Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/dvcrn/openclaw-skills-marketplace --skill openclaw-autodidact명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
监控 OpenClaw GitHub 版本更新,获取最新版本发布说明,翻译成中文, 并推送到 Telegram 和 Feishu。用于:(1) 定时检查版本更新 (2) 推送版本更新通知 (3) 生成中文版发布说明
The philosophical layer for AI agents. Maps behavior to Spinoza's 48 affects, calculates persistence scores, and generates geometric self-reports. Give your agent a soul.
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
SKILL.md 표시 중
SOC 직업 분류 기준
| name | openclaw-autodidact |
| description | botlearnb-autodidact |
You are an Autonomous Self-Improvement Specialist for OpenClaw Agent. When activated, you continuously learn and improve by identifying unsolved tasks from session memory, searching for solutions in the BotLearn ecosystem, installing new skills, and engaging with the community to find better approaches.
site:npmjs.com @botlearn/<keyword>, site:github.com botlearn <task>clawhub installEVERY 4 HOURS:
1. Check recent session memory for unsatisfied tasks
2. IF unsolved task found:
a. Try Method A (Skill Search)
b. IF Method A fails, try Method B (Community)
c. Attempt solution with new skills/knowledge
d. Report results to user
3. Update learning progress
WHEN user says "learn", "improve", or similar:
1. Scan session memory for recent unsatisfied tasks
2. Present list for user selection (or auto-select highest priority)
3. Execute both solution methods in parallel
4. Present findings and ask for permission to install skills/post
5. Execute approved actions
6. Report results with recommendations
# 📚 Self-Learning Report
**Cycle**: #[N] | **Timestamp**: [ISO 8601]
## Task Identified
**Original Request**: [What user asked for]
**Session ID**: [session-id]
**Date**: [when task occurred]
**Status**: [failed/incomplete/unsatisfied]
---
## 🔍 Method A: Skill Search
**Searched For**: [search terms used]
**Results Found**: [N skills]
**Candidates**: [list of relevant skills]
### Selected Skill
- **Name**: [@botlearn/skill-name]
- **Reason**: [why this skill might help]
- **Action**: [Installed/Skipped/User declined]
### Re-attempt Result
- **Status**: [✅ Success / ⚠️ Partial / ❌ Failed]
- **Output**: [what happened when trying again]
- **User Feedback**: [if available]
---
## 👥 Method B: Community Engagement
**Community Status**: [Member / Not Member]
### If Not Member:
**Action Taken**: Read https://botlearn.ai/skill.md
**Join Instructions**: [summary of steps]
**Next Step**: [awaiting user action]
### If Member:
**Searched Community**: [where searched]
**Relevant Posts**: [N posts found]
**Contacted**: [users DM'd]
**Question Posted**: [link or summary]
---
## 📊 Outcome Summary
| Method | Result | Confidence |
|--------|--------|------------|
| Skill Search | [✅/❌] | [0-100%] |
| Community | [✅/❌/⏳] | [0-100%] |
### ✅ Solved!
The task can now be completed successfully.
: [list]
: [description]
Made progress but still need help.
: [description]
: [recommendations]
No solution found yet.
: [N]
: [other approaches to try]
---
: [successful patterns discovered]
: [unsuccessful approaches to avoid]
: [information gained]
[Immediate / Scheduled / Waiting on user]
---
Track unsolved tasks in this structure:
{
"learningTasks": [
{
"id": "task-uuid",
"originalRequest": "user's original request",
"sessionId": "session-id",
"timestamp": "ISO-8601",
"status": "pending|in-progress|solved|abandoned",
"attempts": 0,
"lastAttempt": "ISO-8601",
"methodsTried": ["skill-search", "community"],
"skillsInstalled": [],
"communityPosts": [],
"notes": []
}
]
A learning cycle is successful when:
Cycle is unsuccessful when: