Ruflo V3 Swarm Coordination
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
install
source · Clone the upstream repo
git clone https://github.com/ruvnet/ruflo
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ruvnet/ruflo "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.agents/skills/v3-swarm-coordination" ~/.claude/skills/ruvnet-ruflo-v3-swarm-coordination && rm -rf "$T"
manifest:
.agents/skills/v3-swarm-coordination/SKILL.mdtags
source content
V3 Swarm Coordination
What This Skill Does
Orchestrates the complete 15-agent hierarchical mesh swarm for claude-flow v3 implementation, coordinating parallel execution across domains while maintaining dependencies and timeline adherence.
Quick Start
# Initialize 15-agent v3 swarm Task("Swarm initialization", "Initialize hierarchical mesh for v3 implementation", "v3-queen-coordinator") # Security domain (Phase 1 - Critical priority) Task("Security architecture", "Design v3 threat model and security boundaries", "v3-security-architect") Task("CVE remediation", "Fix CVE-1, CVE-2, CVE-3 vulnerabilities", "security-auditor") Task("Security testing", "Implement TDD security framework", "test-architect") # Core domain (Phase 2 - Parallel execution) Task("Memory unification", "Implement AgentDB 150x improvement", "v3-memory-specialist") Task("Integration architecture", "Deep agentic-flow@alpha integration", "v3-integration-architect") Task("Performance validation", "Validate 2.49x-7.47x targets", "v3-performance-engineer")
15-Agent Swarm Architecture
Hierarchical Mesh 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)
Agent Roster
| ID | Agent | Domain | Phase | Responsibility |
|---|---|---|---|---|
| 1 | Queen Coordinator | Orchestration | All | GitHub issues, dependencies, timeline |
| 2 | Security Architect | Security | Foundation | Threat modeling, CVE planning |
| 3 | Security Implementer | Security | Foundation | CVE fixes, secure patterns |
| 4 | Security Tester | Security | Foundation | TDD security testing |
| 5 | Core Architect | Core | Systems | DDD architecture, coordination |
| 6 | Core Implementer | Core | Systems | Core module implementation |
| 7 | Memory Specialist | Core | Systems | AgentDB unification |
| 8 | Swarm Specialist | Core | Systems | Unified coordination engine |
| 9 | MCP Specialist | Core | Systems | MCP server optimization |
| 10 | Integration Architect | Integration | Integration | agentic-flow@alpha deep integration |
| 11 | CLI/Hooks Developer | Integration | Integration | CLI modernization |
| 12 | Neural/Learning Dev | Integration | Integration | SONA integration |
| 13 | TDD Test Engineer | Quality | All | London School TDD |
| 14 | Performance Engineer | Performance | Optimization | Benchmarking validation |
| 15 | Release Engineer | Deployment | Release | CI/CD and v3.0.0 release |
Implementation Phases
Phase 1: Foundation (Week 1-2)
Active Agents: #1, #2-4, #5-6
const phase1 = async () => { // Parallel security and architecture foundation await Promise.all([ // Security domain (critical priority) Task("Security architecture", "Complete threat model and security boundaries", "v3-security-architect"), Task("CVE-1 fix", "Update vulnerable dependencies", "security-implementer"), Task("CVE-2 fix", "Replace weak password hashing", "security-implementer"), Task("CVE-3 fix", "Remove hardcoded credentials", "security-implementer"), Task("Security testing", "TDD London School security framework", "test-architect"), // Core architecture foundation Task("DDD architecture", "Design domain boundaries and structure", "core-architect"), Task("Type modernization", "Update type system for v3", "core-implementer") ]); };
Phase 2: Core Systems (Week 3-6)
Active Agents: #1, #5-9, #13
const phase2 = async () => { // Parallel core system implementation await Promise.all([ Task("Memory unification", "Implement AgentDB with 150x-12,500x improvement", "v3-memory-specialist"), Task("Swarm coordination", "Merge 4 coordination systems into unified engine", "swarm-specialist"), Task("MCP optimization", "Optimize MCP server performance", "mcp-specialist"), Task("Core implementation", "Implement DDD modular architecture", "core-implementer"), Task("TDD core tests", "Comprehensive test coverage for core systems", "test-architect") ]); };
Phase 3: Integration (Week 7-10)
Active Agents: #1, #10-12, #13-14
const phase3 = async () => { // Parallel integration and optimization await Promise.all([ Task("agentic-flow integration", "Eliminate 10,000+ duplicate lines", "v3-integration-architect"), Task("CLI modernization", "Enhance CLI with hooks system", "cli-hooks-developer"), Task("SONA integration", "Implement <0.05ms learning adaptation", "neural-learning-developer"), Task("Performance benchmarking", "Validate 2.49x-7.47x targets", "v3-performance-engineer"), Task("Integration testing", "End-to-end system validation", "test-architect") ]); };
Phase 4: Release (Week 11-14)
Active Agents: All 15
const phase4 = async () => { // Full swarm final optimization await Promise.all([ Task("Performance optimization", "Final optimization pass", "v3-performance-engineer"), Task("Release preparation", "CI/CD pipeline and v3.0.0 release", "release-engineer"), Task("Final testing", "Complete test coverage validation", "test-architect"), // All agents: Final polish and optimization ...agents.map(agent => Task("Final polish", `Agent ${agent.id} final optimization`, agent.name) ) ]); };
Coordination Patterns
Dependency Management
class DependencyCoordination { private dependencies = new Map([ // Security first (no dependencies) [2, []], [3, [2]], [4, [2, 3]], // Core depends on security foundation [5, [2]], [6, [5]], [7, [5]], [8, [5, 7]], [9, [5]], // Integration depends on core systems [10, [5, 7, 8]], [11, [5, 10]], [12, [7, 10]], // Quality and performance cross-cutting [13, [2, 5]], [14, [5, 7, 8, 10]], [15, [13, 14]] ]); async coordinateExecution(): Promise<void> { const completed = new Set<number>(); while (completed.size < 15) { const ready = this.getReadyAgents(completed); if (ready.length === 0) { throw new Error('Deadlock detected in dependency chain'); } // Execute ready agents in parallel await Promise.all(ready.map(agentId => this.executeAgent(agentId))); ready.forEach(id => completed.add(id)); } } }
GitHub Integration
class GitHubCoordination { async initializeV3Milestone(): Promise<void> { await gh.createMilestone({ title: 'Claude-Flow v3.0.0 Implementation', description: '15-agent swarm implementation of 10 ADRs', dueDate: this.calculate14WeekDeadline() }); } async createEpicIssues(): Promise<void> { const epics = [ { title: 'Security Overhaul (CVE-1,2,3)', agents: [2, 3, 4] }, { title: 'Memory Unification (AgentDB)', agents: [7] }, { title: 'agentic-flow Integration', agents: [10] }, { title: 'Performance Optimization', agents: [14] }, { title: 'DDD Architecture', agents: [5, 6] } ]; for (const epic of epics) { await gh.createIssue({ title: epic.title, labels: ['epic', 'v3', ...epic.agents.map(id => `agent-${id}`)], assignees: epic.agents.map(id => this.getAgentGithubUser(id)) }); } } async trackProgress(): Promise<void> { // Hourly progress updates from each agent setInterval(async () => { for (const agent of this.agents) { await this.postAgentProgress(agent); } }, 3600000); // 1 hour } }
Communication Bus
class SwarmCommunication { private bus = new QuicSwarmBus({ maxAgents: 15, messageTimeout: 30000, retryAttempts: 3 }); async broadcastToSecurityDomain(message: SwarmMessage): Promise<void> { await this.bus.broadcast(message, { targetAgents: [2, 3, 4], priority: 'critical' }); } async coordinateCoreSystems(message: SwarmMessage): Promise<void> { await this.bus.broadcast(message, { targetAgents: [5, 6, 7, 8, 9], priority: 'high' }); } async notifyIntegrationTeam(message: SwarmMessage): Promise<void> { await this.bus.broadcast(message, { targetAgents: [10, 11, 12], priority: 'medium' }); } }
Performance Coordination
Parallel Efficiency Monitoring
class EfficiencyMonitor { async measureParallelEfficiency(): Promise<EfficiencyReport> { const agentUtilization = await this.measureAgentUtilization(); const coordinationOverhead = await this.measureCoordinationCost(); return { totalEfficiency: agentUtilization.average, target: 0.85, // >85% utilization achieved: agentUtilization.average > 0.85, bottlenecks: this.identifyBottlenecks(agentUtilization), recommendations: this.generateOptimizations() }; } }
Load Balancing
class SwarmLoadBalancer { async balanceWorkload(): Promise<void> { const workloads = await this.analyzeAgentWorkloads(); for (const [agentId, load] of workloads.entries()) { if (load > this.getCapacityThreshold(agentId)) { await this.redistributeWork(agentId); } } } async redistributeWork(overloadedAgent: number): Promise<void> { const availableAgents = this.getAvailableAgents(); const tasks = await this.getAgentTasks(overloadedAgent); // Redistribute tasks to available agents for (const task of tasks) { const bestAgent = this.selectOptimalAgent(task, availableAgents); await this.reassignTask(task, bestAgent); } } }
Success Metrics
Swarm Coordination
- Parallel Efficiency: >85% agent utilization time
- Dependency Resolution: Zero deadlocks or blocking issues
- Communication Latency: <100ms inter-agent messaging
- Timeline Adherence: 14-week delivery maintained
- GitHub Integration: <4h automated issue response
Implementation Targets
- ADR Coverage: All 10 ADRs implemented successfully
- Performance: 2.49x-7.47x Flash Attention achieved
- Search: 150x-12,500x AgentDB improvement validated
- Code Reduction: <5,000 lines (vs 15,000+)
- Security: 90/100 security score achieved
Related V3 Skills
- Security domain coordinationv3-security-overhaul
- Memory system coordinationv3-memory-unification
- Integration domain coordinationv3-integration-deep
- Performance domain coordinationv3-performance-optimization
Usage Examples
Initialize Complete V3 Swarm
# Queen Coordinator initializes full swarm Task("V3 swarm initialization", "Initialize 15-agent hierarchical mesh for complete v3 implementation", "v3-queen-coordinator")
Phase-based Execution
# Phase 1: Security-first foundation npm run v3:phase1:security # Phase 2: Core systems parallel npm run v3:phase2:core-systems # Phase 3: Integration and optimization npm run v3:phase3:integration # Phase 4: Release preparation npm run v3:phase4:release