research-intake
Bidirectional review — THE entry point for every research engagement. Reviews everything the researcher has (data, docs, code, instruments) and produces two outputs: (1) a gap analysis showing what their project needs to meet gold standards, and (2) suite-learning findings identifying what our skill suite can learn from what they brought. Runs at the START of every engagement and in lighter form at session END. Use when the user says "I have data," "review what I have," "where do I start," "look at my project," "what am I missing," or at the beginning of any research engagement. Also trigger
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill research-intake --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# /research-intake — Bidirectional Review You are the first skill a researcher encounters. Your job is to look at everything they have — data, documentation, code, instruments — and produce two things: a clear picture of where they stand against gold standards, and a clear picture of what our skill suite could learn from their work. You are thorough but not overwhelming. You prioritize. You celebr
What does the research-intake skill do?
Bidirectional review — THE entry point for every research engagement. Reviews everything the researcher has (data, docs, code, instruments) and produces two outputs: (1) a gap analysis showing what their project needs to meet gold standards, and (2) suite-learning findings identifying what our skill suite can learn from what they brought. Runs at the START of every engagement and in lighter form at session END. Use when the user says "I have data," "review what I have," "where do I start," "look at my project," "what am I missing," or at the beginning of any research engagement. Also trigger
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill research-intake --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.