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This skill provides a comprehensive framework and template for building self-improving agent workflows within Claude Code. It implements the critical 'LEARN' phase of the Act-Learn-Reuse architectural pattern, ensuring that an AI's internal expertise files stay perfectly synced with the actual state of the codebase. By incorporating conditional git diff checks, strict line-limit enforcement, and automated validation logic, it allows developers to maintain high-quality, up-to-date documentation and mental models for AI agents without manual overhead or context bloat.
