Agent Self-Evolve
/install agent-self-evolve
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 \x3Cskill_dir>/scripts/setup-evolution.sh
This creates:
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):
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):
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):
## 🧬 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:
### Category Name
- **Short description**: Root cause → Fix/Prevention
Format for skill-improvements.md:
## Queued
- [ ] target: \x3Cfile/skill> | issue: \x3Cwhat's wrong> | fix: \x3Cproposed solution>
## Completed
- [x] target: \x3Cfile/skill> | issue: \x3Cwhat> | fix: \x3Cwhat was done> ✅ (date)
Loop 2: Daily Evolution (Cron, Every Night)
See references/daily-evolution-prompt.md for the full cron prompt.
Steps:
- Read today's
memory/YYYY-MM-DD.mddaily log - Extract lessons, mistakes, insights not yet captured
- Execute queued improvements from
skill-improvements.md(code fixes, skill updates) - Update
mistakes-learned.mdwith new entries - Update
MEMORY.mdwith significant events - Update
evolution-metrics.jsoncounters - 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:
- Review all daily logs from the past week
- Identify patterns: repeated mistakes, recurring workflows, knowledge gaps
- Consider creating new Skills for repetitive work
- Optimize existing workflows and tools
- Expand domain knowledge base
- Consider if SOUL.md needs updating (notify user first!)
- Update metrics and log the evolution event
Evolution Metrics
Track progress in evolution-metrics.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
- Only fix what's broken — Don't change things for the sake of change
- Record before executing — Ideas go to the queue first, execute during evolution time
- Traceable — Every change gets logged with reason and expected effect
- SOUL.md is sacred — Always notify the user before modifying it
- Compound growth — Small daily improvements create exponential long-term gains
Heartbeat Integration (Optional)
Add to HEARTBEAT.md for real-time urgency checks:
## 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.mdbefore 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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install agent-self-evolve - 安装完成后,直接呼叫该 Skill 的名称或使用
/agent-self-evolve触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Agent Self-Evolve 是什么?
Self-evolution system for OpenClaw agents. Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and autom... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 107 次。
如何安装 Agent Self-Evolve?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-self-evolve」即可一键安装,无需额外配置。
Agent Self-Evolve 是免费的吗?
是的,Agent Self-Evolve 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Agent Self-Evolve 支持哪些平台?
Agent Self-Evolve 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Agent Self-Evolve?
由 zhanghengyi1986-afk(@zhanghengyi1986-afk)开发并维护,当前版本 v1.0.0。