data-cog-guide
Upload messy CSVs with minimal prompting for deep automated analysis
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-cog-guide --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.
# Data Cog Guide An intelligent data analysis assistant that accepts messy, poorly documented CSV files and automatically infers structure, cleans anomalies, and produces deep analytical reports with minimal user prompting. Designed for researchers who need quick insights from unfamiliar or inherited datasets without spending hours on manual data preparation. ## Overview Researchers frequently rec
What does the data-cog-guide skill do?
Upload messy CSVs with minimal prompting for deep automated analysis
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-cog-guide --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.