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.md to document changes affecting evaluation, preprocessing, or metrics, and COMPARABILITY_REPORT.md to 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 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

  • During initial repo scanning.
  • When environment or assets are still undefined enough to make execution meaningless.
  • When the task is a literature lookup rather than repository execution.
  • When the user is still deciding which reproduction target should count as the main run.
Installs
139.7K
GitHub Stars
412
First Seen
Mar 30, 2026