# Claude AI Agent with Skills Architecture

A demonstration of modern AI agent design patterns using Claude API with a modular skills system, persistent memory, and security-first principles.

## 🎯 Purpose

This project showcases:
- **Agentic AI Design**: Modular skill system with progressive disclosure
- **Production Patterns**: Structured prompts, memory management, and error handling
- **Security Best Practices**: Least privilege, context minimization, and input validation
- **Clean Architecture**: Separation of concerns between agent core, skills, and memory

## 🏗️ Architecture

```
agent.py              # Main agent loop with Claude integration
├── prompts/
│   └── system.txt    # System prompt with skill discovery
├── skills/
│   ├── powershell.py # PowerShell execution skill
│   └── examples/
│       ├── SKILL.md      # Skill metadata & instructions
│       ├── reference.md  # Technical reference (loaded on-demand)
│       └── security.md   # Security boundaries
└── memory/
    └── short_term.json   # Conversation history & context
```

## 🚀 Quick Start

1. **Install dependencies:**
   ```bash
   pip install -r requirements.txt
   ```

2. **Configure API key:**
   ```bash
   cp .env.example .env
   # Add your ANTHROPIC_API_KEY to .env
   ```

3. **Run the agent:**
   ```bash
   python agent.py
   ```

## 💡 Key Features

### Modular Skills System
- Skills are self-contained Python modules
- Progressive disclosure: Load detailed context only when needed
- Clear metadata (name, description, parameters)

### Memory Management
- Short-term memory for conversation context
- Persistent storage between sessions
- Automatic memory pruning to stay within token limits

### Security-First Design
- Explicit security boundaries per skill
- Input validation and sanitization
- Audit logging for sensitive operations
- Principle of least privilege

## 📚 Skills Overview

### PowerShell Skill
Execute PowerShell commands with safety guardrails:
- Whitelist of allowed commands
- Output sanitization
- Execution timeout
- Error handling and logging

## 🎓 Learning Outcomes

This project demonstrates:
- ✅ Working with Claude API (Anthropic SDK)
- ✅ Prompt engineering with tool use
- ✅ Modular software architecture
- ✅ Security considerations in AI systems
- ✅ Production-ready error handling
- ✅ Documentation best practices

## 🔒 Security Considerations

- Skills operate with minimal permissions
- No external network access unless explicitly authorized
- All user inputs are validated
- Sensitive data is never logged
- Skills include security.md defining boundaries

## 📝 License

MIT License - Free for learning and demonstration purposes

## 👤 Author

Created as a portfolio demonstration of AI agent architecture and Python best practices.

---

*This is a demonstration project designed to showcase technical skills for potential employers.*
=======
## Security Focus
- Least privilege
- Context minimization
- Trusted content only


## Resources 
- https://platform.claude.com/docs/en/agents-and-tools/agent-skills/overview
>>>>>>> f52fbcd677b74b19ed210fb411f6b1469fba8da5