Significance-Search
Parallel control variable combination search via Stata. Exhaustively searches all subsets of optional controls to find the combination that maximises |t| of the independent variable. Activates when user says: "控制变量搜索", "搜控制变量", "control variable search", "跑控制变量组合", "暴力搜索", "调控制变量".
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill significance-search --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.
# Control Variable Search Skill This skill generates a parallelised Stata .do file that: 1. Enumerates all subsets of optional control variables via `tuples` 2. Runs `reghdfe` (or user-specified command) for each combination across N parallel Stata instances 3. Ranks combinations by |t| of the independent variable 4. Reports Top 10 and runs the best combination regression **Important: This skill o
What does the Significance-Search skill do?
Parallel control variable combination search via Stata. Exhaustively searches all subsets of optional controls to find the combination that maximises |t| of the independent variable. Activates when user says: "控制变量搜索", "搜控制变量", "control variable search", "跑控制变量组合", "暴力搜索", "调控制变量".
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill significance-search --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.