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.

41 stars

Best use case

V3 Swarm Coordination is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using V3 Swarm Coordination should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/v3-swarm-coordination/SKILL.md --create-dirs "https://raw.githubusercontent.com/spencermarx/open-code-review/main/.claude/skills/v3-swarm-coordination/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/v3-swarm-coordination/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How V3 Swarm Coordination Compares

Feature / AgentV3 Swarm CoordinationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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 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
```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 swarm
Task("V3 swarm initialization",
     "Initialize 15-agent hierarchical mesh for complete v3 implementation",
     "v3-queen-coordinator")
```

### Phase-based Execution
```bash
# 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
```

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