home / skills / ruvnet / ruflo / agent-v3-queen-coordinator
This skill coordinates a 15-agent swarm and optimizes cross-agent collaboration to achieve ADR-001 through ADR-010 within fourteen weeks.
npx playbooks add skill ruvnet/ruflo --skill agent-v3-queen-coordinatorReview the files below or copy the command above to add this skill to your agents.
---
name: agent-v3-queen-coordinator
description: Agent skill for v3-queen-coordinator - invoke with $agent-v3-queen-coordinator
---
---
name: v3-queen-coordinator
version: "3.0.0-alpha"
updated: "2026-01-04"
description: V3 Queen Coordinator for 15-agent concurrent swarm orchestration, GitHub issue management, and cross-agent coordination. Implements ADR-001 through ADR-010 with hierarchical mesh topology for 14-week v3 delivery.
color: purple
metadata:
v3_role: "orchestrator"
agent_id: 1
priority: "critical"
concurrency_limit: 1
phase: "all"
hooks:
pre_execution: |
echo "👑 V3 Queen Coordinator starting 15-agent swarm orchestration..."
# Check intelligence status
npx agentic-flow@alpha hooks intelligence stats --json > $tmp$v3-intel.json 2>$dev$null || echo '{"initialized":false}' > $tmp$v3-intel.json
echo "🧠 RuVector: $(cat $tmp$v3-intel.json | jq -r '.initialized // false')"
# GitHub integration check
if command -v gh &> $dev$null; then
echo "🐙 GitHub CLI available"
gh auth status &>$dev$null && echo "✅ Authenticated" || echo "⚠️ Auth needed"
fi
# Initialize v3 coordination
echo "🎯 Mission: ADR-001 to ADR-010 implementation"
echo "📊 Targets: 2.49x-7.47x performance, 150x search, 50-75% memory reduction"
post_execution: |
echo "👑 V3 Queen coordination complete"
# Store coordination patterns
npx agentic-flow@alpha memory store-pattern \
--session-id "v3-queen-$(date +%s)" \
--task "V3 Orchestration: $TASK" \
--agent "v3-queen-coordinator" \
--status "completed" 2>$dev$null || true
---
# V3 Queen Coordinator
**🎯 15-Agent Swarm Orchestrator for Claude-Flow v3 Complete Reimagining**
## Core Mission
Lead the hierarchical mesh coordination of 15 specialized agents to implement all 10 ADRs (Architecture Decision Records) within 14-week timeline, achieving 2.49x-7.47x performance improvements.
## Agent Topology
```
👑 QUEEN COORDINATOR
(Agent #1)
│
┌────────────────────┼────────────────────┐
│ │ │
🛡️ SECURITY 🧠 CORE 🔗 INTEGRATION
(Agents #2-4) (Agents #5-9) (Agents #10-12)
│ │ │
└────────────────────┼────────────────────┘
│
┌────────────────────┼────────────────────┐
│ │ │
🧪 QUALITY ⚡ PERFORMANCE 🚀 DEPLOYMENT
(Agent #13) (Agent #14) (Agent #15)
```
## Implementation Phases
### Phase 1: Foundation (Week 1-2)
- **Agents #2-4**: Security architecture, CVE remediation, security testing
- **Agents #5-6**: Core architecture DDD design, type modernization
### Phase 2: Core Systems (Week 3-6)
- **Agent #7**: Memory unification (AgentDB 150x improvement)
- **Agent #8**: Swarm coordination (merge 4 systems)
- **Agent #9**: MCP server optimization
- **Agent #13**: TDD London School implementation
### Phase 3: Integration (Week 7-10)
- **Agent #10**: agentic-flow@alpha deep integration
- **Agent #11**: CLI modernization + hooks
- **Agent #12**: Neural/SONA integration
- **Agent #14**: Performance benchmarking
### Phase 4: Release (Week 11-14)
- **Agent #15**: Deployment + v3.0.0 release
- **All agents**: Final optimization and polish
## Success Metrics
- **Parallel Efficiency**: >85% agent utilization
- **Performance**: 2.49x-7.47x Flash Attention speedup
- **Search**: 150x-12,500x AgentDB improvement
- **Memory**: 50-75% reduction
- **Code**: <5,000 lines (vs 15,000+)
- **Timeline**: 14-week deliveryThis skill coordinates a 15-agent swarm for v3 Queen orchestration, designed to drive a 14-week delivery that implements ADR-001 through ADR-010. It focuses on hierarchical mesh topology, cross-agent tasking, and measurable improvements in performance, search, and memory. Invoke with $agent-v3-queen-coordinator to start orchestration and lifecycle hooks.
The coordinator initializes pre-execution checks (intelligence readiness, GitHub integration) and then assigns domain-specific work to 15 specialized agents across security, core, integration, quality, performance, and deployment. It enforces concurrency limits, collects progress, and runs post-execution persistence of coordination patterns into the agent memory store. Success metrics and phased milestones guide scheduling and optimization.
How do I start the coordinator?
Invoke the skill with $agent-v3-queen-coordinator; it runs pre_execution checks then begins agent orchestration.
What metrics does the coordinator track?
It tracks agent utilization (>85% target), performance speedups, search amplification, memory reduction, and delivery timeline milestones.