Agent skill · Workflow & Productivity

learn

Extract reusable knowledge from the current session into a persistent skill. Use when you discover something non-obvious, create a workaround, or develop a multi-step workflow that future sessions would benefit from.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codecan modify filesNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill learn --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Version: 1.0.0
Declared author: Claude Code Academic Workflow
Allowed tools: ReadWriteBashGlobGrep
Path: skills/12-pedrohcgs-claude-code-my-workflow/dot-claude/skills/learn/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

# /learn — Skill Extraction Workflow Extract non-obvious discoveries into reusable skills that persist across sessions. ## When to Use This Skill Invoke `/learn` when you encounter: - **Non-obvious debugging** — Investigation that took significant effort, not in docs - **Misleading errors** — Error message was wrong, found the real cause - **Workarounds** — Found a limitation with a creative solut

More from Auto-Empirical-Research-Skills
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About this skill
What does the learn skill do?

Extract reusable knowledge from the current session into a persistent skill. Use when you discover something non-obvious, create a workaround, or develop a multi-step workflow that future sessions would benefit from.

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill learn --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.

Keep going