# Variable Map

> Compare how an empirical variable or construct is measured across papers, including data sources, model roles, and local-project availability

- Skill: `chanw-research/variable-map` (Agent Skill)
- Install (CLI): `npx skillmds@latest add chanw-research/variable-map`
- Raw SKILL.md: https://api.skillmd.com/api/skills/chanw-research/variable-map/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: chanw-research (https://skillmd.com/u/chanw-research)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/chanw-research/variable-map

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# /variable-map

Read `wiki/variables/*.md`, `wiki/papers/*.md`, `wiki/datasets/*.md`, `wiki/models/*.md`, project READMEs, and `raw/notes/research-intent.md` when present.

Produce a comparison table with: construct, variable role, measurement, data source, sample frequency, source papers, advantages, risks, and project availability.

Archive the result to `wiki/outputs/variable-map-{slug}-{YYYY-MM-DD}.md` and log it with `tools/research_wiki.py log`.

Constraints:

- Do not merge genuinely different measurement choices into one row.
- Do not invent database tables or project paths.
- Mark fields that exist in the literature but are missing locally as `missing from project`.