Claude-Flow v3: Enterprise AI Orchestration Platform

Overview

Claude-Flow is a comprehensive AI agent orchestration framework that transforms Claude Code into a powerful multi-agent development platform. It enables teams to deploy, coordinate, and optimize specialized AI agents working together on complex software engineering tasks.

$3

| Capability | Claude Code Alone | Claude Code + Claude-Flow |
|------------|-------------------|---------------------------|
| Agent Collaboration | Agents work in isolation, no shared context | Agents collaborate via swarms with shared memory and consensus |
| Coordination | Manual orchestration between tasks | Queen-led hierarchy with 5 consensus algorithms (Raft, Byzantine, Gossip) |
| Memory | Session-only, no persistence | HNSW vector memory with 150x-12,500x faster retrieval |
| Learning | Static behavior, no adaptation | SONA self-learning with <0.05ms adaptation, improves over time |
| Task Routing | You decide which agent to use | Intelligent routing based on learned patterns (89% accuracy) |
| Complex Tasks | Manual breakdown required | Automatic decomposition across 5 domains (Security, Core, Integration, Support) |
| Background Workers | Nothing runs automatically | 12 context-triggered workers auto-dispatch on file changes, patterns, sessions |
| LLM Provider | Anthropic only | 6 providers with automatic failover and cost-based routing (85% savings) |
| Security | Standard protections | CVE-hardened with bcrypt, input validation, path traversal prevention |
| Performance | Baseline | 2.8-4.4x faster tasks, 4-32x memory reduction via quantization |

$3

- 54+ Specialized Agents - Ready-to-use AI agents for coding, code review, testing, security audits, documentation, and DevOps tasks. Each agent is optimized for its specific role.

- Coordinated Agent Teams - Run unlimited agents simultaneously in organized swarms. Agents can spawn sub-workers, communicate, share context, and divide work automatically using patterns like hierarchical (queen/workers) or mesh (peer-to-peer).

- Learns From Your Workflow - The system remembers what works. Successful patterns are stored and reused, routing similar tasks to the best-performing agents. Gets smarter over time.

- Works With Any LLM - Switch between Claude, GPT-4, Gemini, Cohere, or local models like Llama. Automatic failover if one provider is unavailable. Smart routing picks the cheapest option that meets quality requirements.

- Plugs Into Claude Code - Native integration via MCP (Model Context Protocol). Use claude-flow commands directly in your Claude Code sessions with full tool access.

- Production-Ready Security - Built-in protection against common vulnerabilities: input validation, path traversal prevention, command injection blocking, and safe credential handling.

---

Quick Start

$3

- Node.js 18+ or Bun 1.0+ (Bun is faster)
- npm 9+ / pnpm / bun package manager

IMPORTANT: Claude Code must be installed first:

``bash


1. Install Claude Code globally

npm install -g @anthropic-ai/claude-code

2. (Optional) Skip permissions check for faster setup

claude --dangerously-skip-permissions
`

$3

`bash


With npm/npx (Node.js)

npm install claude-flow@v3alpha
npx claude-flow@v3alpha init

With Bun (faster)

bun add claude-flow@v3alpha
bunx claude-flow@v3alpha init

Start MCP server for Claude Code integration

npx claude-flow@v3alpha mcp start

Run a task with agents

npx claude-flow@v3alpha --agent coder --task "Implement user authentication"

List available agents

npx claude-flow@v3alpha --list
`

---

Features

$3

| Capability | Description | Metrics |
|------------|-------------|---------|
| 54+ Specialized Agents | Purpose-built AI agents for development, testing, security, and operations | 10 categories, unlimited concurrent |
| Multi-Topology Swarms | Hierarchical, mesh, ring, star, and adaptive coordination patterns | 2.8-4.4x speed improvement |
| Self-Learning Hooks | ReasoningBank pattern learning with HNSW vector search | 150x faster retrieval |
| MCP Integration | Native Claude Code support via Model Context Protocol | 27+ tools available |
| Security-First Design | Input validation, path traversal prevention, command sandboxing | CVE-1, CVE-2, CVE-3 addressed |
| Cross-Platform | Full support for Windows, macOS, and Linux environments | Node.js 18+ |

$3

| Category | Agent Count | Key Agents | Purpose |
|----------|-------------|------------|---------|
| Core Development | 5 | coder, reviewer, tester, planner, researcher | Daily development tasks |
| V3 Specialized | 10 | queen-coordinator, security-architect, memory-specialist | Enterprise orchestration |
| Swarm Coordination | 5 | hierarchical-coordinator, mesh-coordinator, adaptive-coordinator | Multi-agent patterns |
| Consensus & Distributed | 7 | byzantine-coordinator, raft-manager, gossip-coordinator | Fault-tolerant coordination |
| Performance | 5 | perf-analyzer, performance-benchmarker, task-orchestrator | Optimization & monitoring |
| GitHub & Repository | 9 | pr-manager, code-review-swarm, issue-tracker, release-manager | Repository automation |
| SPARC Methodology | 6 | sparc-coord, specification, pseudocode, architecture | Structured development |
| Specialized Dev | 8 | backend-dev, mobile-dev, ml-developer, cicd-engineer | Domain expertise |

$3

| Topology | Recommended Agents | Best For | Execution Time | Memory/Agent |
|----------|-------------------|----------|----------------|--------------|
| Hierarchical | 6+ | Structured tasks, clear authority chains | 0.20s | 256 MB |
| Mesh | 4+ | Collaborative work, high redundancy | 0.15s | 192 MB |
| Ring | 3+ | Sequential processing pipelines | 0.12s | 128 MB |
| Star | 5+ | Centralized control, spoke workers | 0.14s | 180 MB |
| Hybrid (Hierarchical-Mesh) | 7+ | Complex multi-domain tasks | 0.18s | 320 MB |
| Adaptive | 2+ | Dynamic workloads, auto-scaling | Variable | Dynamic |

$3

| Feature | Technology | Performance | Description |
|---------|------------|-------------|-------------|
| ReasoningBank | HNSW Vector Search | 150x faster | Pattern storage with similarity-based retrieval |
| SONA Neural | LoRA Fine-tuning | <0.05ms adaptation | Self-optimizing neural architecture |
| Pattern Learning | EWC++ Memory | Zero forgetting | Continuous learning without catastrophic forgetting |
| Intent Routing | MoE (Mixture of Experts) | 95%+ accuracy | Intelligent task-to-agent routing |
| Domain Detection | Vector Clustering | Real-time | Automatic categorization (security, testing, performance) |
| Quality Tracking | Success/Failure Metrics | Per-pattern | Historical performance tracking |

$3

| Backend | Technology | Performance | Use Case |
|---------|------------|-------------|----------|
| AgentDB | HNSW Indexing | 150x-12,500x faster | Primary vector storage |
| SQLite | Relational DB | Standard | Metadata and structured data |
| Hybrid | AgentDB + SQLite | Best of both | Recommended default |
| In-Memory | RAM-based | Fastest | Temporary/session data |

$3

| Category | Tools | Description |
|----------|-------|-------------|
| Coordination | swarm_init, agent_spawn, task_orchestrate | Swarm and agent lifecycle management |
| Monitoring | swarm_status, agent_list, agent_metrics, task_status | Real-time status and metrics |
| Memory & Neural | memory_usage, neural_status, neural_train, neural_patterns | Memory operations and learning |
| GitHub | github_swarm, repo_analyze, pr_enhance, issue_triage, code_review | Repository integration |
| Workers | worker/run, worker/status, worker/alerts, worker/history | Background task management |
| Hooks | hooks/pre-, hooks/post-, hooks/route, hooks/session-, hooks/intelligence/, hooks/worker/* | 31 lifecycle hooks |

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| Feature | Protection | Implementation |
|---------|------------|----------------|
| Input Validation | Injection attacks | Boundary validation on all inputs |
| Path Traversal Prevention | Directory escape | Blocked patterns (../, ~/., /etc/) |
| Command Sandboxing | Shell injection | Allowlisted commands, metacharacter blocking |
| Prototype Pollution | Object manipulation | Safe JSON parsing with validation |
| TOCTOU Protection | Race conditions | Symlink skipping and atomic operations |
| Information Disclosure | Data leakage | Error message sanitization |
| CVE Monitoring | Known vulnerabilities | Active scanning and patching |

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| Feature | Description | Benefit |
|---------|-------------|---------|
| Automatic Topology Selection | AI-driven topology choice based on task complexity | Optimal resource utilization |
| Parallel Execution | Concurrent agent operation with load balancing | 2.8-4.4x speed improvement |
| Neural Training | 27+ model support with continuous learning | Adaptive intelligence |
| Bottleneck Analysis | Real-time performance monitoring and optimization | Proactive issue detection |
| Smart Auto-Spawning | Dynamic agent creation based on workload | Elastic scaling |
| Self-Healing Workflows | Automatic error recovery and task retry | High availability |
| Cross-Session Memory | Persistent pattern storage across sessions | Continuous learning |
| Event Sourcing | Complete audit trail with replay capability | Debugging and compliance |
| Background Workers | 12 auto-triggered workers for analysis and optimization | Automated maintenance |
| GitHub Integration | PR management, issue triage, code review automation | Repository workflow |

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| Component | Description | Key Features |
|-----------|-------------|--------------|
| PluginBuilder | Fluent builder for creating plugins | MCP tools, hooks, workers, providers |
| MCPToolBuilder | Build MCP tools with typed parameters | String, number, boolean, enum params |
| HookBuilder | Build hooks with conditions and transformers | Priorities, conditional execution, data transformation |
| WorkerPool | Managed worker pool with auto-scaling | Min/max workers, task queuing, graceful shutdown |
| ProviderRegistry | LLM provider management with fallback | Cost optimization, automatic failover |
| AgenticFlowBridge | agentic-flow@alpha integration | Swarm coordination, agent spawning |
| AgentDBBridge | Vector storage with HNSW indexing | 150x faster search, batch operations |
| Security Utilities | Input validation and protection | Path traversal, injection, rate limiting |

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| Category | Events | Description |
|----------|--------|-------------|
| Session | session:start, session:end | Session lifecycle management |
| Agent | agent:pre-spawn, agent:post-spawn, agent:pre-terminate, agent:post-terminate | Agent lifecycle hooks |
| Task | task:pre-execute, task:post-complete, task:error | Task execution hooks |
| Tool | tool:pre-call, tool:post-call | MCP tool invocation hooks |
| Memory | memory:pre-store, memory:post-store, memory:pre-retrieve, memory:post-retrieve | Memory operation hooks |
| Swarm | swarm:initialized, swarm:shutdown, swarm:consensus-reached | Swarm coordination hooks |
| File | file:pre-read, file:post-read, file:pre-write, file:post-write | File operation hooks |
| Command | command:pre-execute, command:post-execute | Shell command hooks |
| Learning | learning:pattern-learned, learning:pattern-applied | Pattern learning hooks |

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| Worker Type | Purpose | Capabilities |
|-------------|---------|--------------|
| coder | Code implementation | Code generation, refactoring |
| reviewer | Code review | Quality analysis, suggestions |
| tester | Test generation/execution | Unit tests, integration tests |
| researcher | Information gathering | Web search, documentation |
| planner | Task planning | Decomposition, scheduling |
| coordinator | Multi-agent coordination | Orchestration, consensus |
| security | Security analysis | Vulnerability scanning, audit |
| performance | Performance optimization | Profiling, benchmarking |
| specialized | Custom capabilities | Domain-specific tasks |
| long-running | Background tasks | Async processing, polling |

$3

| Metric | Target | Achieved |
|--------|--------|----------|
| Plugin load time | <50ms | ~20ms |
| Hook execution | <1ms | ~0.5ms |
| Worker spawn | <100ms | ~50ms |
| Vector search (10K) | <10ms | ~5ms |

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| Plugin | Description | Performance |
|--------|-------------|-------------|
| SemanticCodeSearchPlugin | Semantic code search with vector embeddings | Real-time indexing |
| IntentRouterPlugin | Routes user intents to optimal handlers | 95%+ accuracy |
| HookPatternLibraryPlugin | Pre-built patterns for common tasks | Security, testing, performance |
| MCPToolOptimizerPlugin | Optimizes MCP tool selection | Context-aware suggestions |
| ReasoningBankPlugin | Vector-backed pattern storage with HNSW | 150x faster search |
| AgentConfigGeneratorPlugin | Generates optimized agent configurations | From pretrain data |

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Workers run automatically in the background based on context, or can be dispatched manually via MCP tools.

| Worker | Trigger | Purpose | Auto-Triggers On |
|--------|---------|---------|------------------|
| UltraLearn | ultralearn | Deep knowledge acquisition from codebase | New project, major refactors |
| Optimize | optimize | Performance optimization suggestions | Slow operations detected |
| Consolidate | consolidate | Memory pattern consolidation | Session end, memory threshold |
| Predict | predict | Predictive resource preloading | Usage patterns detected |
| Audit | audit | Security vulnerability analysis | Security-related file changes |
| Map | map | Codebase structure mapping | New directories, large changes |
| Preload | preload | Resource and dependency preloading | Project initialization |
| DeepDive | deepdive | Deep code analysis and understanding | Complex file edits |
| Document | document | Auto-documentation generation | New functions/classes created |
| Refactor | refactor | Refactoring opportunity detection | Code smell patterns |
| Benchmark | benchmark | Performance benchmarking | Performance-critical changes |
| TestGaps | testgaps | Test coverage gap analysis | Code changes without tests |

Worker Commands:
`bash


Dispatch a worker manually

npx claude-flow@v3alpha worker dispatch --trigger audit --context "./src"

Check worker status

npx claude-flow@v3alpha worker status

View completed results

npx claude-flow@v3alpha worker results --limit 10
`

$3

| Provider | Models | Features | Cost |
|----------|--------|----------|------|
| Anthropic | Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku | Native, streaming, tool calling | $3-15/1M tokens |
| OpenAI | GPT-4o, GPT-4 Turbo, GPT-3.5, o1-preview, o3-mini | Function calling, vision | $0.50-60/1M tokens |
| Google | Gemini 2.0 Flash, Gemini 1.5 Pro/Flash | Multimodal, long context | $0.075-7/1M tokens |
| Cohere | Command R+, Command R, Command Light | RAG optimized | $0.50-15/1M tokens |
| Ollama | Llama 3.2, Mistral, CodeLlama, DeepSeek | Local, free, offline | Free |
| RuVector | Custom models via @ruvector/ruvllm | WASM optimized | Custom |

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| Strategy | Description | Best For |
|----------|-------------|----------|
| round-robin | Rotate through providers sequentially | Even distribution |
| least-loaded | Use provider with lowest current load | High throughput |
| latency-based | Use fastest responding provider | Low latency |
| cost-based | Use cheapest provider that meets requirements | Cost optimization (85%+ savings) |

$3

| Provider | Models | Dimensions | Latency | Cost |
|----------|--------|------------|---------|------|
| OpenAI | text-embedding-3-small/large, ada-002 | 1536-3072 | ~50-100ms | $0.02-0.13/1M tokens |
| Transformers.js | all-MiniLM-L6-v2, all-mpnet-base-v2, bge-small | 384-768 | ~20-50ms | Free (local) |
| Mock | Deterministic hash-based | Configurable | <1ms | Free |

$3

| Feature | Description | Performance |
|---------|-------------|-------------|
| LRU Caching | Intelligent cache with hit rate tracking | <1ms cache hits |
| Batch Processing | Efficient batch embedding with partial cache | 10 items <500ms |
| Similarity Functions | Cosine, Euclidean, Dot product | Optimized math |
| Event System | Observable operations with listeners | Real-time monitoring |

$3

| Strategy | Algorithm | Fault Tolerance | Latency | Best For |
|----------|-----------|-----------------|---------|----------|
| Byzantine (PBFT) | Practical Byzantine Fault Tolerance | f < n/3 faulty nodes | ~100ms | Adversarial environments |
| Raft | Leader-based log replication | f < n/2 failures | ~50ms | Strong consistency |
| Gossip | Epidemic protocol dissemination | High partition tolerance | ~200ms | Eventually consistent |
| CRDT | Conflict-free Replicated Data Types | Strong eventual consistency | ~10ms | Concurrent updates |
| Quorum | Configurable read/write quorums | Flexible | ~75ms | Tunable consistency |

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| Command | Subcommands | Description |
|---------|-------------|-------------|
| init | 4 | Project initialization (wizard, check, skills, hooks) |
| agent | 8 | Agent lifecycle (spawn, list, status, stop, metrics, pool, health, logs) |
| swarm | 6 | Swarm coordination (init, start, status, stop, scale, coordinate) |
| memory | 11 | Memory operations (store, retrieve, search, list, delete, stats, configure, cleanup, compress, export, import) |
| mcp | 9 | MCP server (start, stop, status, health, restart, tools, toggle, exec, logs) |
| task | 6 | Task management (create, list, status, cancel, assign, retry) |
| session | 7 | Session management (list, save, restore, delete, export, import, current) |
| config | 7 | Configuration (init, get, set, providers, reset, export, import) |
| status | 3 | System status with watch mode (agents, tasks, memory) |
| workflow | 6 | Workflow execution (run, validate, list, status, stop, template) |
| hooks | 31 | Self-learning hooks (pre/post-edit, pre/post-command, route, explain, pretrain, session-, intelligence/, worker/*) |
| hive-mind | 6 | Queen-led coordination (init, spawn, status, task, optimize-memory, shutdown) |
| migrate | 5 | V2→V3 migration (status, run, verify, rollback, breaking) |

$3

| Component | Description | Features |
|-----------|-------------|----------|
| London School TDD | Behavior verification with mocks | Mock-first, interaction testing |
| Vitest Integration | ADR-008 compliant test runner | 10x faster than Jest |
| Fixture Library | Pre-defined test data | Agents, memory, swarm, MCP |
| Mock Factory | Application and service mocks | Auto-reset, state tracking |
| Async Utilities | waitFor, retry, withTimeout | Reliable async testing |
| Performance Assertions | V3 target validation | Speedup, memory, latency checks |

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| Fixture Type | Contents | Use Case |
|--------------|----------|----------|
| agentConfigs | 15 V3 agent configurations | Agent testing |
| memoryEntries | Patterns, rules, embeddings | Memory testing |
| swarmConfigs | V3 default, minimal, mesh, hierarchical | Swarm testing |
| mcpTools | 27+ tool definitions | MCP testing |

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| Feature | Description | Automation |
|---------|-------------|------------|
| Version Bumping | major, minor, patch, prerelease | Automatic semver |
| Changelog Generation | Conventional commits parsing | Auto-generated |
| Git Integration | Tagging, committing | Automatic |
| NPM Publishing | alpha, beta, rc, latest tags | Tag-based |
| Validation | Lint, test, build, dependency checks | Pre-release |
| Dry Run Mode | Test releases without changes | Safe testing |

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| Channel | Version Format | Purpose |
|---------|---------------|---------|
| alpha | 1.0.0-alpha.1 | Early development |
| beta | 1.0.0-beta.1 | Feature complete, testing |
| rc | 1.0.0-rc.1 | Release candidate |
| latest | 1.0.0 | Stable production |

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| Component | Description | Performance |
|-----------|-------------|-------------|
| AgenticFlowBridge | agentic-flow@alpha integration | ADR-001 compliant |
| SONA Adapter | Learning system integration | <0.05ms adaptation |
| Flash Attention | Attention mechanism coordinator | 2.49x-7.47x speedup |
| SDK Bridge | Version negotiation, API compatibility | Auto-detection |
| Feature Flags | Dynamic feature management | 9 configurable flags |
| Runtime Detection | NAPI, WASM, JS auto-selection | Optimal performance |

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| Runtime | Performance | Requirements |
|---------|-------------|--------------|
| NAPI | Optimal | Native bindings, x64 |
| WASM | Good | WebAssembly support |
| JS | Fallback | Always available |

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| Capability | Description | Output |
|------------|-------------|--------|
| Statistical Analysis | Mean, median, P95, P99, stddev | Comprehensive metrics |
| Memory Tracking | Heap, RSS, external, array buffers | Resource monitoring |
| Auto-Calibration | Automatic iteration adjustment | Statistical significance |
| Regression Detection | Baseline comparison | Change detection |
| V3 Target Validation | Built-in performance targets | Pass/fail checking |

$3

| Category | Benchmark | Target |
|----------|-----------|--------|
| Startup | CLI cold start | <500ms |
| Startup | MCP server init | <400ms |
| Startup | Agent spawn | <200ms |
| Memory | Vector search | <1ms |
| Memory | HNSW indexing | <10ms |
| Memory | Memory write | <5ms |
| Swarm | Agent coordination | <50ms |
| Swarm | Consensus latency | <100ms |
| Neural | SONA adaptation | <0.05ms |

$3

| Feature | Description | Performance |
|---------|-------------|-------------|
| SONA Learning | Self-Optimizing Neural Architecture | <0.05ms adaptation |
| 5 Learning Modes | real-time, balanced, research, edge, batch | Mode-specific optimization |
| 9 RL Algorithms | PPO, A2C, DQN, Q-Learning, SARSA, Decision Transformer, etc. | Comprehensive RL |
| LoRA Integration | Low-Rank Adaptation for efficient fine-tuning | Minimal memory overhead |
| MicroLoRA | Ultra-lightweight LoRA for edge/real-time modes | <5MB memory footprint |
| EWC++ Memory | Elastic Weight Consolidation prevents catastrophic forgetting | Zero knowledge loss |
| Trajectory Tracking | Execution path recording for pattern extraction | Continuous learning |

$3

| Feature | Description | Improvement |
|---------|-------------|-------------|
| Scalar Quantization | Reduce vector precision for memory savings | 4x memory reduction |
| Product Quantization | Compress vectors into codebooks | 8-32x memory reduction |
| HNSW Indexing | Hierarchical Navigable Small World graphs | 150x-12,500x faster search |
| LRU Caching | Intelligent embedding cache with TTL | <1ms cache hits |
| Batch Processing | Process multiple embeddings in single call | 10x throughput |
| Memory Compression | Pattern distillation and pruning | 50-75% reduction |

$3

| Feature | Description | Performance |
|---------|-------------|-------------|
| Multi-Provider | OpenAI, Transformers.js (local), Mock | Flexible deployment |
| Dimensions | 384 to 3072 configurable | Quality vs speed tradeoff |
| Similarity Metrics | Cosine, Euclidean, Dot product | Task-specific matching |
| Event System | Observable operations with listeners | Real-time monitoring |
| Partial Cache Hits | Batch requests use cached where available | Reduced API calls |

$3

| Mode | Adaptation | Quality | Memory | Use Case |
|------|------------|---------|--------|----------|
| real-time | <0.5ms | 70%+ | 25MB | Production, low-latency |
| balanced | <18ms | 75%+ | 50MB | General purpose |
| research | <100ms | 95%+ | 100MB | Deep exploration |
| edge | <1ms | 80%+ | 5MB | Resource-constrained |
| batch | <50ms | 85%+ | 75MB | High-throughput |

$3

| Algorithm | Type | Best For |
|-----------|------|----------|
| PPO | Policy Gradient | Stable continuous learning |
| A2C | Actor-Critic | Balanced exploration/exploitation |
| DQN | Value-based | Discrete action spaces |
| Q-Learning | Tabular | Simple state spaces |
| SARSA | On-policy | Online learning |
| Decision Transformer | Sequence modeling | Long-horizon planning |

$3

| Feature | Description | Capability |
|---------|-------------|------------|
| Queen-Led Topology | Hierarchical command structure | Unlimited agents + sub-workers |
| Byzantine Consensus | Fault-tolerant agreement | f < n/3 tolerance |
| Collective Memory | Shared pattern storage | Distillation, compression |
| Specialist Spawning | Domain-specific agents | Security, performance, etc. |
| Adaptive Topology | Dynamic structure changes | Load-based optimization |

$3

| Feature | Description | Benefit |
|---------|-------------|---------|
| ADR-001 Compliance | Build on agentic-flow, don't duplicate | Eliminates 10,000+ duplicate lines |
| Core Foundation | Use agentic-flow as the base layer | Unified architecture |
| SONA Integration | Seamless learning system connection | <0.05ms adaptation |
| Flash Attention | Optimized attention mechanisms | 2.49x-7.47x speedup |
| AgentDB Bridge | Vector storage integration | 150x-12,500x faster search |
| Feature Flags | Dynamic capability management | 9 configurable features |
| Runtime Detection | NAPI/WASM/JS auto-selection | Optimal performance per platform |
| Graceful Fallback | Works with or without agentic-flow | Always functional |

$3

| Feature | Description | Spec |
|---------|-------------|------|
| MCP 2025-11-25 | Full specification compliance | Latest MCP standard |
| Multiple Transports | stdio, HTTP, WebSocket, in-process | Flexible connectivity |
| Resources | list, read, subscribe with caching | Dynamic content |
| Prompts | Templates with arguments and embedding | Reusable prompts |
| Tasks | Async operations with progress/cancel | Long-running ops |
| Tool Registry | O(1) lookup, <10ms registration | Fast tool access |
| Connection Pooling | Max 10 connections, configurable | Resource management |
| Session Management | Timeout handling, authentication | Secure sessions |

$3

| Method | Description |
|--------|-------------|
| initialize | Initialize connection |
| tools/list | List available tools |
| tools/call | Execute a tool |
| resources/list | List resources with pagination |
| resources/read | Read resource content |
| resources/subscribe | Subscribe to updates |
| prompts/list | List prompts with pagination |
| prompts/get | Get prompt with arguments |
| tasks/status | Get task status |
| tasks/cancel | Cancel running task |
| completion/complete | Auto-complete arguments |

$3

| Feature | CVE/Issue | Description |
|---------|-----------|-------------|
| Password Hashing | CVE-2 | Secure bcrypt with 12+ rounds |
| Credential Generation | CVE-3 | Cryptographically secure API keys |
| Safe Command Execution | HIGH-1 | Allowlist-based command execution |
| Path Validation | HIGH-2 | Path traversal and symlink protection |
| Input Validation | General | Zod-based schema validation |
| Token Generation | General | HMAC-signed secure tokens |
| HTML Sanitization | XSS | Script and injection prevention |

$3

| Schema | Purpose |
|--------|---------|
| SafeStringSchema | Basic safe string with length limits |
| IdentifierSchema | Alphanumeric identifiers |
| FilenameSchema | Safe filenames |
| EmailSchema | Email addresses |
| PasswordSchema | Secure passwords (8-72 chars) |
| UUIDSchema | UUID v4 format |
| HttpsUrlSchema | HTTPS URLs only |
| SpawnAgentSchema | Agent spawn requests |
| TaskInputSchema | Task definitions |

$3

| Component | Description | Performance |
|-----------|-------------|-------------|
| ReasoningBank | Pattern storage with HNSW indexing | 150x faster retrieval |
| GuidanceProvider | Context-aware development guidance | Real-time suggestions |
| PatternLearning | Automatic strategy extraction | Continuous improvement |
| QualityTracking | Success/failure rate per pattern | Performance metrics |
| DomainDetection | Auto-categorization of patterns | Security, testing, etc. |
| AgentRouting | Task-to-agent optimization | Historical performance |
| Consolidation | Prune low-quality, promote high-quality | Memory optimization |

$3

| Phase | Hooks | Purpose |
|-------|-------|---------|
| Pre-Edit | pre-edit | Context gathering, security checks |
| Post-Edit | post-edit | Outcome recording, pattern learning |
| Pre-Command | pre-command | Risk assessment, validation |
| Post-Command | post-command | Success/failure tracking |
| Pre-Task | pre-task | Setup, resource allocation |
| Post-Task | post-task | Cleanup, learning |
| Session | session-end, session-restore | State management |

$3

Real-time development status display for Claude Code integration showing DDD progress, swarm activity, security status, and system metrics.

Output Format:
`
▊ Claude Flow V3 ● ruvnet │ ⎇ v3 │ Opus 4.5
─────────────────────────────────────────────────────
🏗️ DDD Domains [●●●●●] 5/5 ⚡ 1.0x → 2.49x-7.47x
🤖 Swarm ◉ [58/15] 👥 0 🟢 CVE 3/3 💾 22282MB 📂 47% 🧠 10%
🔧 Architecture DDD ● 98% │ Security ●CLEAN │ Memory ●AgentDB │ Integration ●
`

| Indicator | Description | Values |
|-----------|-------------|--------|
| ▊ Claude Flow V3 | Project header | Always shown |
| ● ruvnet | GitHub user (via gh CLI) | Dynamic |
| ⎇ v3 | Current git branch | Dynamic |
| Opus 4.5 | Claude model name | From Claude Code |
| [●●●●●] | DDD domain progress bar | 0-5 domains |
| ⚡ 1.0x → 2.49x-7.47x | Performance speedup target | Current → Target |
| ◉/○ | Swarm coordination status | Active/Inactive |
| [58/15] | Active agents / max agents | Process count |
| 👥 0 | Sub-agents spawned | Task tool agents |
| 🟢 CVE 3/3 | Security CVE remediation | Fixed/Total |
| 💾 22282MB | Memory usage (Node.js processes) | Real-time |
| 📂 47% | Context window usage | From Claude Code |
| 🧠 10% | Intelligence score (patterns learned) | 0-100% |
| DDD ● 98% | Domain-Driven Design progress | Percentage |
| Security ●CLEAN | Security audit status | CLEAN/PENDING/FAILED |
| Memory ●AgentDB | Memory backend in use | AgentDB/SQLite/Hybrid |
| Integration ● | agentic-flow integration status | Active/Inactive |

Usage:
`bash


V3 statusline (Node.js)

node v3/@claude-flow/hooks/bin/statusline.js

JSON output for scripting

node v3/@claude-flow/hooks/bin/statusline.js --json

Compact JSON (single line)

node v3/@claude-flow/hooks/bin/statusline.js --compact

Help

node v3/@claude-flow/hooks/bin/statusline.js --help
`

Claude Code Integration:

Add to .claude/settings.json:
`json
{
"statusLine": {
"type": "command",
"command": "node v3/@claude-flow/hooks/bin/statusline.js"
}
}
`

Data Sources:
- .claude-flow/metrics/v3-progress.json - DDD domain progress
- .claude-flow/metrics/swarm-activity.json - Active agent counts
- .claude-flow/security/audit-status.json - CVE remediation status
- .claude-flow/learning/patterns.db - Intelligence score (pattern count)
- Process detection via ps aux - Real-time memory and agent counts
- Git branch via git branch --show-current
- GitHub user via gh api user

$3

Automated background workers for continuous monitoring and metrics collection.

| Daemon | Interval | Purpose | Output |
|--------|----------|---------|--------|
| Swarm Monitor | 3s | Process detection, agent counting | swarm-activity.json |
| Metrics Daemon | 30s | V3 progress sync, SQLite metrics | metrics.db |

Commands:
`bash


Start all daemons

.claude/helpers/daemon-manager.sh start 3 5

Check daemon status

.claude/helpers/daemon-manager.sh status

Stop all daemons

.claude/helpers/daemon-manager.sh stop
`

Daemon Status Output:
`
═══════════════════════════════════════════════════
Claude Flow V3 Daemon Status
═══════════════════════════════════════════════════

● Swarm Monitor RUNNING (PID: 23383)
● Metrics Daemon RUNNING (PID: 2855)
○ MCP Server NOT DETECTED
○ Agentic Flow IDLE

───────────────────────────────────────────────────
Last Update: 2026-01-06T15:13:04+00:00
Active Agents: 0
═══════════════════════════════════════════════════
`

$3

| Worker | Interval | Purpose |
|--------|----------|---------|
| perf | 5 min | Performance benchmarks |
| health | 5 min | Disk, memory, CPU monitoring |
| patterns | 15 min | Pattern dedup & pruning |
| ddd | 10 min | DDD progress tracking |
| adr | 15 min | ADR compliance checking |
| security | 30 min | Security vulnerability scans |
| learning | 30 min | Learning pattern optimization |

Commands:
`bash


Start worker manager

.claude/helpers/worker-manager.sh start 60

Force run all workers immediately

.claude/helpers/worker-manager.sh force

Check worker status

.claude/helpers/worker-manager.sh status
`

---

Use Cases

| Use Case | Command |
|----------|---------|
| Code review | npx claude-flow@v3alpha --agent reviewer --task "Review PR #123" |
| Test generation | npx claude-flow@v3alpha --agent tester --task "Write tests for auth module" |
| Security audit | npx claude-flow@v3alpha --agent security-architect --task "Audit for vulnerabilities" |
| Multi-agent swarm | npx claude-flow@v3alpha swarm init --topology hierarchical |
| Route task | npx claude-flow@v3alpha hooks route "Optimize database queries" |
| Performance analysis | npx claude-flow@v3alpha --agent perf-analyzer --task "Profile API endpoints" |
| GitHub PR management | npx claude-flow@v3alpha --agent pr-manager --task "Review open PRs" |

---

Self-Learning Hooks Commands (26 Hooks)

$3


`bash

Before/after file editing

npx claude-flow@v3alpha hooks pre-edit
npx claude-flow@v3alpha hooks post-edit --success true --train-patterns

Before/after commands

npx claude-flow@v3alpha hooks pre-command ""
npx claude-flow@v3alpha hooks post-command "" --success true

Before/after tasks

npx claude-flow@v3alpha hooks pre-task --description ""
npx claude-flow@v3alpha hooks post-task --task-id "" --success true
`

$3

`bash

Route task to optimal agent using learned patterns

npx claude-flow@v3alpha hooks route "" --include-explanation

Explain routing decision with transparency

npx claude-flow@v3alpha hooks explain "" --depth comprehensive

Bootstrap intelligence from repository

npx claude-flow@v3alpha hooks pretrain --model-type moe --epochs 10

Generate optimized agent configs from pretrain data

npx claude-flow@v3alpha hooks build-agents --agent-types coder,tester --config-format yaml

Transfer patterns from another project

npx claude-flow@v3alpha hooks transfer

Initialize hooks system

npx claude-flow@v3alpha hooks init

View learning metrics dashboard

npx claude-flow@v3alpha hooks metrics

List all registered hooks

npx claude-flow@v3alpha hooks list
`

$3

`bash

Start session with context loading

npx claude-flow@v3alpha hooks session-start --session-id "" --load-context

End session with persistence

npx claude-flow@v3alpha hooks session-end --export-metrics true --persist-patterns

Restore previous session context

npx claude-flow@v3alpha hooks session-restore --session-id ""

Send notifications to swarm

npx claude-flow@v3alpha hooks notify --message "" --swarm-status
`

$3

`bash

Trajectory-based learning (4-step pipeline: RETRIEVE, JUDGE, DISTILL, CONSOLIDATE)

npx claude-flow@v3alpha hooks intelligence trajectory-start --session ""
npx claude-flow@v3alpha hooks intelligence trajectory-step --action "" --reward 0.9
npx claude-flow@v3alpha hooks intelligence trajectory-end --verdict success

Pattern storage with HNSW indexing (150x faster search)

npx claude-flow@v3alpha hooks intelligence pattern-store --pattern "" --embedding "[...]"
npx claude-flow@v3alpha hooks intelligence pattern-search --query "" --limit 10

Learning stats and attention focus

npx claude-flow@v3alpha hooks intelligence stats
npx claude-flow@v3alpha hooks intelligence learn --experience '{"type":"success"}'
npx claude-flow@v3alpha hooks intelligence attention --focus ""

Full intelligence system (SONA, MoE, HNSW, EWC++, Flash Attention)

npx claude-flow@v3alpha hooks intelligence
npx claude-flow@v3alpha hooks intelligence reset --confirm

═══════════════════════════════════════════════════════════════

Background Worker Commands (12 workers for analysis/optimization)

═══════════════════════════════════════════════════════════════

List all available workers

npx claude-flow@v3alpha hooks worker list

Detect triggers from prompt text

npx claude-flow@v3alpha hooks worker detect --prompt "optimize performance"

Auto-dispatch workers when triggers match (confidence ≥0.6)

npx claude-flow@v3alpha hooks worker detect --prompt "deep dive into auth" --auto-dispatch --min-confidence 0.6

Manually dispatch a worker (ultralearn, optimize, audit, map, deepdive, document, refactor, benchmark, testgaps, etc.)

npx claude-flow@v3alpha hooks worker dispatch --trigger refactor --context "auth module"

Check worker status

npx claude-flow@v3alpha hooks worker status

Cancel a running worker

npx claude-flow@v3alpha hooks worker cancel --id worker_refactor_1_abc123
`

---

Architecture

$3

`
v3/
├── @claude-flow/hooks # Event-driven lifecycle hooks + ReasoningBank
├── @claude-flow/memory # AgentDB unification module
├── @claude-flow/security # CVE remediation & patterns
├── @claude-flow/swarm # 15-agent coordination
├── @claude-flow/plugins # RuVector WASM plugins
├── @claude-flow/cli # CLI modernization
├── @claude-flow/neural # SONA learning integration
├── @claude-flow/testing # TDD London School framework
├── @claude-flow/deployment # Release & CI/CD
└── @claude-flow/shared # Shared utilities & types
`



$3

| Metric | Measured |
|--------|----------|
| Swarm task execution | 100% success rate (7/7 strategies) |
| Average task duration | 0.15-0.30 seconds |
| Memory usage per agent | 128-320 MB |
| CPU utilization | 15-30% per agent |
| Parallel agent capacity | Unlimited (resource-dependent) |

$3

| Topology | Agents | Execution Time | Memory |
|----------|--------|----------------|--------|
| Centralized | 2-3 | 0.14-0.20s | 180-256 MB |
| Distributed | 4-5 | 0.10-0.12s | 128-160 MB |
| Hierarchical | 6 | 0.20s | 256 MB |
| Mesh | 4 | 0.15s | 192 MB |
| Hybrid | 7 | 0.18s | 320 MB |

---

Cross-Platform Support

$3

`powershell
npx @claude-flow/security@latest audit --platform windows
$env:CLAUDE_FLOW_MODE = "integration"
`

$3

`bash
npx @claude-flow/security@latest audit --platform darwin
export CLAUDE_FLOW_SECURITY_MODE="strict"
`

$3

`bash
npx @claude-flow/security@latest audit --platform linux
export CLAUDE_FLOW_MEMORY_PATH="./data"
`

---

Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| CLAUDE_FLOW_MODE | Operation mode (development, production, integration) | development |
| CLAUDE_FLOW_MEMORY_PATH | Directory for persistent memory storage | ./data |
| CLAUDE_FLOW_SECURITY_MODE | Security level (strict, standard, permissive) | standard |
| CLAUDE_FLOW_LOG_LEVEL | Logging verbosity (debug, info, warn, error) | info |
| CLAUDE_FLOW_MAX_AGENTS | Default concurrent agent limit (increase for more parallelism) | 15 |
| CLAUDE_FLOW_TOPOLOGY | Default swarm topology | hierarchical |
| CLAUDE_FLOW_HNSW_M | HNSW index M parameter (connectivity) | 16 |
| CLAUDE_FLOW_HNSW_EF | HNSW search ef parameter (accuracy) | 200 |
| CLAUDE_FLOW_EMBEDDING_DIM | Vector embedding dimensions | 384 |
| ANTHROPIC_API_KEY | Anthropic API key for Claude integration | - |

---

Troubleshooting

$3

MCP server won't start
`bash


Check if port is in use

lsof -i :3000

Kill existing process

kill -9

Restart MCP server

npx claude-flow@v3alpha mcp start
`

Agent spawn failures
`bash


Check available memory

free -m

Reduce max agents if memory constrained

export CLAUDE_FLOW_MAX_AGENTS=5
`

Pattern search returning no results
`bash


Verify patterns are stored

npx claude-flow@v3alpha hooks metrics

Re-run pretraining if empty

npx claude-flow@v3alpha hooks pretrain
`

Windows path issues
`powershell


Use forward slashes or escape backslashes

$env:CLAUDE_FLOW_MEMORY_PATH = "./data"

Or use absolute path

$env:CLAUDE_FLOW_MEMORY_PATH = "C:/Users/name/claude-flow/data"
`

Permission denied errors
`bash


Fix npm permissions (Linux/macOS)

sudo chown -R $(whoami) ~/.npm

Or use nvm to manage Node.js

`

High memory usage
`bash


Enable garbage collection

node --expose-gc node_modules/.bin/claude-flow

Reduce HNSW parameters for lower memory

export CLAUDE_FLOW_HNSW_M=8
export CLAUDE_FLOW_HNSW_EF=100
`

---

Migration Guide (V2 → V3)

$3

1. Module Structure: V3 uses scoped packages (@claude-flow/*)
2. Memory Backend: Default changed from JSON to AgentDB with HNSW
3. Hooks System: New ReasoningBank replaces basic pattern storage
4. Security: Stricter input validation enabled by default

$3

`bash


1. Backup existing data

cp -r ./data ./data-backup-v2

2. Update to V3

npm install claude-flow@latest

3. Run migration

npx claude-flow@v3alpha migrate --from v2

4. Verify installation

npx claude-flow@v3alpha --version
npx claude-flow@v3alpha hooks metrics
`

$3

`bash


V2 (deprecated)

npx claude-flow init --mode basic

V3 (new)

npx claude-flow@v3alpha init
npx claude-flow@v3alpha hooks pretrain # Bootstrap learning
`

$3

| V2 API | V3 API |
|--------|--------|
| claude-flow start | claude-flow mcp start |
| --pattern-store | --memory-backend agentdb |
| hooks record | hooks post-edit --success |
| swarm create | swarm init --topology |

---

Documentation

$3

| Module | Description | Docs |
|--------|-------------|------|
| @claude-flow/plugins | Plugin SDK with workers, hooks, providers, security | README |
| @claude-flow/hooks | Event-driven lifecycle hooks + ReasoningBank | Source |
| @claude-flow/memory | AgentDB unification with HNSW indexing | Source |
| @claude-flow/security | CVE remediation & security patterns | Source |
| @claude-flow/swarm | 15-agent coordination engine | Source |
| @claude-flow/cli | CLI modernization | Source |
| @claude-flow/neural | SONA learning integration | Source |
| @claude-flow/testing | TDD London School framework | Source |
| @claude-flow/mcp | MCP server & tools | Source |
| @claude-flow/embeddings | Vector embedding providers | Source |
| @claude-flow/providers | LLM provider integrations | Source |
| @claude-flow/integration | agentic-flow@alpha integration | Source |
| @claude-flow/performance | Benchmarking & optimization | Source |
| @claude-flow/deployment | Release & CI/CD | Source |
| @claude-flow/shared` | Shared utilities & types | Source |

$3

- V2 Documentation
- Architecture Decisions (ADRs)
- API Reference
- Examples

Support

- Documentation: https://github.com/ruvnet/claude-flow
- Issues: https://github.com/ruvnet/claude-flow/issues
- Discord: Agentics Foundation

License

MIT - RuvNet