A universal self-improving agent that learns from ALL skill experiences. Uses multi-memory architecture (semantic + episodic + working) to continuously evolve the codebase. Auto-triggers on skill completion/error with hooks-based self-correction.
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Self-Improving Agent
"An AI agent that learns from every interaction, accumulating patterns and insights to continuously improve its own capabilities." — Based on 2025 lifelong learning research
Overview
This is a universal self-improvement system that learns from ALL skill experiences, not just PRDs. It implements a complete feedback loop with:
Multi-Memory Architecture: Semantic + Episodic + Working memory
Self-Correction: Detects and fixes skill guidance errors
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[Description truncada. Veja o README completo no GitHub.]
