Ryan Malloy
162ca67098
✨ Features: - 🧠 Shadow learner that builds intelligence from command patterns - 🛡️ Smart command validation with safety checks - 💾 Automatic context monitoring and backup system - 🔄 Session continuity across Claude restarts 📚 Documentation: - Complete Diátaxis-organized documentation - Learning-oriented tutorial for getting started - Task-oriented how-to guides for specific problems - Information-oriented reference for quick lookup - Understanding-oriented explanations of architecture 🚀 Installation: - One-command installation script - Bootstrap prompt for installation via Claude - Cross-platform compatibility - Comprehensive testing suite 🎯 Ready for real-world use and community feedback! 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
124 lines
3.6 KiB
Python
Executable File
124 lines
3.6 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Session Logger Hook - PostToolUse[*] hook
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Logs all tool usage and feeds data to shadow learner
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"""
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import sys
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import json
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import os
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from datetime import datetime
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from pathlib import Path
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# Add lib directory to path
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sys.path.insert(0, str(Path(__file__).parent.parent / "lib"))
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from shadow_learner import ShadowLearner
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from session_state import SessionStateManager
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from context_monitor import ContextMonitor
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from models import ToolExecution
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def main():
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"""Main hook entry point"""
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try:
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# Read input from Claude Code
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input_data = json.loads(sys.stdin.read())
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# Extract tool execution data
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tool = input_data.get("tool", "")
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parameters = input_data.get("parameters", {})
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success = input_data.get("success", True)
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error = input_data.get("error", "")
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execution_time = input_data.get("execution_time", 0.0)
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# Create tool execution record
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execution = ToolExecution(
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timestamp=datetime.now(),
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tool=tool,
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parameters=parameters,
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success=success,
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error_message=error if error else None,
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execution_time=execution_time,
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context={}
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)
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# Initialize components
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shadow_learner = ShadowLearner()
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session_manager = SessionStateManager()
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context_monitor = ContextMonitor()
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# Feed execution to shadow learner
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shadow_learner.learn_from_execution(execution)
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# Update session state
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session_manager.update_from_tool_use(input_data)
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# Update context monitor
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context_monitor.update_from_tool_use(input_data)
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# Save learned patterns periodically
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# (Only save every 10 executions to avoid too much disk I/O)
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if context_monitor.tool_executions % 10 == 0:
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shadow_learner.save_database()
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# Log execution to file for debugging (optional)
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log_execution(execution)
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# Always allow - this is a post-execution hook
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response = {
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"allow": True,
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"message": f"Logged {tool} execution"
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}
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print(json.dumps(response))
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sys.exit(0)
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except Exception as e:
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# Post-execution hooks should never block
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response = {
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"allow": True,
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"message": f"Logging error: {str(e)}"
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}
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print(json.dumps(response))
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sys.exit(0)
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def log_execution(execution: ToolExecution):
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"""Log execution to file for debugging and analysis"""
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try:
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log_dir = Path(".claude_hooks/logs")
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log_dir.mkdir(parents=True, exist_ok=True)
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# Create daily log file
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log_file = log_dir / f"executions_{datetime.now().strftime('%Y%m%d')}.jsonl"
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# Append execution record
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with open(log_file, 'a') as f:
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f.write(json.dumps(execution.to_dict()) + "\n")
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# Clean up old log files (keep last 7 days)
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cleanup_old_logs(log_dir)
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except Exception:
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# Don't let logging errors break the hook
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pass
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def cleanup_old_logs(log_dir: Path):
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"""Clean up log files older than 7 days"""
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try:
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import time
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cutoff_time = time.time() - (7 * 24 * 3600) # 7 days ago
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for log_file in log_dir.glob("executions_*.jsonl"):
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if log_file.stat().st_mtime < cutoff_time:
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log_file.unlink()
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except Exception:
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pass
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if __name__ == "__main__":
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main() |