| name | research-reproducibility-audit |
| description | Audit a paper, codebase, benchmark, or artifact for reproducibility gaps in ML, systems, and hardware research. Use when checking whether claims can be reproduced, comparing paper-versus-code behavior, validating release readiness, or preparing an artifact evaluation package. |
Research Reproducibility Audit
Use this skill when a result looks plausible but the path to reproducing it is weak.
Core Workflow
- Enumerate the paper or artifact claims.
- Map each claim to code, config, data, hardware, and evaluation evidence.
- Separate what is released from what is merely described.
- Identify blockers:
- missing checkpoints,
- hidden preprocessing,
- absent seeds,
- undocumented hardware,
- unstable dependencies,
- benchmark ambiguity.
- Rank reproduction risk by impact and fix cost.
Execution Rules
- Distinguish claim failure from release incompleteness.
- Prefer exact paths, commands, and config names over summaries.
- Treat hardware and software environment drift as first-class risks.
- End with the minimum changes required for a third party to reproduce the result.
Output Contract
Return:
- Claim-evidence map.
- Blocking gaps.
- Nice-to-have gaps.
- Reproduction verdict.
- Release hardening checklist.