Github Research

Point it at a deep-research output directory and it runs a six-phase pipeline: extracts GitHub URLs and keywords from your research, searches multiple sources including Papers With Code, ranks 50-200 candidate repos, clones the top 15 for deep analysis, then produces an integration blueprint showing you which components are actually reusable. The script collection is extensive, all Python stdlib, covering everything from dependency extraction to cross-repo comparison matrices. It's built for the moment when you've read a dozen papers and need to know what code exists, what works, and how to combine it. Output is methodically organized with JSONL databases and markdown reports at each phase.