self-improving-agent

Installation
Summary

Universal self-improving agent that learns from all skill experiences using multi-memory architecture.

  • Implements semantic, episodic, and working memory to extract patterns, abstract insights, and continuously evolve skill guidance across the codebase
  • Auto-triggers on skill completion, errors, and session events via hooks-based integration; detects and corrects inaccurate guidance with traceable evolution markers
  • Prioritizes updates across 10+ skill categories (PRD planning, architecture, API design, debugging, code review, performance, security, testing, deployment) based on pattern confidence and application frequency
  • Consolidates feedback loops with user ratings, root cause analysis, and validation workflows to prevent over-generalization and maintain guidance accuracy
SKILL.md

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
  • Self-Validation: Periodically verifies skill accuracy
  • Hooks Integration: Auto-triggers on skill events (before_start, after_complete, on_error)
  • Evolution Markers: Traceable changes with source attribution

Research-Based Design

Based on 2025 research:

Related skills
Installs
27.9K
GitHub Stars
54
First Seen
Jan 22, 2026