Takes a fresh repo and does the boring first pass: reads the README, scans for setup scripts and documented commands, then categorizes what looks like inference versus training versus evaluation workflows. Outputs a structured plan with the safest reproduction path forward. Saves you from manually parsing through project files to figure out where to start, especially when you're dealing with academic ML repos that have scattered documentation. The classification tends to be conservative, which is good since it's meant to feed into an orchestrator that makes the actual execution decisions.
claude skill add lllllllama/ai-paper-reproduction-skill:repo-intake-and-plan