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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Excellent skill documentation for Meta's Segment Anything Model. The description clearly articulates when to use SAM (zero-shot segmentation with flexible prompts) vs alternatives. SKILL.md provides comprehensive task knowledge with detailed code examples covering all major use cases: interactive segmentation (points, boxes, masks), automatic mask generation, batch processing, and ONNX deployment. Structure is logical with clear sections progressing from quick start to advanced workflows. The skill offers meaningful novelty by packaging a complex foundation model with domain-specific guidance that would require substantial tokens for a CLI agent to discover independently. Documentation includes proper model selection guidance, performance optimization, and practical workflows (annotation tools, object extraction, medical imaging). Minor improvement opportunity: could benefit from a more prominent index/TOC given the comprehensive coverage, though the linear flow remains clear.
zechenzhangAGI
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