wrangling-skills
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill wrangling --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 Wrangling — 10 Skills Select the skill matching the user's need, then `read` its SKILL.md. | Skill | Description | |-------|-------------| | [csv-data-analyzer](./csv-data-analyzer/SKILL.md) | Load, explore, clean, and analyze CSV data with statistical summaries | | [data-cleaning-pipeline](./data-cleaning-pipeline/SKILL.md) | Systematic data cleaning workflows for research datasets | | [da
What does the wrangling-skills skill do?
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation tasks.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill wrangling --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.