estimate
Run a structural estimation pipeline — routes to /workflows:work with estimation context from empirical-playbook
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill estimate --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.
This command routes to `/workflows:work` with estimation pipeline context. Before starting, load the `empirical-playbook` skill and its `references/estimation-pipeline.md` for the phased estimation workflow (data validation → identification → estimation → standard errors → robustness → results). Now run `/workflows:work` with the estimation pipeline framing. Follow the phase gates in `estimation-pipeline.md` — do not proceed to the next phase until the current phase's gate conditions are met.
What does the estimate skill do?
Run a structural estimation pipeline — routes to /workflows:work with estimation context from empirical-playbook
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill estimate --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.