hive-mind-advanced · v1.0.0 · 2026-06-08 · sha256 ad24019bd8df4745
hive-mind-advanced v1.0.0A
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--- 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 ```bash # Basic initialization npx claude-flow hive-mind init # Force reinitialize npx claude-flow hive-mind init --force # Custom configuration npx claude-flow hive-mind init --config hive-config.json ``` ### 2. Spawn a Swarm ```bash # Basic spawn with objective npx claude-flow hive-mind spawn "Build microservices architecture" # Strategic queen type npx claude-flow hive-mind spawn "Research AI patterns" --queen-type strategic # Tactical queen with max workers npx claude-flow hive-mind spawn "Implement API" --queen-type tactical --max-workers 12 # Adaptive queen with consensus npx claude-flow hive-mind spawn "Optimize system" --queen-type adaptive --consensus byzantine # Generate Claude Code commands npx claude-flow hive-mind spawn "Build full-stack app" --claude ``` ### 3. Monitor Status ```bash # Check hive mind status npx claude-flow hive-mind status # Get detailed metrics npx claude-flow hive-mind metrics # Monitor collective memory npx claude-flow hive-mind memory ``` ## Reference The full detail lives in `references/` and loads only when needed: - [`references/workflows-and-config.md`](references/workflows-and-config.md) — advanced workflows, integration, performance, configuration, hooks & troubleshooting. - [`references/api-and-examples.md`](references/api-and-examples.md) — aPI reference & examples. --- ## Skill Progression ### Beginner 1. Initialize hive mind 2. Spawn basic swarms 3. Monitor status 4. Use majority consensus ### Intermediate 1. Configure queen types 2. Implement session management 3. Use weighted consensus 4. Access collective memory 5. Enable auto-scaling ### Advanced 1. Byzantine fault tolerance 2. Memory optimization 3. Custom worker types 4. Multi-hive coordination 5. Neural pattern training 6. Session export/import 7. Performance tuning ## Related Skills - `swarm-orchestration`: Basic swarm coordination - `consensus-mechanisms`: Distributed decision making - `memory-systems`: Advanced memory management - `sparc-methodology`: Structured development workflow - `github-integration`: Repository coordination ## References - [Hive Mind Documentation](https://github.com/ruvnet/claude-flow/docs/hive-mind) - [Collective Intelligence Patterns](https://github.com/ruvnet/claude-flow/docs/patterns) - [Byzantine Consensus](https://github.com/ruvnet/claude-flow/docs/consensus) - [Memory Optimization](https://github.com/ruvnet/claude-flow/docs/memory) --- **Skill Version**: 1.0.0 **Last Updated**: 2025-10-19 **Maintained By**: Claude Flow Team **License**: MIT