stata-causal-inference
Design, run, and critique causal inference workflows in Stata. Use when the user is working on identification, treatment effects, DiD, IV, event studies, RD, or assumption-sensitive empirical claims.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill stata-causal-inference --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.
# Causal Inference Use this skill when the question is causal, not merely predictive. 1. Clarify the identification strategy. 2. Check the right diagnostics and assumptions for the design. 3. Separate point estimates from identification credibility. Read `references/designs.md` for design-specific guidance.
What does the stata-causal-inference skill do?
Design, run, and critique causal inference workflows in Stata. Use when the user is working on identification, treatment effects, DiD, IV, event studies, RD, or assumption-sensitive empirical claims.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill stata-causal-inference --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.