V3 Swarm Coordination

ruvnet/ruflo/v3/@claude-flow/cli/.claude/skills/v3-swarm-coordination

作者 ruvnet58e0ae7e14e68aab45a4127d6f42f567bbcfb328無授權條款74K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫今天更新

15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

AI 產生的概覽

協調 15 個代理的階層式叢集,規劃並執行橫跨安全、核心與整合領域的 14 週 v3 軟體實作。

功能
此技能提供編排 15 個代理階層式網狀叢集以完成 v3 實作的指示。它定義了包含角色與領域的代理名冊、四個實作階段與時程、相依性管理、GitHub 議題與里程碑協調、通訊匯流排,以及負載平衡與平行效率目標等效能監控。其產出是協調計畫與任務分派,而非檔案或程式碼成品。
適用情境
適用於規劃或執行大型多代理實作專案,且需要依安全、核心、整合、品質、效能與發佈等領域拆分時。也適合需要分階段排程、相依性排序,以及跨多個平行代理追蹤進度的工作。
執行需求
僅為指示,不隨附指令碼。它假定具備代理任務執行環境、用於里程碑與議題協調的 GitHub 存取權,以及用於分階段執行的 npm 指令碼。

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

bash
# Initialize 15-agent v3 swarmTask("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

IDAgentDomainPhaseResponsibility
1Queen CoordinatorOrchestrationAllGitHub issues, dependencies, timeline
2Security ArchitectSecurityFoundationThreat modeling, CVE planning
3Security ImplementerSecurityFoundationCVE fixes, secure patterns
4Security TesterSecurityFoundationTDD security testing
5Core ArchitectCoreSystemsDDD architecture, coordination
6Core ImplementerCoreSystemsCore module implementation
7Memory SpecialistCoreSystemsAgentDB unification
8Swarm SpecialistCoreSystemsUnified coordination engine
9MCP SpecialistCoreSystemsMCP server optimization
10Integration ArchitectIntegrationIntegrationagentic-flow@alpha deep integration
11CLI/Hooks DeveloperIntegrationIntegrationCLI modernization
12Neural/Learning DevIntegrationIntegrationSONA integration
13TDD Test EngineerQualityAllLondon School TDD
14Performance EngineerPerformanceOptimizationBenchmarking validation
15Release EngineerDeploymentReleaseCI/CD and v3.0.0 release

Implementation Phases

Phase 1: Foundation (Week 1-2)

Active Agents: #1, #2-4, #5-6

typescript
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

typescript
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

typescript
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

typescript
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

typescript
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

typescript
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

typescript
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

typescript
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

typescript
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

  • v3-security-overhaul - Security domain coordination
  • v3-memory-unification - Memory system coordination
  • v3-integration-deep - Integration domain coordination
  • v3-performance-optimization - Performance domain coordination

Usage Examples

Initialize Complete V3 Swarm

bash
# Queen Coordinator initializes full swarmTask("V3 swarm initialization",     "Initialize 15-agent hierarchical mesh for complete v3 implementation",     "v3-queen-coordinator")

Phase-based Execution

bash
# Phase 1: Security-first foundationnpm run v3:phase1:security
# Phase 2: Core systems parallelnpm run v3:phase2:core-systems
# Phase 3: Integration and optimizationnpm run v3:phase3:integration
# Phase 4: Release preparationnpm run v3:phase4:release

來源與署名

來源:ruvnet/ruflo位於v3/@claude-flow/cli/.claude/skills/v3-swarm-coordination提交58e0ae7

授權條款: 無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架