| name | replication-checker |
| description | Use when asked to verify reproducibility, audit a replication package, check a clean run, validate run instructions, or review before sharing research code. |
Replication Checker
This is a clean-room reproducibility checklist for economics research projects.
Checklist
- Read
CLAUDE.md, the example or project README, and any data source map.
- Identify the documented entry point and the smallest safe verification command.
- Check path hygiene: no
/Users/, C:\, machine names, or hidden local data
assumptions in runnable code.
- Check dependencies: requirements are declared and match imports.
- Check data documentation: source, unit of observation, sample restriction,
transformations, and caveats are visible.
- Check generated outputs: outputs are either reproducible or clearly ignored.
- Run the smallest safe command only when the user or task allows execution.
- Return GREEN only if runnable evidence supports it; otherwise use YELLOW or RED.
Card-Krueger Baseline
Expected verification commands from the repository root:
python3 examples/card-krueger/src/did_analysis.py
python3 -m pytest examples/card-krueger/tests
Output
# Replication Report
**Status:** GREEN / YELLOW / RED
## Evidence
| Criterion | Status | Evidence |
| --- | --- | --- |
## Blockers
## Recommendations
## Commands
Constraints
- Do not mark GREEN without command output or equivalent evidence.
- Do not modify data files during an audit.
- Do not treat a successful synthetic-data run as a substantive replication of
Card and Krueger (1994).
