data-audit
Scans notebooks for data file references and verifies each file exists on disk. Use when checking for broken data paths.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-audit --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.
# Audit Data References Scan all notebooks for data file references and verify they exist on disk. ## Steps 1. Scan all `.ipynb` files in `notebooks/` for data loading patterns: - **Python:** `pd.read_csv(...)`, `pd.read_stata(...)`, `pd.read_excel(...)`, `pd.read_parquet(...)`, `open(...)`, `np.loadtxt(...)` - **R:** `read.csv(...)`, `read_csv(...)`, `read.dta(...)`, `haven::read_dta(...)`, `read
What does the data-audit skill do?
Scans notebooks for data file references and verifies each file exists on disk. Use when checking for broken data paths.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-audit --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.