aer-preregistration
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill aer-preregistration --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.
# AER Pre-Registration ## Overview For experimental and prospective-data AER-track work, credibility is bought **before** the data exist. This skill writes the pre-analysis plan (PAP), sizes the sample from a power calculation, and registers the study. Its job is to make the eventual results un-p-hackable: a referee who sees a public PAP timestamp predating data collection cannot accuse you of spe
What does the aer-preregistration skill do?
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill aer-preregistration --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.