Agent skill

workflows:compound

Document a recently solved research problem to compound methodological knowledge

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codecan modify filesNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill workflows-compound --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 13 KB
Bundled scripts: none
Allowed tools: ReadWriteEditGlob
Path: skills/11-James-Traina-compound-science/skills/workflows-compound/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# /compound **Pipeline mode:** This command operates fully autonomously. All decisions are made automatically. Coordinate multiple subagents working in parallel to document a recently solved research problem. Creates structured documentation in `docs/solutions/` with YAML frontmatter for searchability and future reference. ## Purpose Captures problem solutions while context is fresh. Uses parallel

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About this skill
What does the workflows:compound skill do?

Document a recently solved research problem to compound methodological knowledge

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill workflows-compound --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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