Claude-Force Documentation — claude-force 2.2.0 documentation

# Claude-Force Documentation

Production-Ready Multi-Agent Orchestration System for Claude

Welcome to the comprehensive documentation for claude-force, a powerful framework for orchestrating multiple Claude AI agents to solve complex software engineering tasks.

## Quick Links

- Installation Guide - Get started in 30 seconds

- Quick Start - Build your first multi-agent workflow

- API Reference - Complete API documentation

- Guides - In-depth tutorials and best practices

- Examples - Real-world usage examples

## What is Claude-Force?

Claude-Force is a Python framework that enables you to:

- Orchestrate Multiple AI Agents: Coordinate specialized Claude agents for different tasks

- Semantic Agent Selection: Automatically recommend the best agent for your task using embeddings

- Hybrid Model Orchestration: Optimize costs by automatically selecting Haiku/Sonnet/Opus based on task complexity

- Performance Tracking: Monitor execution time, token usage, and costs

- Workflow Composition: Create custom multi-agent workflows

- Marketplace Integration: Install and share community agents

## Key Features

### 🧠 Semantic Agent Recommendation

    claude-force recommend --task "Review authentication code for security"
    # → Recommends: security-specialist (confidence: 0.92)

### ⚡ Hybrid Model Orchestration

Automatically selects the optimal Claude model based on task complexity:

- Haiku for simple tasks (typo fixes, formatting)

- Sonnet for moderate tasks (code reviews, refactoring)

- Opus for complex tasks (architecture design, security audits)

### 📊 Performance Analytics

    claude-force analyze performance
    # Shows: execution times, token usage, costs, success rates

### 🎨 Project Initialization

    claude-force init ./my-project \
      --description "Build a chat application" \
      --name "chat-app"
    # Creates optimized .claude/ configuration

## Installation

### From PyPI (Recommended)

    pip install claude-force
    claude-force --help

### From Source

    git clone https://github.com/khanh-vu/claude-force.git
    cd claude-force
    pip install -e .

## Quick Example

    from claude_force.orchestrator import AgentOrchestrator

    # Initialize orchestrator
    orchestrator = AgentOrchestrator(
        config_path=".claude/claude.json",
        enable_tracking=True
    )

    # Run single agent
    result = orchestrator.run_agent(
        agent_name="code-reviewer",
        task="Review this authentication function for security issues"
    )

    print(result.output)

    # Run multi-agent workflow
    results = orchestrator.run_workflow(
        workflow_name="full-stack-feature",
        task="Implement user authentication with JWT"
    )

    for result in results:
        print(f"{result.agent_name}: {result.success}")

## Architecture

Claude-Force consists of several key components:

- AgentOrchestrator: Core execution engine

- SemanticAgentSelector: AI-powered agent recommendation

- HybridOrchestrator: Model selection and cost optimization

- PerformanceTracker: Metrics collection and analytics

- WorkflowComposer: Custom workflow creation

- AgentMarketplace: Community agent sharing

## Documentation Sections

### For Users

- Installation: System requirements and installation methods

- Quick Start: Get started in minutes

- CLI Reference: All command-line commands

- Guides: Tutorials and best practices

### For Developers

- API Reference: Complete Python API documentation

- Architecture: System design and internals

- Contributing: How to contribute to claude-force

- Testing: Running and writing tests

### Advanced Topics

- Semantic Selection: How agent recommendation works

- Performance Optimization: Cost and latency optimization

- Custom Workflows: Building multi-agent workflows

- Marketplace: Publishing and installing agents

## System Requirements

- Python 3.8 or higher (3.10+ recommended)

- Anthropic API key (Get one here)

- 100MB disk space

### Optional Dependencies

- `sentence-transformers`: For semantic agent selection (recommended)

- `numpy`: For vector operations (required if using semantic selection)

## Support

- GitHub Issues: https://github.com/khanh-vu/claude-force/issues

- Documentation: https://claude-force.readthedocs.io

- Source Code: https://github.com/khanh-vu/claude-force

## License

MIT License - see LICENSE file for details.

## Next Steps

- New Users: Start with the Quick Start Guide

- Developers: Check out the API Reference

- Advanced Users: Explore Guides for in-depth topics

Version: 2.1.0 Last Updated: 2025-11-14 Status: Production Ready