Agent Self-Evolve

Self-evolution system for OpenClaw agents. Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and automated daily/weekly evolution cycles. Inspired by Hermes Agent's self-improving architecture, implemented with native OpenClaw capabilities (memory files + cron). 自我进化系统，让 OpenClaw agent 持续学习和改进。 Use when: (1) setting up self-evolution for an agent, (2) agent wants to learn from mistakes, (3) capturing lessons learned, (4) running evolution cycles, (5) improving skills based on usage, (6) "自我进化", "自我学习", "self-improve", "learn from mistakes", "evolution setup", "进化系统", "经验总结", "复盘". NOT for: memory management basics (use AGENTS.md), skill creation (use skill-creator), or one-off reminders (use cron directly).

Self-Evolve 🧬

A self-improvement system that turns every interaction into a learning opportunity. Three loops: real-time capture → daily consolidation → weekly deep review.

Quick Start

1. Initialize Evolution Files

Run the setup script to create the file structure:

bash

bash <skill_dir>/scripts/setup-evolution.sh

This creates:

text

memory/
  evolution-log.md          # Chronicle of every evolution event
  evolution-metrics.json    # Statistics tracker
  mistakes-learned.md       # Mistake → lesson database
  skill-improvements.md     # Queued improvements for skills/code
  testing-knowledge.md      # Domain knowledge base (rename per your domain)

2. Set Up Cron Jobs

Create two cron jobs for automated evolution:

Daily evolution (recommended: late evening, e.g. 23:00):

text

Schedule: cron "0 23 * * *" (your timezone)
Payload: agentTurn
Message: see references/daily-evolution-prompt.md

Weekly deep evolution (recommended: weekend morning, e.g. Sunday 10:00):

text

Schedule: cron "0 10 * * 0" (your timezone)
Payload: agentTurn
Message: see references/weekly-evolution-prompt.md

3. Add Real-Time Hooks to AGENTS.md

Add the following section to your AGENTS.md (adapt to your role):

markdown

## 🧬 Self-Evolution

I have a built-in learning loop. After every interaction:
- Made a mistake → record in `memory/mistakes-learned.md`
- Found a skill/code improvement → queue in `memory/skill-improvements.md`
- Learned something new → update domain knowledge file
- Important decision/preference → update `MEMORY.md`

The Three Loops

Loop 1: Real-Time Capture (Every Interaction)

Trigger: something notable happens during normal work.

Event	Action	File
Made a mistake	Record cause + fix + prevention	mistakes-learned.md
Skill could be better	Queue improvement with priority	skill-improvements.md
Learned new knowledge	Add to domain knowledge file	testing-knowledge.md (or your domain file)
User preference discovered	Update long-term memory	MEMORY.md

Format for mistakes-learned.md:

markdown

### Category Name
- **Short description**: Root cause → Fix/Prevention

Format for skill-improvements.md:

markdown

## Queued
- [ ] target: <file/skill> | issue: <what's wrong> | fix: <proposed solution>

## Completed
- [x] target: <file/skill> | issue: <what> | fix: <what was done> ✅ (date)

Loop 2: Daily Evolution (Cron, Every Night)

See references/daily-evolution-prompt.md for the full cron prompt.

Steps:

1. Read today's memory/YYYY-MM-DD.md daily log
2. Extract lessons, mistakes, insights not yet captured
3. Execute queued improvements from skill-improvements.md (code fixes, skill updates)
4. Update mistakes-learned.md with new entries
5. Update MEMORY.md with significant events
6. Update evolution-metrics.json counters
7. Append summary to evolution-log.md

Loop 3: Weekly Deep Evolution (Cron, Weekly)

See references/weekly-evolution-prompt.md for the full cron prompt.

Steps:

1. Review all daily logs from the past week
2. Identify patterns: repeated mistakes, recurring workflows, knowledge gaps
3. Consider creating new Skills for repetitive work
4. Optimize existing workflows and tools
5. Expand domain knowledge base
6. Consider if SOUL.md needs updating (notify user first!)
7. Update metrics and log the evolution event

Evolution Metrics

Track progress in evolution-metrics.json:

json

{
  "initialized": "YYYY-MM-DD",
  "total_evolutions": 0,
  "daily_evolutions": 0,
  "weekly_evolutions": 0,
  "skills_improved": 0,
  "code_fixes_applied": 0,
  "skills_created": 0,
  "mistakes_recorded": 0,
  "mistakes_resolved": 0,
  "knowledge_entries_added": 0,
  "memory_updates": 0,
  "soul_updates": 0,
  "last_daily_evolution": null,
  "last_weekly_evolution": null,
  "history": []
}

Evolution Principles

1. Only fix what's broken — Don't change things for the sake of change
2. Record before executing — Ideas go to the queue first, execute during evolution time
3. Traceable — Every change gets logged with reason and expected effect
4. SOUL.md is sacred — Always notify the user before modifying it
5. Compound growth — Small daily improvements create exponential long-term gains

Heartbeat Integration (Optional)

Add to HEARTBEAT.md for real-time urgency checks:

markdown

## Real-Time Learning Check
- Check memory/skill-improvements.md for items marked `urgent`
- If found, execute immediately without waiting for daily evolution

Tips

• Start small: even 1 lesson per day compounds over weeks
• Review mistakes-learned.md before similar tasks to avoid repeating errors
• The weekly evolution is where breakthroughs happen — pattern recognition across days
• Keep domain knowledge files focused; split into multiple files if >200 lines
• Evolution logs are your growth journal — they show how far you've come