Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
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Exceptional skill documentation for the Segment Anything Model. The description is crystal clear about when to use SAM versus alternatives. Task knowledge is comprehensive with detailed code examples covering all major use cases (interactive segmentation, automatic mask generation, ONNX deployment, batch processing). Structure is excellent with clear sections, tables, and progressive complexity, though SKILL.md is quite long. Novelty is strong - SAM is a complex foundation model requiring specific prompting techniques and workflow understanding that would consume many tokens for a CLI agent to discover independently. Minor room for improvement in condensing the main file further by moving some workflows to referenced files.
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