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🚀 Claude Flow Plugin - Complete Enterprise AI Agent Orchestration
Enterprise-grade AI agent orchestration plugin with 150+ commands, 74+ specialized agents, SPARC methodology, swarm coordination, GitHub integration, and neural training capabilities
📋 Table of Contents
- Overview
- Features
- Quick Start
- Installation
- Components
- Usage
- MCP Integration
- Examples
- Documentation
- Support
🌟 Overview
Claude Flow is the most comprehensive Claude Code plugin for enterprise AI agent orchestration. It provides a complete ecosystem for:
- Multi-Agent Coordination: 74+ specialized agents with swarm intelligence
- SPARC Methodology: Systematic development with 18 specialized modes
- GitHub Automation: 14+ tools for complete repository workflow automation
- Neural Training: 27+ models with WASM acceleration
- 150+ Commands: Complete slash command library for all workflows
- MCP Integration: 110+ tools across 3 MCP servers
✨ Features
🐝 Swarm Coordination
- 4 Topologies: Hierarchical, Mesh, Ring, Star
- Auto-Spawning: Intelligent agent creation based on task complexity
- Auto-Optimization: Dynamic topology adjustment for performance
- 100 Max Agents: Scale to handle enterprise workloads
- Cross-Session Memory: Persistent context and learnings
🎯 SPARC Methodology
- Specification: Requirements analysis and planning
- Pseudocode: Algorithm design and logic flow
- Architecture: System design and component structure
- Refinement: TDD and iterative improvement
- Code: Implementation and optimization
- 18 Specialized Modes: Complete development lifecycle coverage
🐙 GitHub Integration
- PR Management: Automated pull request workflows
- Code Review Swarms: Multi-agent code analysis
- Issue Tracking: Intelligent issue triage and assignment
- Release Automation: Coordinated multi-package releases
- Workflow Automation: Custom GitHub Actions integration
- Multi-Repo Coordination: Cross-repository synchronization
🧠 Neural Training
- 27+ Models: Pre-trained patterns for common tasks
- WASM Acceleration: 2.8-4.4x speed improvement
- SIMD Optimization: Advanced vector processing
- Pattern Learning: Self-improving agent behaviors
- Context Persistence: Cross-session learning retention
🎨 74+ Specialized Agents
Core Development (5)
coder- Code implementation specialistplanner- Strategic planning and roadmapsresearcher- Information gathering and analysisreviewer- Code quality and security reviewtester- Comprehensive test creation
Swarm Coordination (5)
hierarchical-coordinator- Queen-led command structuremesh-coordinator- Peer-to-peer coordinationadaptive-coordinator- Dynamic topology managementcollective-intelligence-coordinator- Distributed decision-makingswarm-memory-manager- Cross-agent memory coordination
Consensus & Fault Tolerance (7)
byzantine-coordinator- Byzantine fault toleranceraft-manager- Raft consensus protocolgossip-coordinator- Gossip-based consensuscrdt-synchronizer- Conflict-free data replicationquorum-manager- Dynamic quorum managementsecurity-manager- Comprehensive security protocolsperformance-benchmarker- Consensus performance testing
GitHub Automation (13)
pr-manager- Pull request coordinationcode-review-swarm- Multi-agent code reviewsissue-tracker- Issue management and triagerelease-manager- Release coordinationworkflow-automation- GitHub Actions managementrepo-architect- Repository structure optimizationmulti-repo-swarm- Cross-repository coordinationsync-coordinator- Version alignment across repos- And 5 more specialized GitHub agents...
Specialized Development (8)
backend-dev- Backend API developmentmobile-dev- React Native mobile developmentml-developer- Machine learning workflowscicd-engineer- CI/CD pipeline creationapi-docs- OpenAPI/Swagger documentationsystem-architect- System design and architecturecode-analyzer- Advanced code quality analysisbase-template-generator- Boilerplate generation
SPARC Methodology (4)
specification- Requirements analysispseudocode- Algorithm designarchitecture- System architecturerefinement- Iterative improvement
And 32 more specialized agents!
📦 150+ Commands
Coordination (6)
/coordination-swarm-init- Initialize swarm with topology/coordination-agent-spawn- Create specialized agents/coordination-task-orchestrate- Coordinate task execution/coordination-spawn- Quick agent spawning/coordination-orchestrate- Advanced orchestration/coordination-init- Setup coordination environment
SPARC Methodology (18)
/sparc-modes- List all SPARC modes/sparc-coder- Clean code implementation/sparc-tdd- Test-driven development/sparc-architect- Architecture design/sparc-reviewer- Code review mode/sparc-tester- Test creation mode/sparc-analyzer- Code analysis/sparc-researcher- Research mode/sparc-optimizer- Performance optimization/sparc-debugger- Debugging assistance/sparc-designer- UI/UX design mode/sparc-documenter- Documentation creation/sparc-innovator- Innovation and R&D/sparc-orchestrator- Workflow orchestration/sparc-batch-executor- Batch operations/sparc-memory-manager- Memory management/sparc-workflow-manager- Workflow management/sparc-swarm-coordinator- Swarm coordination
GitHub Integration (18)
/github-code-review- Automated code reviews/github-code-review-swarm- Multi-agent reviews/github-pr-manager- PR lifecycle management/github-pr-enhance- PR enhancement automation/github-issue-tracker- Issue tracking/github-issue-triage- Intelligent issue triage/github-repo-analyze- Repository analysis/github-repo-architect- Repo structure optimization/github-release-manager- Release coordination/github-release-swarm- Multi-package releases/github-workflow-automation- GitHub Actions automation/github-swarm-pr- PR swarm management/github-swarm-issue- Issue swarm coordination/github-multi-repo-swarm- Cross-repo coordination/github-sync-coordinator- Version synchronization/github-project-board-sync- Project board integration/github-modes- GitHub integration modes/github-swarm- GitHub swarm orchestration
Hive Mind (11)
/hive-mind- Initialize hive mind coordination/hive-mind-init- Setup hive mind topology/hive-mind-spawn- Spawn hive agents/hive-mind-status- Check hive status/hive-mind-consensus- Consensus protocols/hive-mind-memory- Shared memory management/hive-mind-metrics- Performance metrics/hive-mind-sessions- Session management/hive-mind-resume- Resume hive sessions/hive-mind-stop- Stop hive coordination/hive-mind-wizard- Guided setup wizard
Memory Management (5)
/memory-usage- Memory storage and retrieval/memory-persist- Cross-session persistence/memory-search- Pattern-based search/memory-neural- Neural memory integration
Monitoring (5)
/monitoring-status- System status overview/monitoring-agents- Agent status monitoring/monitoring-agent-metrics- Performance metrics/monitoring-swarm-monitor- Real-time swarm monitoring/monitoring-real-time-view- Live dashboard
Optimization (5)
/optimization-topology-optimize- Auto-optimize topology/optimization-auto-topology- Automatic topology selection/optimization-parallel-execution- Parallel task execution/optimization-parallel-execute- Execute tasks in parallel/optimization-cache-manage- Cache management
Analysis (5)
/analysis-performance-report- Performance reports/analysis-performance-bottlenecks- Bottleneck detection/analysis-bottleneck-detect- Real-time bottleneck analysis/analysis-token-usage- Token consumption analysis/analysis-token-efficiency- Token optimization
Automation (6)
/automation-smart-spawn- Intelligent agent spawning/automation-smart-agents- Auto-agent selection/automation-auto-agent- Automated agent management/automation-self-healing- Self-healing workflows/automation-session-memory- Session persistence/automation-workflow-select- Workflow selection
Hooks (7)
/hooks-setup- Configure hooks system/hooks-overview- Hooks documentation/hooks-pre-task- Pre-task hook setup/hooks-post-task- Post-task hook setup/hooks-pre-edit- Pre-edit hook setup/hooks-post-edit- Post-edit hook setup/hooks-session-end- Session end hook setup
Swarm Management (15)
/swarm- Main swarm command/swarm-init- Initialize swarm/swarm-spawn- Spawn swarm agents/swarm-status- Swarm status/swarm-monitor- Real-time monitoring/swarm-modes- Available swarm modes/swarm-strategies- Execution strategies/swarm-background- Background swarm execution/swarm-analysis- Swarm analysis workflows/swarm-research- Research swarms/swarm-development- Development swarms/swarm-testing- Testing swarms/swarm-maintenance- Maintenance swarms/swarm-optimization- Optimization swarms/swarm-examples- Swarm examples
Workflows (5)
/workflows-create- Create custom workflows/workflows-execute- Execute workflows/workflows-export- Export workflow definitions/workflows-development- Development workflows/workflows-research- Research workflows
Neural Training (5)
/training-neural-train- Train neural patterns/training-neural-patterns- Pattern management/training-pattern-learn- Pattern learning/training-model-update- Model updates/training-specialization- Agent specialization
Flow Nexus (9)
/flow-nexus-swarm- Cloud swarm orchestration/flow-nexus-workflow- Event-driven workflows/flow-nexus-neural-network- Distributed neural training/flow-nexus-sandbox- E2B sandbox management/flow-nexus-app-store- Application marketplace/flow-nexus-challenges- Coding challenges/flow-nexus-payments- Credit management/flow-nexus-user-tools- User management/flow-nexus-login- Authentication
And 50+ more commands!
🚀 Quick Start
1. Install Claude Code Plugin
In Claude Code:
/plugin add ruvnet/claude-flow
Or from local directory:
git clone https://github.com/ruvnet/claude-flow.git
cd claude-flow
Then in Claude Code:
/plugin add .
2. Restart Claude Code
/restart
3. Configure MCP Servers (Optional)
# Add MCP servers to Claude Code
claude mcp add claude-flow npx claude-flow@alpha mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start # Optional
claude mcp add flow-nexus npx flow-nexus@latest mcp start # Optional
4. Verify Installation
# Check plugin status
claude plugin list
# Test a command
# In Claude Code, type:
/coordination-swarm-init
📦 Installation
Prerequisites
- Claude Code CLI >= 2.0.0
- Node.js >= 20.0.0
- Git (for GitHub integration features)
- Read/write permissions in project directory
Method 1: Direct Installation (Recommended)
In Claude Code:
/plugin add ruvnet/claude-flow
/restart
Method 2: Local Installation
# Clone the repository
git clone https://github.com/ruvnet/claude-flow.git
cd claude-flow/claude-plugin
# Run installation script
bash scripts/install.sh
# Or copy manually
cp -r commands ~/.claude/commands/
cp -r agents ~/.claude/agents/
Method 3: NPX (One-Time Setup)
# Run setup via npx
npx claude-flow@alpha init --plugin
# This will:
# 1. Create .claude directory
# 2. Copy all commands and agents
# 3. Configure MCP servers
# 4. Setup hooks
🏗️ Components
Directory Structure
claude-flow/
├── .claude-plugin/
│ ├── plugin.json # Plugin metadata
│ ├── README.md # This file
│ └── ...
├── commands/ # 150+ slash commands
│ ├── coordination/ # Swarm coordination commands
│ ├── sparc/ # SPARC methodology commands
│ ├── github/ # GitHub integration commands
│ ├── hive-mind/ # Hive mind commands
│ ├── hooks/ # Hooks configuration commands
│ ├── memory/ # Memory management commands
│ ├── monitoring/ # Monitoring commands
│ ├── optimization/ # Optimization commands
│ ├── analysis/ # Analysis commands
│ ├── automation/ # Automation commands
│ ├── swarm/ # Swarm management commands
│ ├── workflows/ # Workflow commands
│ ├── training/ # Neural training commands
│ ├── flow-nexus/ # Flow Nexus integration
│ └── ... # And more!
├── agents/ # 74+ specialized agents
│ ├── core/ # Core development agents
│ ├── consensus/ # Consensus protocol agents
│ ├── github/ # GitHub automation agents
│ ├── swarm/ # Swarm coordination agents
│ ├── hive-mind/ # Hive mind agents
│ ├── sparc/ # SPARC methodology agents
│ ├── optimization/ # Optimization agents
│ ├── specialized/ # Domain-specific agents
│ ├── templates/ # Template agents
│ ├── testing/ # Testing agents
│ └── ... # And more!
├── hooks/ # Hook scripts
│ ├── pre-tool-use.sh
│ ├── post-tool-use.sh
│ ├── pre-task.sh
│ ├── post-task.sh
│ ├── session-start.sh
│ └── session-end.sh
├── scripts/ # Installation and setup scripts
│ ├── install.sh
│ ├── setup-mcp.sh
│ ├── verify.sh
│ └── uninstall.sh
└── docs/ # Documentation
├── QUICKSTART.md
├── USER_GUIDE.md
├── API_REFERENCE.md
├── EXAMPLES.md
└── TROUBLESHOOTING.md
💡 Usage
Basic Swarm Coordination
# Initialize a hierarchical swarm
/coordination-swarm-init
# Spawn specialized agents
/coordination-agent-spawn
# Orchestrate a complex task
/coordination-task-orchestrate "Build REST API with authentication"
SPARC Development Workflow
# Start with specification
/sparc-modes specification "User authentication system"
# Design architecture
/sparc-architect
# Implement with TDD
/sparc-tdd "Implement JWT authentication"
# Code review
/sparc-reviewer
# Optimize performance
/sparc-optimizer
GitHub Automation
# Analyze repository
/github-repo-analyze
# Create PR with automated review
/github-pr-manager
# Multi-agent code review
/github-code-review-swarm
# Coordinate release across repos
/github-multi-repo-swarm
Hive Mind Coordination
# Initialize hive mind
/hive-mind-init
# Spawn hive agents with consensus
/hive-mind-spawn
# Check consensus status
/hive-mind-consensus
# View shared memory
/hive-mind-memory
🔌 MCP Integration
Claude Flow integrates with 3 MCP servers providing 110+ tools:
Claude Flow MCP (Required)
{
"mcpServers": {
"claude-flow": {
"command": "npx",
"args": ["claude-flow@alpha", "mcp", "start"]
}
}
}
Tools: 40+ orchestration tools
- Swarm initialization and management
- Agent spawning and coordination
- Task orchestration
- Memory management
- Neural training
- Performance monitoring
ruv-swarm MCP (Optional)
{
"mcpServers": {
"ruv-swarm": {
"command": "npx",
"args": ["ruv-swarm", "mcp", "start"]
}
}
}
Tools: Enhanced coordination features
- WASM acceleration (2.8-4.4x speed)
- SIMD optimization
- Advanced topology management
- Byzantine fault tolerance
Flow Nexus MCP (Optional - Requires Auth)
{
"mcpServers": {
"flow-nexus": {
"command": "npx",
"args": ["flow-nexus@latest", "mcp", "start"]
}
}
}
Tools: 70+ cloud features
- E2B sandbox execution
- Distributed neural training
- Event-driven workflows
- Application marketplace
- Real-time collaboration
📚 Examples
Example 1: Full-Stack Development with Swarm
# Initialize hierarchical swarm
/coordination-swarm-init
# The swarm automatically spawns:
# - backend-dev agent
# - coder agent for frontend
# - tester agent
# - reviewer agent
# Orchestrate the full-stack build
/coordination-task-orchestrate "Build a todo app with React frontend and Express backend"
# Monitor progress
/monitoring-swarm-monitor
# Get performance metrics
/analysis-performance-report
Example 2: SPARC TDD Workflow
# Start with specification
/sparc-modes specification "Shopping cart with inventory management"
# Generate pseudocode
/sparc-modes pseudocode
# Design architecture
/sparc-architect
# TDD implementation
/sparc-tdd
# Automated review
/sparc-reviewer
# Performance optimization
/sparc-optimizer
Example 3: GitHub PR Automation
# Analyze current PR
/github-pr-manager
# Multi-agent code review
/github-code-review-swarm
# Auto-fix issues
/github-pr-enhance
# Sync across repositories
/github-sync-coordinator
# Prepare release
/github-release-manager
📖 Documentation
- Quickstart Guide - Get started in 5 minutes
- User Guide - Complete usage documentation
- API Reference - All commands and agents
- Examples - Real-world usage examples
- Troubleshooting - Common issues and solutions
🤝 Support
- Documentation: GitHub Wiki
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Website: Flow Nexus
📊 Performance
- 84.8% SWE-Bench solve rate
- 32.3% token reduction vs. sequential execution
- 2.8-4.4x speed improvement with WASM acceleration
- 27+ neural models for pattern recognition
- 100 max concurrent agents
🔧 Advanced Configuration
Custom Swarm Topology
{
"swarmCoordination": {
"topology": "mesh",
"maxAgents": 50,
"autoSpawn": true,
"autoOptimize": true
}
}
Enable Neural Training
{
"neuralTraining": {
"enabled": true,
"wasmAcceleration": true,
"simdOptimization": true
}
}
Configure Hooks
{
"hooks": {
"PreToolUse": { "enabled": true },
"PostToolUse": { "enabled": true },
"SessionEnd": { "enabled": true }
}
}
📝 License
MIT License - see LICENSE file for details
🌟 Star History
Made with ❤️ by rUv
Enterprise AI Agent Orchestration for Claude Code