| name | hive-mind-advanced |
| description | Queen-led collective-intelligence coordination with consensus mechanisms and persistent shared memory. Use when orchestrating a large swarm of agents under a lead coordinator, building consensus across agents, or maintaining durable cross-agent memory. |
| version | 1.0.0 |
| category | coordination |
| tags | ["hive-mind","swarm","queen-worker","consensus","collective-intelligence","multi-agent","coordination"] |
| author | Claude Flow Team |
Hive Mind Advanced Skill
Master the advanced Hive Mind collective intelligence system for sophisticated multi-agent coordination using queen-led architecture, Byzantine consensus, and collective memory.
Overview
The Hive Mind system represents the pinnacle of multi-agent coordination in Claude Flow, implementing a queen-led hierarchical architecture where a strategic queen coordinator directs specialized worker agents through collective decision-making and shared memory.
Core Concepts
Architecture Patterns
Queen-Led Coordination
- Strategic queen agents orchestrate high-level objectives
- Tactical queens manage mid-level execution
- Adaptive queens dynamically adjust strategies based on performance
Worker Specialization
- Researcher agents: Analysis and investigation
- Coder agents: Implementation and development
- Analyst agents: Data processing and metrics
- Tester agents: Quality assurance and validation
- Architect agents: System design and planning
- Reviewer agents: Code review and improvement
- Optimizer agents: Performance enhancement
- Documenter agents: Documentation generation
Collective Memory System
- Shared knowledge base across all agents
- LRU cache with memory pressure handling
- SQLite persistence with WAL mode
- Memory consolidation and association
- Access pattern tracking and optimization
Consensus Mechanisms
Majority Consensus
Simple voting where the option with most votes wins.
Weighted Consensus
Queen vote counts as 3x weight, providing strategic guidance.
Byzantine Fault Tolerance
Requires 2/3 majority for decision approval, ensuring robust consensus even with faulty agents.
Getting Started
1. Initialize Hive Mind
npx claude-flow hive-mind init
npx claude-flow hive-mind init --force
npx claude-flow hive-mind init --config hive-config.json
2. Spawn a Swarm
npx claude-flow hive-mind spawn "Build microservices architecture"
npx claude-flow hive-mind spawn "Research AI patterns" --queen-type strategic
npx claude-flow hive-mind spawn "Implement API" --queen-type tactical --max-workers 12
npx claude-flow hive-mind spawn "Optimize system" --queen-type adaptive --consensus byzantine
npx claude-flow hive-mind spawn "Build full-stack app" --claude
3. Monitor Status
npx claude-flow hive-mind status
npx claude-flow hive-mind metrics
npx claude-flow hive-mind memory
Reference
The full detail lives in references/ and loads only when needed:
Skill Progression
Beginner
- Initialize hive mind
- Spawn basic swarms
- Monitor status
- Use majority consensus
Intermediate
- Configure queen types
- Implement session management
- Use weighted consensus
- Access collective memory
- Enable auto-scaling
Advanced
- Byzantine fault tolerance
- Memory optimization
- Custom worker types
- Multi-hive coordination
- Neural pattern training
- Session export/import
- Performance tuning
Related Skills
swarm-orchestration: Basic swarm coordinationconsensus-mechanisms: Distributed decision makingmemory-systems: Advanced memory managementsparc-methodology: Structured development workflowgithub-integration: Repository coordination
References
Skill Version: 1.0.0
Last Updated: 2025-10-19
Maintained By: Claude Flow Team
License: MIT
