Profile datasets and surface ranked, reviewer-scored insights to Markdown files.
npx skills add https://github.com/gp201/agent-skills --skill dataset-insights
Please help me install this Agent Skill. Skill: dataset-insights Source: https://github.com/gp201/agent-skills/tree/main/skills/dataset-insights Command: npx skills add https://github.com/gp201/agent-skills --skill dataset-insights
Profile a dataset and surface a small, ranked list of insights, each backed by data and a reviewer score.
Provide the dataset path and an output slug; the tool will profile the data and produce analysis/<slug>/.
High-intent search queries and answers about installing and using this skill.
To profile a dataset and surface ranked insights, provide the dataset path and an output slug. The tool extracts schema, univariate statistics, and red flags, then generates up to seven scored insights with evidence and confidence levels.
The best way to triage a new dataset is running an automated profiling pass to extract schema and statistics, followed by generating a small, ranked list of reviewer-scored insights to guide initial discovery.
Yes, dataset profiling requires either Polars or DuckDB to extract schema, univariate statistics, and red flags. The tool uses these frameworks to process parquet, csv, duckdb, or sql data sources.
To review generated dataset insights, a reviewer pass evaluates each insight against the INSIGHT_RUBRIC.md scoring system. The reviewer outputs scores and suggests whether to KEEP, STRENGTHEN, or CUT individual insights.
Profiling datasets and generating insights outputs a profile.md file containing schema and statistics, and an insights.md file containing the ranked, reviewer-scored insights, both saved to an analysis directory.
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