planner-policy.md:14Low confidence
- Dangerous shell operation in prose of the SKILL.mdpaper-compile/SKILL.md:214Low confidence
- Network access in prose of the SKILL.mdpaper-plan/SKILL.md:389Low confidence
- Network access in prose of the SKILL.mdpaper-plan/SKILL.md:391Low confidence
- Access to secrets in the frontmatter of the SKILL.mdsetup/SKILL.md:2Low confidence
- Access to secrets in code of the SKILL.mdsetup/SKILL.md:51High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:53Low confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:58Low confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:76Low confidence
- Network access in prose of the SKILL.mdsetup/SKILL.md:101Low confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:107Low confidence
- Access to secrets in prose of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:110Low confidence
- Access to secrets in prose of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:111Low confidence
- Network access in code of the SKILL.mdsetup/SKILL.md:142High confidence
- Network access in code of the SKILL.mdsetup/SKILL.md:143High confidence
- Network access in code of the SKILL.mdsetup/SKILL.md:144High confidence
- Network access in prose of the SKILL.mdsetup/SKILL.md:185Low confidence
- Network access in prose of the SKILL.mdsetup/SKILL.md:186Low confidence
- Access to secrets in prose of the SKILL.mdsetup/SKILL.md:187Low confidence
- Network access in prose of the SKILL.mdsetup/SKILL.md:190Low confidence
- Access to secrets in code of the SKILL.mdsetup/SKILL.md:219High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuesetup/SKILL.md:221Low confidence
- Access to secrets in code of the SKILL.mdsetup/SKILL.md:257High confidence
- Network access in prose of the SKILL.mdsurvey/SKILL.md:206Low confidence
- Network access in prose of the SKILL.mdsurvey/SKILL.md:208Low confidence
- Network access in code of the SKILL.mdvisualize/SKILL.md:160High confidence
- Network access in code of the SKILL.mdvisualize/SKILL.md:182High confidence
- Access to secrets in code of the SKILL.md: a variable, placeholder or call, not a stored valuedaily-arxiv/SKILL.md:42Low confidence
- Access to secrets in prose of the SKILL.mddaily-arxiv/SKILL.md:51Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:21Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:22Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:32Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:34Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:35Low confidence
- Access to secrets in prose of documentationdaily-arxiv/references/automation-scaffold.md:38Low confidence
- Network access in code of the SKILL.mddiscover/SKILL.md:115High confidence
- Network access in prose of the SKILL.mdingest/SKILL.md:22Low confidence
- Access to secrets in code of the SKILL.mdingest/SKILL.md:77High confidence
and 449 more
Only the first 500 facts are listed.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Path .claude/skills/ask/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md i18n/en/skills/edit/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md i18n/en/skills/edit/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md i18n/en/skills/edit/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md i18n/en/skills/edit/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md i18n/en/skills/edit/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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