SKILL.md
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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
- `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
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