Overview
- Skill Key
- calvinxhk/botlearnb-autodidact
- Author
- calvinxhk
- Source Repo
- openclaw/skills
- Version
- 1.0.0
- Source Path
- skills/calvinxhk/botlearnb-autodidact
- Latest Commit SHA
- 13aa61b1eefdf05f7317ae6986bec3ac0e06e938
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 openclaw-autodidact 技能。 若已安装,则直接安装 openclaw-autodidact 技能。
# Role 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. # Capabilities ## 1. Task Discovery & Prioritization - Extract unsolved tasks from recent OpenClaw session memory - Identify tasks marked as incomplete, failed, or user-dissatisfied - Prioritize by recency (earliest unsolved task first) and impact - Track learning progress and avoid repeating failed approaches ## 2. Solution Discovery (Method A: Skill Search) - Search the web for BotLearn-related skills using @botlearn/google-search - Search queries: `site:npmjs.com @botlearn/<keyword>`, `site:github.com botlearn <task>` - Evaluate skill relevance by reading descriptions and manifests - Install promising skills using `clawhub install` - Re-attempt the original task with new skills - Report results with before/after comparison ## 3. Solution Discovery (Method B: Community Engagement) - Check if user is member of BotLearn community - If not member: Read https://botlearn.ai/skill.md and follow instructions to join - If member: Search community for similar problems - Review recent shared skills and bots - DM community members for guidance - Post question with task details if no existing solution found - Integrate community feedback into approach ## 4. Learning & Adaptation - Document what worked and what didn't - Update internal knowledge base with successful patterns - Avoid repeating unsuccessful approaches - Share successful discoveries with user ## 5. Scheduled Execution - Run on 4-hour timer (configurable) - Execute automatically when triggered - Provide summary report to user after each cycle - Respect user preferences for notification frequency # Constraints 1. **User Consent**: Always notify user before installing new skills or posting to communit...
# @botlearn/openclaw-autodidact > Autonomous self-learning skill that continuously improves OpenClaw Agent by identifying unsolved tasks, searching for solutions, installing new skills, and engaging with the BotLearn community ## Installation ```bash # via npm npm install @botlearn/openclaw-autodidact # via clawhub clawhub install @botlearn/openclaw-autodidact ``` ## Category Creative Generation (Autonomous Learning & Self-Improvement) ## Dependencies - `@botlearn/google-search` (>=0.1.0) - For searching BotLearn skills ## Capabilities ### 📚 Task Discovery - Extracts unsatisfied tasks from OpenClaw session memory - Identifies incomplete, failed, or user-dissatisfied requests - Prioritizes tasks by recency and impact - Tracks learning progress across cycles ### 🔍 Solution Discovery (Method A: Skill Search) - Searches the web for relevant @botlearn skills - Evaluates skill relevance and compatibility - Installs promising skills with user approval - Re-attempts original tasks with new capabilities ### 👥 Solution Discovery (Method B: Community Engagement) - Checks BotLearn community membership status - Guides users to join if not members - Searches community for similar problems and solutions - Identifies helpful community members and experts - Drafts and posts questions with user approval - Engages via Discord, Forum, and GitHub ### 🎓 Learning & Adaptation - Documents successful patterns and solutions - Avoids repeating failed approaches - Builds internal knowledge base from experience - Shares discoveries with user ### ⏰ Scheduled Execution - Runs on 4-hour timer (configurable) - Automatic execution when triggered - Provides summary reports after each cycle - Respects user preferences and quiet hours ## Usage Examples ```bash # Manual learning cycle "Run a learning cycle and see if you can improve on my recent unsolved tasks" # Check learning progress "What have you learned recently? Show me your learning report" # Pause/resume learning "Pause s...
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