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SKILL.md

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+---
+name: self-improving-agent
+description: "分析对话质量、识别改进机会并持续优化响应策略的自我改进代理系统。"
+version: "1.0.0"
+author: xiucheng
+type: skill
+tags: [self-improvement, learning, optimization, reflection, growth]
+homepage: https://github.com/xiucheng/self-improving-agent
+license: MIT
+---
+
+# Self-Improving Agent
+
+An intelligent self-improvement system for OpenClaw agents that analyzes conversation quality and continuously optimizes performance.
+
+## Features
+
+- 📊 **Quality Analysis**: Evaluates conversation effectiveness
+- 🎯 **Improvement Tracking**: Identifies areas for enhancement
+- 📝 **Learning Log**: Records insights and lessons learned
+- 📈 **Weekly Reports**: Generates improvement summaries
+- 🔄 **Strategy Optimization**: Adapts response patterns over time
+
+## Installation
+
+```bash
+clawhub install self-improving-agent
+```
+
+## Usage
+
+### Automatic Analysis
+The skill automatically analyzes conversations after each session.
+
+### Manual Improvement Logging
+```python
+from self_improving import SelfImprovingAgent
+
+sia = SelfImprovingAgent()
+sia.log_improvement("Need to be more concise in technical explanations")
+```
+
+### Generate Weekly Report
+```python
+report = sia.generate_weekly_report()
+print(report)
+```
+
+## Configuration
+
+| Setting | Default | Description |
+|---------|---------|-------------|
+| improvement_log | ./improvement_log.md | Learning log file |
+| soul_file | ./SOUL.md | Personality anchor file |
+| auto_analyze | true | Auto-analyze conversations |
+
+## Integration
+
+Works best with:
+- `memory-manager`: For tracking improvement history
+- Custom agent personalities (SOUL.md)
+
+## License
+
+MIT License - Help agents get better every day!

_meta.json

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+{
+  "ownerId": "kn7c2cjr3n1gggfqy000zq5g898285x4",
+  "slug": "xiucheng-self-improving-agent",
+  "version": "1.0.0",
+  "publishedAt": 1772840626935
+}

self_improving.py

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+#!/usr/bin/env python3
+"""Self-Improving Agent - Continuous improvement system for OpenClaw agents.
+
+Author: xiucheng
+Version: 1.0.0
+License: MIT
+"""
+
+import os
+import json
+import re
+from datetime import datetime, timedelta
+from pathlib import Path
+from typing import List, Dict, Optional, Any
+
+
+class SelfImprovingAgent:
+    """Analyzes and improves agent performance over time."""
+    
+    def __init__(self, workspace: str = "/root/.openclaw/workspace"):
+        """Initialize self-improving agent.
+        
+        Args:
+            workspace: Path to OpenClaw workspace
+        """
+        self.workspace = Path(workspace)
+        self.improvement_log = self.workspace / "improvement_log.md"
+        self.soul_file = self.workspace / "SOUL.md"
+        
+    def analyze_conversation(
+        self, 
+        conversation: str, 
+        feedback: Optional[str] = None,
+        metrics: Optional[Dict] = None
+    ) -> Dict[str, Any]:
+        """Analyze conversation quality.
+        
+        Args:
+            conversation: Conversation text to analyze
+            feedback: Optional user feedback
+            metrics: Optional performance metrics
+            
+        Returns:
+            Analysis results dict
+        """
+        analysis = {
+            "timestamp": datetime.now().isoformat(),
+            "length": len(conversation),
+            "feedback": feedback,
+            "improvements": [],
+            "strengths": []
+        }
+        
+        # Heuristic analysis
+        if feedback:
+            if any(word in feedback for word in ["好", "棒", "优秀", "good", "great"]):
+                analysis["strengths"].append("Current approach is effective")
+            if any(word in feedback for word in ["慢", "慢", "slow", "delay"]):
+                analysis["improvements"].append("Improve response speed")
+            if any(word in feedback for word in ["长", "啰嗦", "verbose", "long"]):
+                analysis["improvements"].append("Be more concise")
+        
+        # Length-based analysis
+        if len(conversation) > 5000:
+            analysis["improvements"].append("Consider summarizing long responses")
+        elif len(conversation) < 100:
+            analysis["improvements"].append("Provide more detailed explanations")
+        else:
+            analysis["strengths"].append("Response length is appropriate")
+        
+        return analysis
+    
+    def log_improvement(self, insight: str, category: str = "general") -> None:
+        """Log an improvement insight.
+        
+        Args:
+            insight: The improvement insight
+            category: Category (e.g., 'communication', 'technical', 'speed')
+        """
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")
+        
+        with open(self.improvement_log, "a", encoding="utf-8") as f:
+            f.write(f"\n## [{timestamp}] {category}\n")
+            f.write(f"- {insight}\n")
+    
+    def generate_weekly_report(self) -> str:
+        """Generate weekly improvement report.
+        
+        Returns:
+            Formatted report string
+        """
+        week_start = datetime.now() - timedelta(days=7)
+        
+        report_lines = [
+            "# 🔄 Self-Improvement Weekly Report",
+            f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}",
+            "",
+            "## 📊 This Week's Insights",
+        ]
+        
+        # Read improvement log
+        if self.improvement_log.exists():
+            with open(self.improvement_log, "r", encoding="utf-8") as f:
+                content = f.read()
+                # Count entries from this week
+                entries = [line for line in content.split("\n## ") 
+                          if week_start.strftime("%Y-%m-%d") in line]
+                report_lines.append(f"- Total improvements logged: {len(entries)}")
+        else:
+            report_lines.append("- No improvements logged yet")
+        
+        report_lines.extend([
+            "",
+            "## 🎯 Next Week Goals",
+            "- Continue monitoring conversation quality",
+            "- Identify patterns in user feedback",
+            "- Update response strategies based on insights",
+            "",
+            "---",
+            "*Keep improving, one conversation at a time!*"
+        ])
+        
+        return "\n".join(report_lines)
+    
+    def get_improvement_stats(self) -> Dict[str, Any]:
+        """Get improvement statistics.
+        
+        Returns:
+            Statistics dict
+        """
+        stats = {
+            "log_exists": self.improvement_log.exists(),
+            "soul_exists": self.soul_file.exists(),
+            "total_entries": 0
+        }
+        
+        if self.improvement_log.exists():
+            with open(self.improvement_log, "r", encoding="utf-8") as f:
+                content = f.read()
+                stats["total_entries"] = content.count("\n## [")
+                stats["log_size_kb"] = round(len(content) / 1024, 2)
+        
+        return stats
+    
+    def suggest_soul_updates(self) -> List[str]:
+        """Suggest updates to SOUL.md based on learnings.
+        
+        Returns:
+            List of suggested updates
+        """
+        suggestions = []
+        
+        if not self.improvement_log.exists():
+            return ["Start logging improvements to generate suggestions"]
+        
+        with open(self.improvement_log, "r", encoding="utf-8") as f:
+            content = f.read()
+            
+        # Analyze patterns
+        if "concise" in content.lower() or "简洁" in content:
+            suggestions.append("Consider adding 'conciseness' to personality traits")
+        if "speed" in content.lower() or "慢" in content:
+            suggestions.append("Consider emphasizing efficiency in work style")
+        
+        return suggestions if suggestions else ["No specific updates suggested at this time"]
+
+
+def main():
+    """CLI entry point."""
+    import argparse
+    
+    parser = argparse.ArgumentParser(description="Self-Improving Agent CLI")
+    parser.add_argument("--log", "-l", help="Log an improvement insight")
+    parser.add_argument("--category", "-c", default="general", help="Category")
+    parser.add_argument("--report", "-r", action="store_true", help="Generate weekly report")
+    parser.add_argument("--stats", "-s", action="store_true", help="Show stats")
+    parser.add_argument("--suggest", action="store_true", help="Suggest SOUL updates")
+    
+    args = parser.parse_args()
+    
+    sia = SelfImprovingAgent()
+    
+    if args.log:
+        sia.log_improvement(args.log, args.category)
+        print(f"✅ Logged: {args.log}")
+    elif args.report:
+        print(sia.generate_weekly_report())
+    elif args.stats:
+        print(json.dumps(sia.get_improvement_stats(), indent=2))
+    elif args.suggest:
+        suggestions = sia.suggest_soul_updates()
+        print("Suggested SOUL.md updates:")
+        for s in suggestions:
+            print(f"  - {s}")
+    else:
+        print("🔄 Self-Improving Agent initialized!")
+        print(f"Stats: {sia.get_improvement_stats()}")
+
+
+if __name__ == "__main__":
+    main()

skill.yaml

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+name: self-improving-agent
+description: Self-improving agent system for continuous optimization
+version: "1.0.0"
+author: xiucheng
+type: skill
+tags:
+  - self-improvement
+  - learning
+  - optimization
+license: MIT