Agent Skills: Agent Prompt Evolution

Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.

UncategorizedID: majiayu000/claude-skill-registry/Agent Prompt Evolution

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pnpm dlx add-skill https://github.com/majiayu000/claude-skill-registry/Agent Prompt Evolution

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