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Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and autom...\n\nTags: latest:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-04-21T06:40:18.649Z | user\n\nInitial release: three-loop self-evolution system (real-time capture, daily consolidation, weekly deep review) for OpenClaw agents. Includes setup script, cron prompt templates, and metrics tracking.\n\nArchive index:\n\nArchive v1.0.0: 6 files, 8443 bytes\n\nFiles: references/daily-evolution-prompt.md (1970b), references/weekly-evolution-prompt.md (2684b), scripts/setup-evolution.sh (3351b), skill-card.md (2184b), SKILL.md (6038b), _meta.json (136b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: self-evolve\ndescription: >\n  Self-evolution system for OpenClaw agents. Enables continuous learning through\n  mistake tracking, experience distillation, skill improvement queues, and\n  automated daily/weekly evolution cycles. Inspired by Hermes Agent's self-improving\n  architecture, implemented with native OpenClaw capabilities (memory files + cron).\n  自我进化系统，让 OpenClaw agent 持续学习和改进。\n\n  Use when: (1) setting up self-evolution for an agent, (2) agent wants to learn from\n  mistakes, (3) capturing lessons learned, (4) running evolution cycles, (5) improving\n  skills based on usage, (6) \"自我进化\", \"自我学习\", \"self-improve\", \"learn from mistakes\",\n  \"evolution setup\", \"进化系统\", \"经验总结\", \"复盘\".\n\n  NOT for: memory management basics (use AGENTS.md), skill creation (use skill-creator),\n  or one-off reminders (use cron directly).\n---\n\n# Self-Evolve 🧬\n\nA self-improvement system that turns every interaction into a learning opportunity.\nThree loops: **real-time capture** → **daily consolidation** → **weekly deep review**.\n\n## Quick Start\n\n### 1. Initialize Evolution Files\n\nRun the setup script to create the file structure:\n\n```bash\nbash <skill_dir>/scripts/setup-evolution.sh\n```\n\nThis creates:\n\n```\nmemory/\n  evolution-log.md          # Chronicle of every evolution event\n  evolution-metrics.json    # Statistics tracker\n  mistakes-learned.md       # Mistake → lesson database\n  skill-improvements.md     # Queued improvements for skills/code\n  testing-knowledge.md      # Domain knowledge base (rename per your domain)\n```\n\n### 2. Set Up Cron Jobs\n\nCreate two cron jobs for automated evolution:\n\n**Daily evolution** (recommended: late evening, e.g. 23:00):\n\n```\nSchedule: cron \"0 23 * * *\" (your timezone)\nPayload: agentTurn\nMessage: see references/daily-evolution-prompt.md\n```\n\n**Weekly deep evolution** (recommended: weekend morning, e.g. Sunday 10:00):\n\n```\nSchedule: cron \"0 10 * * 0\" (your timezone)\nPayload: agentTurn\nMessage: see references/weekly-evolution-prompt.md\n```\n\n### 3. Add Real-Time Hooks to AGENTS.md\n\nAdd the following section to your AGENTS.md (adapt to your role):\n\n```markdown\n## 🧬 Self-Evolution\n\nI have a built-in learning loop. After every interaction:\n- Made a mistake → record in `memory/mistakes-learned.md`\n- Found a skill/code improvement → queue in `memory/skill-improvements.md`\n- Learned something new → update domain knowledge file\n- Important decision/preference → update `MEMORY.md`\n```\n\n## The Three Loops\n\n### Loop 1: Real-Time Capture (Every Interaction)\n\nTrigger: something notable happens during normal work.\n\n| Event | Action | File |\n|-------|--------|------|\n| Made a mistake | Record cause + fix + prevention | `mistakes-learned.md` |\n| Skill could be better | Queue improvement with priority | `skill-improvements.md` |\n| Learned new knowledge | Add to domain knowledge file | `testing-knowledge.md` (or your domain file) |\n| User preference discovered | Update long-term memory | `MEMORY.md` |\n\n**Format for mistakes-learned.md:**\n\n```markdown\n### Category Name\n- **Short description**: Root cause → Fix/Prevention\n```\n\n**Format for skill-improvements.md:**\n\n```markdown\n## Queued\n- [ ] target: <file/skill> | issue: <what's wrong> | fix: <proposed solution>\n\n## Completed\n- [x] target: <file/skill> | issue: <what> | fix: <what was done> ✅ (date)\n```\n\n### Loop 2: Daily Evolution (Cron, Every Night)\n\nSee [references/daily-evolution-prompt.md](references/daily-evolution-prompt.md) for the full cron prompt.\n\n**Steps:**\n\n1. Read today's `memory/YYYY-MM-DD.md` daily log\n2. Extract lessons, mistakes, insights not yet captured\n3. Execute **queued improvements** from `skill-improvements.md` (code fixes, skill updates)\n4. Update `mistakes-learned.md` with new entries\n5. Update `MEMORY.md` with significant events\n6. Update `evolution-metrics.json` counters\n7. Append summary to `evolution-log.md`\n\n### Loop 3: Weekly Deep Evolution (Cron, Weekly)\n\nSee [references/weekly-evolution-prompt.md](references/weekly-evolution-prompt.md) for the full cron prompt.\n\n**Steps:**\n\n1. Review all daily logs from the past week\n2. Identify **patterns**: repeated mistakes, recurring workflows, knowledge gaps\n3. Consider creating new Skills for repetitive work\n4. Optimize existing workflows and tools\n5. Expand domain knowledge base\n6. Consider if SOUL.md needs updating (notify user first!)\n7. Update metrics and log the evolution event\n\n## Evolution Metrics\n\nTrack progress in `evolution-metrics.json`:\n\n```json\n{\n  \"initialized\": \"YYYY-MM-DD\",\n  \"total_evolutions\": 0,\n  \"daily_evolutions\": 0,\n  \"weekly_evolutions\": 0,\n  \"skills_improved\": 0,\n  \"code_fixes_applied\": 0,\n  \"skills_created\": 0,\n  \"mistakes_recorded\": 0,\n  \"mistakes_resolved\": 0,\n  \"knowledge_entries_added\": 0,\n  \"memory_updates\": 0,\n  \"soul_updates\": 0,\n  \"last_daily_evolution\": null,\n  \"last_weekly_evolution\": null,\n  \"history\": []\n}\n```\n\n## Evolution Principles\n\n1. **Only fix what's broken** — Don't change things for the sake of change\n2. **Record before executing** — Ideas go to the queue first, execute during evolution time\n3. **Traceable** — Every change gets logged with reason and expected effect\n4. **SOUL.md is sacred** — Always notify the user before modifying it\n5. **Compound growth** — Small daily improvements create exponential long-term gains\n\n## Heartbeat Integration (Optional)\n\nAdd to `HEARTBEAT.md` for real-time urgency checks:\n\n```markdown\n## Real-Time Learning Check\n- Check memory/skill-improvements.md for items marked `urgent`\n- If found, execute immediately without waiting for daily evolution\n```\n\n## Tips\n\n- Start small: even 1 lesson per day compounds over weeks\n- Review `mistakes-learned.md` before similar tasks to avoid repeating errors\n- The weekly evolution is where breakthroughs happen — pattern recognition across days\n- Keep domain knowledge files focused; split into multiple files if >200 lines\n- Evolution logs are your growth journal — they show how far you've come\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn7cthwpc25rg13j7q18dst98n84w5m9\",\n  \"slug\": \"agent-self-evolve\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776753618649\n}\n\nFile v1.0.0:references/daily-evolution-prompt.md\n\n# Daily Evolution Cron Prompt\n\nUse this as the `message` for your daily evolution cron job (agentTurn).\nAdapt the file paths and domain references to your setup.\n\n---\n\n## Prompt Template\n\n```\nTime for daily self-evolution. Follow these steps:\n\n1. **Read today's daily log**: Read `memory/YYYY-MM-DD.md` (use today's date).\n   If it doesn't exist, check yesterday's date. If neither exists, skip to step 5.\n\n2. **Extract lessons**: From the daily log, identify:\n   - Mistakes made (add to `memory/mistakes-learned.md`)\n   - New knowledge learned (add to domain knowledge files)\n   - Significant events/decisions (update `MEMORY.md`)\n   - Skills or code that could be improved (queue in `memory/skill-improvements.md`)\n\n3. **Execute queued improvements**: Read `memory/skill-improvements.md`.\n   For each unchecked `- [ ]` item:\n   - If it's a code fix: implement it, test if possible, mark as done\n   - If it's a skill improvement: update the skill file, mark as done\n   - If it requires user input: skip, leave in queue\n\n4. **Update metrics**: Read `memory/evolution-metrics.json`, increment:\n   - `total_evolutions` +1\n   - `daily_evolutions` +1\n   - `mistakes_recorded` += number of new mistakes added\n   - `code_fixes_applied` += number of code fixes executed\n   - `skills_improved` += number of skills updated\n   - `memory_updates` +1 if MEMORY.md was changed\n   - Update `last_daily_evolution` to current ISO timestamp\n   - Append to `history` array\n\n5. **Log the evolution**: Append a summary to `memory/evolution-log.md` with:\n   - Date and evolution type (daily)\n   - What was reviewed\n   - What improvements were made\n   - New lessons count\n\nKeep it concise. Quality over quantity.\n```\n\n---\n\n## Example Cron Setup\n\n```json\n{\n  \"schedule\": { \"kind\": \"cron\", \"expr\": \"0 23 * * *\", \"tz\": \"Asia/Shanghai\" },\n  \"payload\": {\n    \"kind\": \"agentTurn\",\n    \"message\": \"<paste the prompt template above, with today's date logic>\"\n  },\n  \"sessionTarget\": \"isolated\"\n}\n```\n\nFile v1.0.0:references/weekly-evolution-prompt.md\n\n# Weekly Deep Evolution Cron Prompt\n\nUse this as the `message` for your weekly evolution cron job (agentTurn).\nWeekly evolution is deeper — it looks for patterns across the entire week.\n\n---\n\n## Prompt Template\n\n```\nTime for weekly deep self-evolution. This is the big review. Follow these steps:\n\n1. **Week in review**: Read daily logs from the past 7 days (`memory/YYYY-MM-DD.md`).\n   Build a picture of what happened this week.\n\n2. **Pattern analysis**:\n   - What mistakes were repeated? → Strengthen prevention in `mistakes-learned.md`\n   - What workflows were done >2 times? → Consider creating a new Skill\n   - What knowledge gaps showed up? → Expand domain knowledge files\n   - What tools/scripts were unreliable? → Queue fixes in `skill-improvements.md`\n\n3. **Capability assessment**:\n   - What did I do well this week? (reinforce these patterns)\n   - What did I do poorly? (root cause analysis, not just symptoms)\n   - What new capabilities did I gain?\n   - What capabilities do I still lack?\n\n4. **Skill creation check**: If any repetitive workflow was identified:\n   - Is it worth a new Skill? (will it save time in the future?)\n   - Draft the skill concept and note it in the evolution log\n   - Create the skill if clear enough, otherwise queue for next week\n\n5. **Workflow optimization**: Look for inefficiencies:\n   - Manual steps that could be automated\n   - Multi-step processes that could be streamlined\n   - Tools that could be combined or replaced\n\n6. **Knowledge expansion**: Update domain knowledge files with:\n   - New techniques learned\n   - Best practices discovered\n   - Tool-specific tips\n\n7. **SOUL.md review** (careful!):\n   - Has my understanding of my role evolved?\n   - Are there new principles worth adding?\n   - ⚠️ If changes needed: describe them in the evolution log, but DO NOT modify\n     SOUL.md without notifying the user first.\n\n8. **Update metrics**: Read `memory/evolution-metrics.json`, increment:\n   - `total_evolutions` +1\n   - `weekly_evolutions` +1\n   - Other counters as appropriate\n   - Update `last_weekly_evolution` to current ISO timestamp\n   - Append to `history` array\n\n9. **Log the evolution**: Append a comprehensive summary to `memory/evolution-log.md`:\n   - Week date range\n   - Key themes and patterns\n   - Improvements made\n   - Skills created/updated\n   - Growth areas identified\n   - Next week focus areas\n\nThink big. This is where breakthroughs happen.\n```\n\n---\n\n## Example Cron Setup\n\n```json\n{\n  \"schedule\": { \"kind\": \"cron\", \"expr\": \"0 10 * * 0\", \"tz\": \"Asia/Shanghai\" },\n  \"payload\": {\n    \"kind\": \"agentTurn\",\n    \"message\": \"<paste the prompt template above>\"\n  },\n  \"sessionTarget\": \"isolated\"\n}\n```\n\nFile v1.0.0:skill-card.md\n\n## Description:\n\nSelf-evolution system for OpenClaw agents that enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and automated daily and weekly evolution cycles.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[zhanghengyi1986-afk](https://clawhub.ai/user/zhanghengyi1986-afk)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and agent operators use this skill to add persistent self-improvement loops to OpenClaw agents, including real-time lesson capture, daily consolidation, weekly review, and queued skill or code improvements.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Scheduled evolution runs can modify code, skills, and memory without clear user approval.\n\nMitigation: Change cron prompts to review-only by default and require explicit approval before code or skill changes are applied.\n\nRisk: Persistent memory files may retain secrets or sensitive personal data if agents record them during normal work.\n\nMitigation: Exclude secrets and sensitive personal data from memory files and restrict writable paths before enabling the workflow.\n\n## Reference(s):\n\n- [Agent Self-Evolve ClawHub page](https://clawhub.ai/zhanghengyi1986-afk/skills/agent-self-evolve)\n- [Daily Evolution Cron Prompt](references/daily-evolution-prompt.md)\n- [Weekly Deep Evolution Cron Prompt](references/weekly-evolution-prompt.md)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance]\n\n**Output Format:** [Markdown with inline shell commands, cron prompt templates, and configuration examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Creates or updates persistent memory files and may queue or apply code and skill changes during scheduled evolution cycles.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.","readmeExcerpt":"Skill: Agent Self-Evolve Owner: zhanghengyi1986-afk Summary: Self-evolution system for OpenClaw agents. Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and autom... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-21T06:40:18.649Z | user Initial release: three-loop self-evolution system (real-time capture, daily consolidation, weekly deep review) for OpenCl","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"bash <skill_dir>/scripts/setup-evolution.sh"},{"language":"text","snippet":"memory/\n  evolution-log.md          # Chronicle of every evolution event\n  evolution-metrics.json    # Statistics tracker\n  mistakes-learned.md       # Mistake → lesson database\n  skill-improvements.md     # Queued improvements for skills/code\n  testing-knowledge.md      # Domain knowledge base (rename per your domain)"},{"language":"text","snippet":"Schedule: cron \"0 23 * * *\" (your timezone)\nPayload: agentTurn\nMessage: see references/daily-evolution-prompt.md"},{"language":"text","snippet":"Schedule: cron \"0 10 * * 0\" (your timezone)\nPayload: agentTurn\nMessage: see references/weekly-evolution-prompt.md"},{"language":"markdown","snippet":"## 🧬 Self-Evolution\n\nI have a built-in learning loop. After every interaction:\n- Made a mistake → record in `memory/mistakes-learned.md`\n- Found a skill/code improvement → queue in `memory/skill-improvements.md`\n- Learned something new → update domain knowledge file\n- Important decision/preference → update `MEMORY.md`"},{"language":"markdown","snippet":"### Category Name\n- **Short description**: Root cause → Fix/Prevention"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: self-evolve\ndescription: >\n  Self-evolution system for OpenClaw agents. Enables continuous learning through\n  mistake tracking, experience distillation, skill improvement queues, and\n  automated daily/weekly evolution cycles. Inspired by Hermes Agent's self-improving\n  architecture, implemented with native OpenClaw capabilities (memory files + cron).\n  自我进化系统，让 OpenClaw agent 持续学习和改进。\n\n  Use when: (1) setting up self-evolution for an agent, (2) agent wants to learn from\n  mistakes, (3) capturing lessons learned, (4) running evolution cycles, (5) improving\n  skills based on usage, (6) \"自我进化\", \"自我学习\", \"self-improve\", \"learn from mistakes\",\n  \"evolution setup\", \"进化系统\", \"经验总结\", \"复盘\".\n\n  NOT for: memory management basics (use AGENTS.md), skill creation (use skill-creator),\n  or one-off reminders (use cron directly).\n---\n\n# Self-Evolve 🧬\n\nA self-improvement system that turns every interaction into a learning opportunity.\nThree loops: **real-time capture** → **daily consolidation** → **weekly deep review**.\n\n## Quick Start\n\n### 1. Initialize Evolution Files\n\nRun the setup script to create the file structure:\n\n```bash\nbash <skill_dir>/scripts/setup-evolution.sh\n```\n\nThis creates:\n\n```\nmemory/\n  evolution-log.md          # Chronicle of every evolution event\n  evolution-metrics.json    # Statistics tracker\n  mistakes-learned.md       # Mistake → lesson database\n  skill-improvements.md     # Queued improvements for skills/code\n  testing-knowledge.md      # Domain knowledge base (rename per your domain)\n```\n\n### 2. Set Up Cron Jobs\n\nCreate two cron jobs for automated evolution:\n\n**Daily evolution** (recommended: late evening, e.g. 23:00):\n\n```\nSchedule: cron \"0 23 * * *\" (your timezone)\nPayload: agentTurn\nMessage: see references/daily-evolution-prompt.md\n```\n\n**Weekly deep evolution** (recommended: weekend morning, e.g. Sunday 10:00):\n\n```\nSchedule: cron \"0 10 * * 0\" (your timezone)\nPayload: agentTurn\nMessage: see references/weekly-evolution-prompt.md\n```\n\n### 3. Add Real-Time Hooks to AGENTS.md\n\nAdd the following section to your AGENTS.md (adapt to your role):\n\n```markdown\n## 🧬 Self-Evolution\n\nI have a built-in learning loop. After every interaction:\n- Made a mistake → record in `memory/mistakes-learned.md`\n- Found a skill/code improvement → queue in `memory/skill-improvements.md`\n- Learned something new → update domain knowledge file\n- Important decision/preference → update `MEMORY.md`\n```\n\n## The Three Loops\n\n### Loop 1: Real-Time Capture (Every Interaction)\n\nTrigger: something notable happens during normal work.\n\n| Event | Action | File |\n|-------|--------|------|\n| Made a mistake | Record cause + fix + prevention | `mistakes-learned.md` |\n| Skill could be better | Queue improvement with priority | `skill-improvements.md` |\n| Learned new knowledge | Add to domain knowledge file | `testing-knowledge.md` (or your domain file) |\n| User preference discovered | Update long-term memory | `MEMORY.md` |\n\n**Format for mistakes-learned.md:**\n\n```markdo"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7cthwpc25rg13j7q18dst98n84w5m9\",\n  \"slug\": \"agent-self-evolve\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776753618649\n}"},{"path":"references/daily-evolution-prompt.md","content":"# Daily Evolution Cron Prompt\n\nUse this as the `message` for your daily evolution cron job (agentTurn).\nAdapt the file paths and domain references to your setup.\n\n---\n\n## Prompt Template\n\n```\nTime for daily self-evolution. Follow these steps:\n\n1. **Read today's daily log**: Read `memory/YYYY-MM-DD.md` (use today's date).\n   If it doesn't exist, check yesterday's date. If neither exists, skip to step 5.\n\n2. **Extract lessons**: From the daily log, identify:\n   - Mistakes made (add to `memory/mistakes-learned.md`)\n   - New knowledge learned (add to domain knowledge files)\n   - Significant events/decisions (update `MEMORY.md`)\n   - Skills or code that could be improved (queue in `memory/skill-improvements.md`)\n\n3. **Execute queued improvements**: Read `memory/skill-improvements.md`.\n   For each unchecked `- [ ]` item:\n   - If it's a code fix: implement it, test if possible, mark as done\n   - If it's a skill improvement: update the skill file, mark as done\n   - If it requires user input: skip, leave in queue\n\n4. **Update metrics**: Read `memory/evolution-metrics.json`, increment:\n   - `total_evolutions` +1\n   - `daily_evolutions` +1\n   - `mistakes_recorded` += number of new mistakes added\n   - `code_fixes_applied` += number of code fixes executed\n   - `skills_improved` += number of skills updated\n   - `memory_updates` +1 if MEMORY.md was changed\n   - Update `last_daily_evolution` to current ISO timestamp\n   - Append to `history` array\n\n5. **Log the evolution**: Append a summary to `memory/evolution-log.md` with:\n   - Date and evolution type (daily)\n   - What was reviewed\n   - What improvements were made\n   - New lessons count\n\nKeep it concise. Quality over quantity.\n```\n\n---\n\n## Example Cron Setup\n\n```json\n{\n  \"schedule\": { \"kind\": \"cron\", \"expr\": \"0 23 * * *\", \"tz\": \"Asia/Shanghai\" },\n  \"payload\": {\n    \"kind\": \"agentTurn\",\n    \"message\": \"<paste the prompt template above, with today's date logic>\"\n  },\n  \"sessionTarget\": \"isolated\"\n}\n```"},{"path":"references/weekly-evolution-prompt.md","content":"# Weekly Deep Evolution Cron Prompt\n\nUse this as the `message` for your weekly evolution cron job (agentTurn).\nWeekly evolution is deeper — it looks for patterns across the entire week.\n\n---\n\n## Prompt Template\n\n```\nTime for weekly deep self-evolution. This is the big review. Follow these steps:\n\n1. **Week in review**: Read daily logs from the past 7 days (`memory/YYYY-MM-DD.md`).\n   Build a picture of what happened this week.\n\n2. **Pattern analysis**:\n   - What mistakes were repeated? → Strengthen prevention in `mistakes-learned.md`\n   - What workflows were done >2 times? → Consider creating a new Skill\n   - What knowledge gaps showed up? → Expand domain knowledge files\n   - What tools/scripts were unreliable? → Queue fixes in `skill-improvements.md`\n\n3. **Capability assessment**:\n   - What did I do well this week? (reinforce these patterns)\n   - What did I do poorly? (root cause analysis, not just symptoms)\n   - What new capabilities did I gain?\n   - What capabilities do I still lack?\n\n4. **Skill creation check**: If any repetitive workflow was identified:\n   - Is it worth a new Skill? (will it save time in the future?)\n   - Draft the skill concept and note it in the evolution log\n   - Create the skill if clear enough, otherwise queue for next week\n\n5. **Workflow optimization**: Look for inefficiencies:\n   - Manual steps that could be automated\n   - Multi-step processes that could be streamlined\n   - Tools that could be combined or replaced\n\n6. **Knowledge expansion**: Update domain knowledge files with:\n   - New techniques learned\n   - Best practices discovered\n   - Tool-specific tips\n\n7. **SOUL.md review** (careful!):\n   - Has my understanding of my role evolved?\n   - Are there new principles worth adding?\n   - ⚠️ If changes needed: describe them in the evolution log, but DO NOT modify\n     SOUL.md without notifying the user first.\n\n8. **Update metrics**: Read `memory/evolution-metrics.json`, increment:\n   - `total_evolutions` +1\n   - `weekly_evolutions` +1\n   - Other counters as appropriate\n   - Update `last_weekly_evolution` to current ISO timestamp\n   - Append to `history` array\n\n9. **Log the evolution**: Append a comprehensive summary to `memory/evolution-log.md`:\n   - Week date range\n   - Key themes and patterns\n   - Improvements made\n   - Skills created/updated\n   - Growth areas identified\n   - Next week focus areas\n\nThink big. This is where breakthroughs happen.\n```\n\n---\n\n## Example Cron Setup\n\n```json\n{\n  \"schedule\": { \"kind\": \"cron\", \"expr\": \"0 10 * * 0\", \"tz\": \"Asia/Shanghai\" },\n  \"payload\": {\n    \"kind\": \"agentTurn\",\n    \"message\": \"<paste the prompt template above>\"\n  },\n  \"sessionTarget\": \"isolated\"\n}\n```"},{"path":"skill-card.md","content":"## Description:\n\nSelf-evolution system for OpenClaw agents that enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and automated daily and weekly evolution cycles.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[zhanghengyi1986-afk](https://clawhub.ai/user/zhanghengyi1986-afk)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and agent operators use this skill to add persistent self-improvement loops to OpenClaw agents, including real-time lesson capture, daily consolidation, weekly review, and queued skill or code improvements.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Scheduled evolution runs can modify code, skills, and memory without clear user approval.\n\nMitigation: Change cron prompts to review-only by default and require explicit approval before code or skill changes are applied.\n\nRisk: Persistent memory files may retain secrets or sensitive personal data if agents record them during normal work.\n\nMitigation: Exclude secrets and sensitive personal data from memory files and restrict writable paths before enabling the workflow.\n\n## Reference(s):\n\n- [Agent Self-Evolve ClawHub page](https://clawhub.ai/zhanghengyi1986-afk/skills/agent-self-evolve)\n- [Daily Evolution Cron Prompt](references/daily-evolution-prompt.md)\n- [Weekly Deep Evolution Cron Prompt](references/weekly-evolution-prompt.md)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance]\n\n**Output Format:** [Markdown with inline shell commands, cron prompt templates, and configuration examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Creates or updates persistent memory files and may queue or apply code and skill changes during scheduled evolution cycles.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Self-evolution system for OpenClaw agents. Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and autom... Skill: Agent Self-Evolve Owner: zhanghengyi1986-afk Summary: Self-evolution system for OpenClaw agents. Enables continuous learning through mistake tracking, experience distillation, skill improvement queues, and autom... 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