What problem does it solve? Building a Griptape Nodes library around an open-source ML model requires manually digging through the model's repository to understand its dependencies, inference APIs, HuggingFace models, and licensing. This Skill automates that research and produces a complete, structured specification file that downstream library setup and node implementation phases can consume directly. ## Core Features & Use Cases - Automated Repository Analysis: Fetches the GitHub repo page and README, shallow-clones the source, and inspects dependency files, inference entry points, and licenses. - Dependency and Hardware Detection: Identifies requirements.txt, pip-installability, GPU requirements, and build-time torch dependencies like flash-attn or auto_gptq. - HuggingFace Model Validation: Verifies every discovered HuggingFace model ID is a real, publicly accessible repository before including it in the spec. - Node Design Recommendations: Proposes node classes with complete input/output tables, base classes, and processing logic based on the model's API boundaries. - Use Case: Given the SAM3 repository URL and a target library path, produce a spec.md defining the library name, package structure, categories, and fully specified segmentation nodes ready for implementation. ## Quick Start Research the open-source model at https://github.com/facebookresearch/sam3 and write a library specification into my Griptape Nodes library repo at /Users/me/nodes/griptape-nodes-library-sam3.
