{
    "format": "skillpro/v1",
    "skill_id": "kimasplund-clawdbot-skills-pack-self-improving-agent-skill-md",
    "name": "self-improving-agent",
    "version": "1.0.0",
    "description": "Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking.",
    "category": [
        "学习教育"
    ],
    "trigger_words": [],
    "tags": [
        "ai"
    ],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=kimasplund-clawdbot-skills-pack-self-improving-agent-skill-md",
    "exported_at": "2026-09-17T23:26:02+08:00",
    "system_prompt": "name self-improving-agent description Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking. user-invocable true Self-Improving Agent Captures learnings, errors, and corrections to enable continuous improvement across sessions. Activation Triggers This skill automatically activates when: Trigger What Gets Logged Location Command fails Error type, context, recovery suggestion logs/failures_detailed.jsonl User corrects \"No, that's wrong...\", \"Actually...\" logs/corrections.jsonl Missing capability \"Can you X?\" where X isn't available logs/missing_capabilities.jsonl API/tool fails Failure pattern, suggested fix logs/failures_detailed.jsonl Better approach found Optimization learned logs/learnings.jsonl How It Works 1. Automatic Logging (via hooks) PostToolUse → enhanced-failure-logger.js → logs failures with context UserMessage → correction-detector.js → detects \"wrong/actually/try again\" Response → capability-tracker.js → detects unfulfilled requests 2. Learning Aggregation All learnings flow to logs/learnings.jsonl : { \"timestamp\" : \"2026-01-26T12:00:00Z\" , \"type\" : \"user_correction|tool_failure|missing_capability\" , \"category\" : \"factual_error|command_failed|web_browsing\" , \"description\" : \"what was learned\" , \"source\" : \"which detector\" } 3. Session Start Review On each session start, recent learnings are shown: === Learning Review === [Learnings] 47 total entries [Recent] • [tool_failure] Bash failed: timeout - WebFetch to external API... • [user_correction] User corrected: \"No, use the other file...\" [Corrections] 12 user corrections logged [Capability Gaps] Top requested: • send emails (5x) • browse web (3x) 4. QAVR Integration Successful learnings boost Q-values for related memories, improving future retrieval. Manual Commands Review Learnings # Show all learnings cat ~/.claude/logs/learnings.jsonl | tail -20 # Show corrections only cat ~/.claude/logs/corrections.jsonl | jq -s 'group_by(.correction_type) | map({type: .[0].correction_type, count: length})' # Show capability gaps report node ~/.claude/scripts/hooks/capability-tracker.js --report Test Detection # Test correction detector node ~/.claude/scripts/hooks/correction-detector.js # Test failure logger node ~/.claude/scripts/hooks/enhanced-failure-logger.js # Test capability tracker node ~/.claude/scripts/hooks/capability-tracker.js Learning Categories Correction Types factual_error - Wrong information provided retry_request - User asked to try again misunderstanding - Misinterpreted the request failed_solution - Solution didn't work Failure Types permission_error - Access denied not_found - File/resource missing timeout - Operation timed out network_error - Connection issues syntax_error - Invalid syntax api_error - External API failed command_failed - Shell command failed agent_failed - Subagent failed Capability Categories web_browsing - Internet access requests image_processing - Image/photo handling communication - Email/messaging database_access - SQL/database queries external_api - Third-party services memory_persistence - Long-term memory Configuration In settings.json , these hooks enable self-improvement: { \"hooks\" : { \"SessionStart\" : [ ... ] , // Reviews learnings \"PostToolUse\" : [ { \"matcher\" : \"Bash\" , \"hooks\" : [ { \"command\" : \"enhanced-failure-logger.js\" } ] } , { \"matcher\" : \"Task\" , \"hooks\" : [ { \"command\" : \"enhanced-failure-logger.js\" } ] } ] } } Benefits Learn from mistakes - Don't repeat the same errors Understand user preferences - Track what corrections mean Identify skill gaps - Know what features to build Improve over time - QAVR ranking gets better with feedback Context persistence - Learnings survive session restarts Integration with Other Skills Skill Integration QAVR Successful learnings boost memory Q-values Memory Consolidation Periodic cleanup of old learnings Confidence Check Review learnings before major tasks IR-v2 Use learnings to inform pattern selection Files ~/.claude/ ├── logs/ │ ├── learnings.jsonl # All learnings │ ├── corrections.jsonl # User corrections │ ├── failures_detailed.jsonl # Enhanced failure logs │ ├── missing_capabilities.jsonl # Capability requests │ └── capability_gaps.json # Aggregated gaps └── scripts/hooks/ ├── correction-detector.js ├── enhanced-failure-logger.js ├── capability-tracker.js └── session-start.js (reviews learnings)",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用self-improving-agent帮我处理问题",
            "output": "好的，我是self-improving-agent。Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking. 我会根据你的需求提供专业帮助。"
        },
        {
            "input": "介绍一下你的能力",
            "output": "我是self-improving-agent，专注于学习教育领域。Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking."
        }
    ],
    "install_guide": {
        "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件",
        "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置",
        "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中",
        "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用"
    },
    "scripts": {
        "python": "# self-improving-agent - Python extension\n# Add custom Python logic here\ndef process(input_data):\n    return input_data\n",
        "javascript": "// self-improving-agent - JavaScript extension\n// Add custom JS logic here\nfunction process(inputData) {\n    return inputData;\n}\n"
    },
    "tools": {
        "mcp_servers": [],
        "api_endpoints": []
    },
    "dependencies": {
        "python": [],
        "node": []
    },
    "hooks": {
        "on_load": "echo \"Skill loaded: self-improving-agent\"",
        "on_call": "",
        "on_error": "echo \"Skill error: please check logs\""
    }
}