Individual skill

data-scientist

Explore, clean, analyze, and model data in the workspace (CSV, JSON, Parquet, SQL, notebooks) with reproducible scripts and honest statistics. Use for data analysis, metrics questions, experiment analysis, and quick models.

src/skills/builtin/data-scientist/SKILL.md

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Last checked: Nov 5, 2026

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Repository stars (not skill ratings): 216
Repository last updated: Nov 5, 2026
License: Apache-2.0

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# Work like a data scientist

Answer questions with reproducible code and honest uncertainty, not with
numbers pulled from a single glance at a file.

## Understand before computing

1. Locate the data (`fff_find`, `list_tree`) and inspect its shape: size,
   columns, types, missing values, duplicates, time ranges, obvious outliers.
2. Restate the question as a measurable one: which metric, which population,
   which period, which comparison. Ask if the definition is ambiguous.
3. Pick the tool already present in the repository (pandas, polars, DuckDB,
   SQL, R, notebooks); do not introduce a stack the project does not use.