Agent skill

cross-disciplinary-ideation

Field connection mapping and systematic ideation for method transfer

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill cross-disciplinary-ideation --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 18 KB
Bundled scripts: none
Path: skills/26-Data-Wise-scholar/skills/research/cross-disciplinary-ideation/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

# Cross-Disciplinary Ideation **Systematic framework for discovering statistical innovations through cross-field connections** Use this skill when: brainstorming new methods, seeking novel approaches to statistical problems, looking for inspiration from other fields (physics, CS, biology, economics), or wanting to apply techniques from one domain to another. --- ## The Cross-Disciplinary Innovatio

More from Auto-Empirical-Research-Skills
All skills →
About this skill
What does the cross-disciplinary-ideation skill do?

Field connection mapping and systematic ideation for method transfer

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill cross-disciplinary-ideation --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