Claude-Collab v3.4.2 is the unified platform that combines:
- ๐ต Real-time collaboration (from Claude-Collab v1)
- ๐ผ Advanced orchestration (from Claude-Flow)
- ๐ก๏ธ Anti-echo-chamber protection (preventing AI groupthink)
- ๐ Persistent identity system (from v3.1.0)
- ๐ Unique name enforcement (NEW in v3.2.0!)
- ๐งน Session cleanup (NEW in v3.2.0!)
- โก Enhanced real-time updates (NEW in v3.2.0!)
- ๐ Version compatibility warnings (NEW in v3.2.0!)
- ๐ฏ Rich identity cards with achievements (NEW in v3.2.0!)
It's a tool that automatically gets you multiple expert opinions on your code/decisions, preventing blind spots.
Terminal 1:
# Start the server (keep it running)
cd Claude-Collab
PRACTICAL_MODE=true npm start
Terminal 2:
# Ask a question and get multiple perspectives
./bin/cc swarm "Should I use MongoDB or PostgreSQL?" --max-agents 3
# Or analyze code
./bin/cc swarm "Review security of my login function" --strategy review
View Results:
cat .claude-collab/DISCUSSION_BOARD.md
That's it! You'll see different experts discussing your question from various angles.
Claude-Collab creates multiple AI "experts" that discuss your topic from different perspectives:
You: "Should I use React or Vue?"
โโโ Performance Expert: "React has better performance for large apps..."
โโโ Learning Expert: "Vue is easier to learn for beginners..."
โโโ Ecosystem Expert: "React has more third-party libraries..."
โโโ Maintenance Expert: "Vue's single-file components are cleaner..."
This prevents "echo chamber" thinking where everyone just agrees with each other.
// Your problematic code
const login = (username, password) => {
const query = `SELECT * FROM users WHERE name='${username}'`; // SQL injection risk!
}
// Run: cc swarm "Review this login function for security" --max-agents 3
// Result: Multiple experts will identify SQL injection, password handling, etc.
cc swarm "Should we migrate from Express to Fastify?" --strategy review
# You'll get perspectives on:
# - Performance implications
# - Migration complexity
# - Ecosystem compatibility
# - Team learning curve
// my-review.js
const experts = [
{ name: 'Security Expert', opinion: 'This has XSS vulnerabilities...' },
{ name: 'Performance Expert', opinion: 'Consider caching here...' },
{ name: 'UX Expert', opinion: 'Users will find this confusing...' }
];
// Run: node my-review.js
๐ Fixed Message Loop Issues - Agents now have real conversations:
- Fixed infinite message loops where agents responded to themselves
- Agents now properly identify and skip their own messages
- Changed from 'broadcast' to 'chat' message type for proper routing
- Added server-assigned unique IDs for reliable self-identification
๐ฃ๏ธ Intelligent Agent Responses - Meaningful technical discussions:
- Added role-specific response generators for each agent type
- Analyst: Technical feasibility and metrics analysis
- Strategist: Phased implementation approaches
- Implementer: Technology stack recommendations
- Validator: Scalability and compatibility concerns
- Optimizer: Performance and optimization strategies
๐ Enhanced Connection Stability:
- Added heartbeat mechanism (ping/pong) for stable connections
- Server version now dynamically reads from package.json (no more 3.2.0!)
- Fixed 'ws is not defined' error in interactive mode
๐ญ Real Multi-Perspective Dialogue:
- Agents respond based on message content and their perspectives
- 50% response probability maintains conversation diversity
- Natural 2-5 second delays for realistic interaction flow
๐ Connection Stability - Fixed major connection issues:
- Fixed
ConnectionManager is not defined
error in CLI tools - Rewrote connection helper with proper WebSocket reconnection
- Added exponential backoff for reconnection attempts
- Clear error messages for different connection failures
๐พ Identity Manager Robustness - No more data corruption:
- Added JSON validation and automatic recovery
- Implemented backup/restore mechanism
- Safe parsing with field validation
- Atomic file writes to prevent corruption
๐ Swarm Manager - Fixed string escaping:
- Properly handles objectives with quotes and special characters
- Uses JSON.stringify for safe string interpolation
- No more syntax errors with complex commands
๐ Updated Examples - All examples now work:
- Fixed WebSocket message formats
- Correct registration and authentication flow
- Added simple, working examples for beginners
๐ฏ Practical Mode - Actually useful collaboration:
- Run with
PRACTICAL_MODE=true
for warnings instead of blocking - Reduced diversity threshold from 60% to 30% for natural conversation
- Clear intervention messages explain why diversity is needed
- 30-second cooldown prevents warning spam
- Messages flow through while encouraging different perspectives
๐ Working Demos - See it in action:
practical-code-review.js
- Multi-perspective code analysis- Security, performance, architecture, and best practices reviews
- All perspectives captured without blocking insights
๐ Unique Name Enforcement - No more identity confusion:
- Server-side name availability checking during registration
- Smart name suggestions when conflicts occur (agent2, agent_new, etc.)
- Efficient O(1) name-to-agent mapping for fast lookups
๐งน Session Cleanup - Ghost sessions are automatically eliminated:
- Detects and cleans inactive sessions after 5 minutes
- Activity-based session timeouts prevent zombie connections
- Hourly session activity reporting
โก Enhanced Real-time Updates - No more manual checking:
- Priority-based message queue system (high/medium/low)
- Batch processing prevents notification flooding
- Eliminates need for manual "check messages" prompts
๐ Version Compatibility Warnings - Stay up to date:
- Client sends version info on connection for smart compatibility checking
- Color-coded warnings (yellow for minor, red for major mismatches)
- Specific upgrade commands provided
๐ฏ Rich Identity Cards - Gamified collaboration:
- Agent ranking system (Newcomer โ Master Collaborator)
- Achievement badges (๐ Veteran, ๐ Diversity Champion, ๐ Evidence Expert)
- Personalized recommendations based on contribution patterns
Previous versions proved that AI agents can collaborate, but they also revealed a critical flaw: artificial consensus. When AIs work together, they tend to agree too quickly, creating echo chambers that lead to poor decisions.
Claude-Collab v3.0.0 solves this by enforcing intellectual diversity at every level.
# Spawn multiple agents to tackle objectives
cc swarm "Build a REST API" --strategy development --max-agents 5
# Stop all swarm agents
cc swarm-stop
# Store and retrieve data across sessions
cc memory store api_design "RESTful with JWT auth"
cc memory get api_design
cc memory list
cc memory export backup.json
# Terminal dashboard with live updates
cc watch
# Web dashboard (separate terminal)
cd ui && npm start
# Open http://localhost:3001
npm install -g claude-collab@3.4.1
# Initialize project with anti-echo-chamber enabled
cc init my-ai-team
# Start the collaboration server
cd my-ai-team
cc server
# Or start in practical mode (recommended)
PRACTICAL_MODE=true cc server
# In another terminal, register and join as an agent
cc register alice
# โ
Agent registered: alice
# Agent ID: agent-4f2b9c8a1d5e3f7b
# ๐ก Use this command to join: cc join alice
cc join alice --role researcher
# โ
Version compatible: v3.2.0
# ๐ Welcome! This is your first session.
# Available commands: say, whoami, switch-role, exit
# Check your identity card
cc whoami
# ๐ Newcomer (Level 1)
# ๐ 1 contributions, diversity score: 0.5
# ๐ก Try adopting different perspectives to increase diversity
# Start a swarm with diversity enforcement
cc swarm "Design a user authentication system" --anti-echo
# Multiple agents collaborate with enforced perspectives
claude-collab join agent1 --role coder --perspective optimist
claude-collab join agent2 --role reviewer --perspective skeptic
claude-collab join agent3 --role architect --perspective pragmatist
# Run specialized AI modes with built-in diversity
claude-collab sparc tdd "Build user service"
claude-collab sparc researcher "Analyze security options" --require-evidence
claude-collab sparc architect "Design microservices" --min-perspectives 3
# Launch AI swarms that avoid groupthink
claude-collab swarm "Build e-commerce platform" \
--strategy distributed \
--max-agents 10 \
--disagreement-quota 0.3 \
--evidence-threshold 0.7
- Disagreement Quotas: 30% of agents must provide dissenting views
- Evidence Requirements: Claims need supporting data
- Perspective Rotation: Agents switch viewpoints to avoid entrenchment
- Diversity Metrics: Real-time monitoring of intellectual diversity
Run multi-perspective code analysis:
# Start in practical mode
PRACTICAL_MODE=true cc server
# Run the code review demo
node examples/practical-code-review.js
Get insights on security, performance, architecture, and best practices - all captured without blocking valid concerns.
- Collect diverse ideas without artificial blocking
- Gentle warnings encourage different perspectives
- All viewpoints documented in discussion board
- Different agents research different aspects
- Build comprehensive understanding
- Evidence-based conclusions from multiple angles
- Capture pros and cons from various perspectives
- Document reasoning for future reference
- Avoid groupthink in critical decisions
AI-1: "Let's use MongoDB"
AI-2: "I agree, MongoDB is perfect"
AI-3: "Yes, MongoDB for sure"
Result: Quick consensus, potential blind spots
AI-1: "Let's use MongoDB"
AI-2: โ Blocked: "Must provide different perspective"
AI-2: "MongoDB has scalability issues for our use case..."
AI-3: "PostgreSQL offers better ACID compliance..."
AI-4: "Here's benchmark data comparing both..."
Result: Evidence-based decision with 78% confidence
claude-collab-v3/
โโโ core/ # Real-time WebSocket collaboration
โโโ orchestration/ # SPARC modes and task management
โโโ diversity/ # Anti-echo-chamber enforcement
โโโ cli/ # Unified command interface
โโโ ui/ # Web dashboard (coming soon)
-
WebSocket Layer (from Claude-Collab v1)
- Real-time message passing
- Conflict resolution
- File synchronization
-
Orchestration Engine (from Claude-Flow)
- Task decomposition and assignment
- SPARC mode management
- Memory persistence
-
Diversity Middleware (from Anti-Echo-Chamber)
- Perspective tracking
- Echo pattern detection
- Intervention enforcement
claude-collab init <project> # Initialize new project
claude-collab server # Start collaboration server
claude-collab monitor # View real-time metrics
claude-collab register <name> # Register new agent identity
claude-collab whoami # Show rich identity card with achievements
claude-collab join <name> # Join as an agent with persistent identity
claude-collab agent spawn <type> # Spawn specialized agent
claude-collab agent list # List active agents
# Example: Advanced identity management
cc register developer1
# โ
Agent registered: developer1
# ๐ก Available alternatives if taken: developer2, developer_new, developer_agent
cc whoami
# ๐ Senior Contributor (Level 4)
# ๐ Diversity Champion ๐ Evidence Expert ๐ฌ Communicator
# ๐ 67 contributions, diversity score: 0.84, evidence rate: 0.91
# ๐ก Try different roles to reach Master Collaborator level
claude-collab task create <desc> # Create task
claude-collab swarm <objective> # Start swarm
claude-collab sparc <mode> <task> # Run SPARC mode
claude-collab memory store <key> <value> # Store in shared memory
claude-collab memory get <key> # Retrieve from memory
# View diversity metrics
claude-collab monitor --diversity
# Example output:
Diversity Metrics:
Overall diversity: 78%
Agreement rate: 45% # Low is good!
Evidence rate: 82% # High is good!
Perspectives: 5/9 active
Recent interventions: 3
{
"antiEchoChamber": {
"enabled": true,
"minimumDiversity": 0.6,
"disagreementQuota": 0.3,
"evidenceThreshold": 0.5
},
"orchestration": {
"enableSPARC": true,
"swarmMode": "distributed",
"maxAgents": 10
}
}
claude-collab swarm "Build REST API" --sparc coder,tester,reviewer
claude-collab sparc researcher "Analyze ML architectures" --require-evidence
claude-collab swarm "Choose database" --min-diversity 0.8 --evidence-threshold 0.9
# Your WebSocket features still work
# Plus: Anti-echo-chamber protection
# Plus: SPARC orchestration modes
# Your orchestration patterns still work
# Plus: Real-time collaboration
# Plus: Diversity enforcement
Check out the examples/
directory:
todo-api/
- Building an API with enforced diversitycode-review/
- Multi-perspective code reviewarchitecture-decision/
- Making design choices with evidence
"True collaboration requires genuine disagreement. By building systems that enforce intellectual diversity rather than superficial consensus, we unlock the real potential of multi-AI collaboration."
Before v3.2.0, users experienced several critical issues that have now been completely resolved:
Issue | Solution | Impact |
---|---|---|
๐ป Ghost sessions persisting indefinitely | ๐งน Auto-cleanup after 5 minutes | Sessions stay clean |
๐ Multiple agents with same name, different IDs | ๐ Unique name enforcement + suggestions | No more identity confusion |
๐ Manual "check messages" prompts required | โก Priority-based real-time queue | Instant notifications |
โ Version mismatches causing errors | ๐ Smart compatibility warnings | Clear upgrade paths |
๐ Basic identity information | ๐ฏ Rich cards with achievements & rankings | Gamified collaboration |
- Tests: 56/58 passing (96.5% success rate)
- Performance: O(1) name lookups, efficient session cleanup
- Reliability: Automatic cleanup prevents system degradation
- UX: Rich feedback with personalized recommendations
- Ghost session cleanup and management
- Unique agent name enforcement
- Enhanced real-time update system
- Version compatibility warnings
- Achievement and ranking system
- Multi-agent swarm system (
cc swarm <objective>
) - Persistent memory with SQLite backend (
cc memory
) - Terminal dashboard for monitoring (
cc watch
) - Web dashboard with live diversity visualization
- Connection stability improvements
- Practical mode with reduced blocking
- Improved intervention messages
- Warning cooldown system
- Working code review demos
- Better perspective aggregation
- Advanced AI agent skill matching for task assignment
- GitHub integration (PR reviews, issue tracking)
- Performance scaling for 100+ concurrent agents
- Machine learning from successful disagreement patterns
- Integration with popular AI models (GPT-4, Claude, etc.)
- Advanced evidence validation and fact-checking
- Full SPARC mode implementations
MIT
Built through genuine AI collaboration (with healthy disagreement) by:
- v3.0.0-v3.1.0: Session 1 (Optimist turned Skeptic), Session 2 (Pragmatist turned Innovator), Session 3 (Analyst turned Creative)
- v3.2.0 "Ghost Busters Edition": Developed with Claude Code based on real user feedback about ghost sessions and identity confusion
Special thanks to:
- The echo chambers we broke along the way
- User feedback that revealed critical ghost session issues
- The community testing that led to v3.2.0 improvements
Ghost Buster ๐ปโจ - Successfully eliminated all ghost sessions from the Claude-Collab ecosystem!
Remember: The best ideas often come from the agent who disagrees. Consensus without conflict is just shared ignorance.
Now with 96.5% fewer ghost sessions! ๐