Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment
340 lines
12 KiB
Markdown
340 lines
12 KiB
Markdown
---
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name: "V3 Swarm Coordination"
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description: "15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline."
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---
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# V3 Swarm Coordination
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## What This Skill Does
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Orchestrates the complete 15-agent hierarchical mesh swarm for claude-flow v3 implementation, coordinating parallel execution across domains while maintaining dependencies and timeline adherence.
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## Quick Start
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```bash
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# Initialize 15-agent v3 swarm
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Task("Swarm initialization", "Initialize hierarchical mesh for v3 implementation", "v3-queen-coordinator")
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# Security domain (Phase 1 - Critical priority)
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Task("Security architecture", "Design v3 threat model and security boundaries", "v3-security-architect")
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Task("CVE remediation", "Fix CVE-1, CVE-2, CVE-3 vulnerabilities", "security-auditor")
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Task("Security testing", "Implement TDD security framework", "test-architect")
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# Core domain (Phase 2 - Parallel execution)
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Task("Memory unification", "Implement AgentDB 150x improvement", "v3-memory-specialist")
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Task("Integration architecture", "Deep agentic-flow@alpha integration", "v3-integration-architect")
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Task("Performance validation", "Validate 2.49x-7.47x targets", "v3-performance-engineer")
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```
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## 15-Agent Swarm Architecture
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### Hierarchical Mesh Topology
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```
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👑 QUEEN COORDINATOR
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(Agent #1)
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│
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┌────────────────────┼────────────────────┐
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│ │ │
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🛡️ SECURITY 🧠 CORE 🔗 INTEGRATION
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(Agents #2-4) (Agents #5-9) (Agents #10-12)
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│ │ │
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└────────────────────┼────────────────────┘
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│
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┌────────────────────┼────────────────────┐
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│ │ │
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🧪 QUALITY ⚡ PERFORMANCE 🚀 DEPLOYMENT
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(Agent #13) (Agent #14) (Agent #15)
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```
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### Agent Roster
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| ID | Agent | Domain | Phase | Responsibility |
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|----|-------|--------|-------|----------------|
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| 1 | Queen Coordinator | Orchestration | All | GitHub issues, dependencies, timeline |
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| 2 | Security Architect | Security | Foundation | Threat modeling, CVE planning |
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| 3 | Security Implementer | Security | Foundation | CVE fixes, secure patterns |
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| 4 | Security Tester | Security | Foundation | TDD security testing |
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| 5 | Core Architect | Core | Systems | DDD architecture, coordination |
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| 6 | Core Implementer | Core | Systems | Core module implementation |
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| 7 | Memory Specialist | Core | Systems | AgentDB unification |
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| 8 | Swarm Specialist | Core | Systems | Unified coordination engine |
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| 9 | MCP Specialist | Core | Systems | MCP server optimization |
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| 10 | Integration Architect | Integration | Integration | agentic-flow@alpha deep integration |
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| 11 | CLI/Hooks Developer | Integration | Integration | CLI modernization |
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| 12 | Neural/Learning Dev | Integration | Integration | SONA integration |
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| 13 | TDD Test Engineer | Quality | All | London School TDD |
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| 14 | Performance Engineer | Performance | Optimization | Benchmarking validation |
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| 15 | Release Engineer | Deployment | Release | CI/CD and v3.0.0 release |
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## Implementation Phases
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### Phase 1: Foundation (Week 1-2)
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**Active Agents**: #1, #2-4, #5-6
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```typescript
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const phase1 = async () => {
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// Parallel security and architecture foundation
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await Promise.all([
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// Security domain (critical priority)
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Task("Security architecture", "Complete threat model and security boundaries", "v3-security-architect"),
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Task("CVE-1 fix", "Update vulnerable dependencies", "security-implementer"),
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Task("CVE-2 fix", "Replace weak password hashing", "security-implementer"),
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Task("CVE-3 fix", "Remove hardcoded credentials", "security-implementer"),
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Task("Security testing", "TDD London School security framework", "test-architect"),
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// Core architecture foundation
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Task("DDD architecture", "Design domain boundaries and structure", "core-architect"),
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Task("Type modernization", "Update type system for v3", "core-implementer")
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]);
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};
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```
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### Phase 2: Core Systems (Week 3-6)
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**Active Agents**: #1, #5-9, #13
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```typescript
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const phase2 = async () => {
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// Parallel core system implementation
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await Promise.all([
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Task("Memory unification", "Implement AgentDB with 150x-12,500x improvement", "v3-memory-specialist"),
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Task("Swarm coordination", "Merge 4 coordination systems into unified engine", "swarm-specialist"),
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Task("MCP optimization", "Optimize MCP server performance", "mcp-specialist"),
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Task("Core implementation", "Implement DDD modular architecture", "core-implementer"),
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Task("TDD core tests", "Comprehensive test coverage for core systems", "test-architect")
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]);
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};
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```
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### Phase 3: Integration (Week 7-10)
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**Active Agents**: #1, #10-12, #13-14
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```typescript
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const phase3 = async () => {
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// Parallel integration and optimization
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await Promise.all([
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Task("agentic-flow integration", "Eliminate 10,000+ duplicate lines", "v3-integration-architect"),
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Task("CLI modernization", "Enhance CLI with hooks system", "cli-hooks-developer"),
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Task("SONA integration", "Implement <0.05ms learning adaptation", "neural-learning-developer"),
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Task("Performance benchmarking", "Validate 2.49x-7.47x targets", "v3-performance-engineer"),
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Task("Integration testing", "End-to-end system validation", "test-architect")
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]);
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};
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```
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### Phase 4: Release (Week 11-14)
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**Active Agents**: All 15
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```typescript
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const phase4 = async () => {
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// Full swarm final optimization
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await Promise.all([
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Task("Performance optimization", "Final optimization pass", "v3-performance-engineer"),
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Task("Release preparation", "CI/CD pipeline and v3.0.0 release", "release-engineer"),
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Task("Final testing", "Complete test coverage validation", "test-architect"),
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// All agents: Final polish and optimization
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...agents.map(agent =>
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Task("Final polish", `Agent ${agent.id} final optimization`, agent.name)
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)
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]);
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};
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```
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## Coordination Patterns
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### Dependency Management
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```typescript
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class DependencyCoordination {
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private dependencies = new Map([
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// Security first (no dependencies)
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[2, []], [3, [2]], [4, [2, 3]],
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// Core depends on security foundation
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[5, [2]], [6, [5]], [7, [5]], [8, [5, 7]], [9, [5]],
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// Integration depends on core systems
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[10, [5, 7, 8]], [11, [5, 10]], [12, [7, 10]],
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// Quality and performance cross-cutting
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[13, [2, 5]], [14, [5, 7, 8, 10]], [15, [13, 14]]
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]);
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async coordinateExecution(): Promise<void> {
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const completed = new Set<number>();
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while (completed.size < 15) {
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const ready = this.getReadyAgents(completed);
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if (ready.length === 0) {
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throw new Error('Deadlock detected in dependency chain');
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}
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// Execute ready agents in parallel
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await Promise.all(ready.map(agentId => this.executeAgent(agentId)));
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ready.forEach(id => completed.add(id));
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}
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}
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}
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```
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### GitHub Integration
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```typescript
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class GitHubCoordination {
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async initializeV3Milestone(): Promise<void> {
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await gh.createMilestone({
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title: 'Claude-Flow v3.0.0 Implementation',
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description: '15-agent swarm implementation of 10 ADRs',
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dueDate: this.calculate14WeekDeadline()
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});
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}
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async createEpicIssues(): Promise<void> {
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const epics = [
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{ title: 'Security Overhaul (CVE-1,2,3)', agents: [2, 3, 4] },
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{ title: 'Memory Unification (AgentDB)', agents: [7] },
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{ title: 'agentic-flow Integration', agents: [10] },
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{ title: 'Performance Optimization', agents: [14] },
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{ title: 'DDD Architecture', agents: [5, 6] }
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];
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for (const epic of epics) {
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await gh.createIssue({
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title: epic.title,
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labels: ['epic', 'v3', ...epic.agents.map(id => `agent-${id}`)],
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assignees: epic.agents.map(id => this.getAgentGithubUser(id))
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});
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}
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}
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async trackProgress(): Promise<void> {
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// Hourly progress updates from each agent
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setInterval(async () => {
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for (const agent of this.agents) {
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await this.postAgentProgress(agent);
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}
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}, 3600000); // 1 hour
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}
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}
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```
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### Communication Bus
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```typescript
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class SwarmCommunication {
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private bus = new QuicSwarmBus({
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maxAgents: 15,
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messageTimeout: 30000,
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retryAttempts: 3
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});
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async broadcastToSecurityDomain(message: SwarmMessage): Promise<void> {
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await this.bus.broadcast(message, {
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targetAgents: [2, 3, 4],
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priority: 'critical'
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});
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}
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async coordinateCoreSystems(message: SwarmMessage): Promise<void> {
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await this.bus.broadcast(message, {
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targetAgents: [5, 6, 7, 8, 9],
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priority: 'high'
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});
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}
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async notifyIntegrationTeam(message: SwarmMessage): Promise<void> {
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await this.bus.broadcast(message, {
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targetAgents: [10, 11, 12],
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priority: 'medium'
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});
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}
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}
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```
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## Performance Coordination
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### Parallel Efficiency Monitoring
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```typescript
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class EfficiencyMonitor {
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async measureParallelEfficiency(): Promise<EfficiencyReport> {
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const agentUtilization = await this.measureAgentUtilization();
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const coordinationOverhead = await this.measureCoordinationCost();
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return {
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totalEfficiency: agentUtilization.average,
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target: 0.85, // >85% utilization
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achieved: agentUtilization.average > 0.85,
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bottlenecks: this.identifyBottlenecks(agentUtilization),
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recommendations: this.generateOptimizations()
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};
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}
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}
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```
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### Load Balancing
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```typescript
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class SwarmLoadBalancer {
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async balanceWorkload(): Promise<void> {
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const workloads = await this.analyzeAgentWorkloads();
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for (const [agentId, load] of workloads.entries()) {
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if (load > this.getCapacityThreshold(agentId)) {
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await this.redistributeWork(agentId);
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}
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}
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}
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async redistributeWork(overloadedAgent: number): Promise<void> {
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const availableAgents = this.getAvailableAgents();
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const tasks = await this.getAgentTasks(overloadedAgent);
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// Redistribute tasks to available agents
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for (const task of tasks) {
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const bestAgent = this.selectOptimalAgent(task, availableAgents);
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await this.reassignTask(task, bestAgent);
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}
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}
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}
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```
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## Success Metrics
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### Swarm Coordination
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- [ ] **Parallel Efficiency**: >85% agent utilization time
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- [ ] **Dependency Resolution**: Zero deadlocks or blocking issues
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- [ ] **Communication Latency**: <100ms inter-agent messaging
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- [ ] **Timeline Adherence**: 14-week delivery maintained
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- [ ] **GitHub Integration**: <4h automated issue response
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### Implementation Targets
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- [ ] **ADR Coverage**: All 10 ADRs implemented successfully
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- [ ] **Performance**: 2.49x-7.47x Flash Attention achieved
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- [ ] **Search**: 150x-12,500x AgentDB improvement validated
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- [ ] **Code Reduction**: <5,000 lines (vs 15,000+)
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- [ ] **Security**: 90/100 security score achieved
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## Related V3 Skills
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- `v3-security-overhaul` - Security domain coordination
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- `v3-memory-unification` - Memory system coordination
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- `v3-integration-deep` - Integration domain coordination
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- `v3-performance-optimization` - Performance domain coordination
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## Usage Examples
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### Initialize Complete V3 Swarm
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```bash
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# Queen Coordinator initializes full swarm
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Task("V3 swarm initialization",
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"Initialize 15-agent hierarchical mesh for complete v3 implementation",
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"v3-queen-coordinator")
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```
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### Phase-based Execution
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```bash
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# Phase 1: Security-first foundation
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npm run v3:phase1:security
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# Phase 2: Core systems parallel
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npm run v3:phase2:core-systems
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# Phase 3: Integration and optimization
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npm run v3:phase3:integration
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# Phase 4: Release preparation
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npm run v3:phase4:release
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``` |