{"slug":"github-reuse-assistant","title":"github-reuse-assistant","description":"ML/DL GitHub project reuse assistant - a structured 6-phase workflow plugin for Claude Code. Guides users from git\nclone to successful training and testing of any ML/DL GitHub project. Features include: deep research via DeepWiki\nand paper reading with structured PROJECT_NOTES.md output, environment compatibility checking with OOM estimation and\nbatch size recommendations, dataset format validation with automatic conversion script generation and visualization,\nconfiguration file management with parameter checklists, and built-in error auto-diagnosis for common training\nfailures (OOM, NaN loss, size mismatch, etc.). Supports PyTorch, TensorFlow, and multi-platform (Linux/macOS/WSL2).","developer":null,"category":null,"reported_installs":null,"active":true,"first_seen_at":"2026-10-03T22:13:33.942Z","last_seen_at":"2026-10-10T12:00:00.763Z","last_changed_at":"2026-10-03T22:13:33.942Z","platform":"claude","sources":["Community"],"works_with":["Claude Code"],"marketplace_url":null,"repository_url":"https://github.com/lidapengpeng/github-reuse-assistant.git","web_data":{},"github_data":{},"catalog_sources":{"community":[{"name":"github-reuse-assistant","source":{"sha":"2d3ee37cb318ef98bbf0cc61d8f7bb75bf01770e","url":"https://github.com/lidapengpeng/github-reuse-assistant.git","source":"url"},"homepage":"https://github.com/lidapengpeng/github-reuse-assistant","description":"ML/DL GitHub project reuse assistant - a structured 6-phase workflow plugin for Claude Code. Guides users from git\nclone to successful training and testing of any ML/DL GitHub project. Features include: deep research via DeepWiki\nand paper reading with structured PROJECT_NOTES.md output, environment compatibility checking with OOM estimation and\nbatch size recommendations, dataset format validation with automatic conversion script generation and visualization,\nconfiguration file management with parameter checklists, and built-in error auto-diagnosis for common training\nfailures (OOM, NaN loss, size mismatch, etc.). Supports PyTorch, TensorFlow, and multi-platform (Linux/macOS/WSL2)."}]}}