aejpol-robustness
Use when an AEJ: Economic Policy manuscript's headline policy estimate needs to be shown stable and credible against specification, sample, inference, and identification threats. Organizes the robustness program by threat-to-the-policy-conclusion; it does not design the primary identification or write exhibits.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejpol-robustness --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.
# Robustness — Defending the Policy Estimate (aejpol-robustness) ## When to trigger - The headline causal estimate moves across specifications, or you do not yet know if it does - A referee will ask "is this robust?" and you have no organized answer - Inference (clustering, few clusters, multiple outcomes) is not yet airtight - You need to show the **policy conclusion**, not just a coefficient, su
What does the aejpol-robustness skill do?
Use when an AEJ: Economic Policy manuscript's headline policy estimate needs to be shown stable and credible against specification, sample, inference, and identification threats. Organizes the robustness program by threat-to-the-policy-conclusion; it does not design the primary identification or write exhibits.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aejpol-robustness --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/Awesome-Journal-Skills, a repository with 909 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.