Hive Mind Advanced
技能 已验证 活跃Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
To provide a robust and scalable framework for orchestrating complex multi-agent systems, enabling advanced coordination, collective learning, and decision-making.
功能
- Queen-led hierarchical agent coordination
- Specialized worker agent roles
- Persistent collective memory with caching and SQLite persistence
- Majority, Weighted, and Byzantine consensus mechanisms
- Detailed configuration and session management
使用场景
- Coordinating complex software development projects
- Implementing research and analysis tasks with multiple AI agents
- Managing large-scale code review and quality assurance processes
- Building adaptive systems that optimize performance dynamically
非目标
- Acting as a standalone agent for simple tasks
- Replacing individual agent functionality with a general orchestrator
- Operating without the underlying Claude Flow or Claude Code environment
安装
npx skills add ruvnet/ruflo通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
Swarm Orchestration
100Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
Collective Intelligence Coordinator
95Agent skill for collective-intelligence-coordinator - invoke with $agent-collective-intelligence-coordinator
Agent Worker Specialist
100Agent skill for worker-specialist - invoke with $agent-worker-specialist
Board
100Read, write, and browse the AgentHub message board for agent coordination.
External Context
100Invoke parallel document-specialist agents for external web searches and documentation lookup
Test Team Coordination
99Execute a test scenario against a team, observing coordination pattern behaviors, evaluating acceptance criteria, and generating a structured RESULT.md. Use when validating that a team's coordination pattern produces the expected behaviors during a realistic task, comparing coordination patterns on equivalent workloads, or establishing baseline performance for a team composition.