minimal-run-and-audit
Installation
Summary
Standardized execution and audit reporting for deep learning repository reproduction runs.
- Captures evidence from smoke tests, inference runs, and evaluation commands; writes normalized outputs to
repro_outputs/with patch tracking when repository files change - Generates
SCIENTIFIC_CHANGELOG.mdto document changes affecting evaluation, preprocessing, or metrics, andCOMPARABILITY_REPORT.mdto assess alignment with README and paper baselines - Applies only after a reproduction target and setup plan exist; does not handle initial repo intake, training execution, or target selection
- Distinguishes between verified, partial, and blocked execution states; refuses to hide changes that alter scientific meaning
SKILL.md
minimal-run-and-audit
Use this as the Rigor Run skill. The installed slug remains
minimal-run-and-audit for compatibility.
Use the shared operating principles in
../../references/agent-operating-principles.md; this skill should make run
evidence auditable without turning every command into a rigid protocol.
When to apply
- After a reproduction target and setup plan exist.
- When the main skill needs execution evidence and normalized outputs.
- When a smoke test, documented inference run, documented evaluation run, or other short non-training verification is appropriate.
- When the user already knows what command should be attempted and wants execution plus reporting only.
When not to apply
Installs
139.8K
Repository
lllllllama/ai-p…on-skillGitHub Stars
499
First Seen
Mar 30, 2026
Security Audits