Minimal Run And Audit

You call this after you've already figured out what command to run in a deep learning reproduction attempt and now need clean evidence capture. It executes your smoke test or documented inference run, then writes standardized reports to repro_outputs including patch notes if files changed and a scientific changelog when changes touch metrics or evaluation logic. The boundaries are strict: it won't pick your reproduction target, won't do paper analysis, and won't hide risky edits. Think of it as the auditable execution layer that sits between "I know what to try" and "here's normalized proof of what happened." Good for turning messy README-driven repos into something you can actually cite evidence from.

Install to Claude Code

npx -y skills add lllllllama/rigorpilot-skills --skill minimal-run-and-audit --agent claude-code