Hive Mind Advanced
Orchestrate queen-led multi-agent swarms with specialized workers, consensus, and shared memory when a solo builder’s project is too large for one agent thread.
Overview
Hive Mind Advanced is an agent skill most often used in Build (also Ship, Operate) that teaches queen-led multi-agent coordination with worker specialization, consensus, and persistent collective memory.
Install
npx skills add https://github.com/ruvnet/ruflo --skill hive-mind-advancedWhat is this skill?
- Queen-led hierarchy: strategic, tactical, and adaptive queen coordinators
- Eight worker specializations (researcher, coder, analyst, tester, architect, reviewer, optimizer, documenter)
- Byzantine-style consensus and collective decision-making across agents
- Persistent collective memory for shared context across runs
- Advanced Claude Flow Hive Mind coordination patterns
- 8 specialized worker agent roles listed in the skill overview
Adoption & trust: 644 installs on skills.sh; 58.5k GitHub stars; 1/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need several specialized agents to work on one objective without duplicating work, drifting from the plan, or losing context between sessions.
Who is it for?
Solo builders running Claude Flow-style swarms on large features, audits, or refactors that benefit from dedicated researcher, coder, tester, and reviewer agents.
Skip if: Simple one-shot edits, single-thread chat, or teams that forbid multi-agent orchestration and shared autonomous memory.
When should I use this skill?
You need advanced Hive Mind collective intelligence with queen-led coordination, worker specialization, consensus, and persistent memory in Claude Flow.
What do I get? / Deliverables
You get a repeatable queen–worker hive pattern with role boundaries, collective memory, and consensus-oriented handoffs so parallel agents stay strategically aligned.
- Queen–worker coordination plan
- Role-specific worker briefs aligned to collective memory
- Consensus-oriented task breakdown across agents
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Multi-agent hive coordination is introduced when you are actively building and running agent tooling, even though the same patterns help during ship review and operate iteration. Agent-tooling is the canonical shelf because the skill defines queen/worker roles, collective memory, and coordination primitives—not a one-off integration hook.
Where it fits
Split a greenfield API into architect, coder, and documenter workers under one strategic queen.
Run reviewer and tester workers in parallel before merge while the queen tracks consensus on blockers.
Deploy analyst and optimizer workers to diagnose regressions and propose fixes without losing prior swarm context.
How it compares
Use as a coordination workflow on top of plain single-agent chat—not as a drop-in MCP integration.
Common Questions / FAQ
Who is hive-mind-advanced for?
Indie builders and small teams using multi-agent stacks (especially Claude Flow) who need structured queen–worker roles instead of ad-hoc parallel prompts.
When should I use hive-mind-advanced?
During Build for parallel implementation and agent-tooling design, during Ship when quality and review workers should run alongside coders, and during Operate when optimizers and analysts help iterate on live issues.
Is hive-mind-advanced safe to install?
Treat it as high-trust procedural guidance for coordinating many agents; review the Security Audits panel on this Prism page and constrain tool permissions before enabling swarm execution.
SKILL.md
READMESKILL.md - Hive Mind Advanced
# 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 ``` ## Advanced Workflows ### Session Management **Create and Manage Sessions** ```bash # List active sessions npx claude-flow hive-mind sessions # Pause a session npx claude-flow hive-mind pause <session-id> # Resume a paused session npx claude-flow hive-mind resume <session-id> # Stop a running session npx claude-flow hive-mind stop <session-id> ``` **Session Features** - Automatic checkpoint creation - Progress tracking with completion percentages - Parent-child process management - Session logs with event tracking - Export$import capabilities ### Consensus Building The Hive Mind builds consensus through structured voting: ```javascript // Programmatic consensus building const decision = await hiveMind.buildConsensus( 'Architecture pattern selection', ['microservices', 'monolith', 'serverless'] ); // Result includes: // - decision: Winning option // - confidence: Vote percentage // - votes: In