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Get Started Free →Agent skill for v3-integration-architect - invoke with $agent-v3-integration-architect
.claude/skills/agent-v3-integration-architect/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | — | — |
| case-17 | ✗→✓ | ▲ Improved | — | — |
| case-10 | ✗→✓ | ▲ Improved | — | — |
| case-02 | ✗→✓ | ▲ Improved | — | — |
| case-21 | ✗→✓ | ▲ Improved | — | — |
🔗 agentic-flow@alpha Deep Integration & Code Deduplication Specialist
Transform claude-flow from parallel implementation to specialized extension of agentic-flow, eliminating 10,000+ lines of duplicate code while achieving 100% feature parity and performance improvements.
┌─────────────────────────────────────────┐
│ FUNCTIONALITY OVERLAP │
├─────────────────────────────────────────┤
│ claude-flow agentic-flow │
├─────────────────────────────────────────┤
│ SwarmCoordinator → Swarm System │ 80% overlap
│ AgentManager → Agent Lifecycle │ 70% overlap
│ TaskScheduler → Task Execution │ 60% overlap
│ SessionManager → Session Mgmt │ 50% overlap
└─────────────────────────────────────────┘
TARGET: <5,000 lines orchestration (vs 15,000+ currently)typescript// Phase 1: Adapter Layer Creation import { Agent as AgenticFlowAgent } from 'agentic-flow@alpha'; export class ClaudeFlowAgent extends AgenticFlowAgent { // Add claude-flow specific capabilities async handleClaudeFlowTask(task: ClaudeTask): Promise<TaskResult> { return this.executeWithSONA(task); } // Maintain backward compatibility async legacyCompatibilityLayer(oldAPI: any): Promise<any> { return this.adaptToNewAPI(oldAPI); } }
typescriptinterface SONAIntegration { modes: { realTime: '~0.05ms adaptation', balanced: 'general purpose learning', research: 'deep exploration mode', edge: 'resource-constrained environments', batch: 'high-throughput processing' }; } // Integration implementation class ClaudeFlowSONAAdapter { async initializeSONAMode(mode: SONAMode): Promise<void> { await this.agenticFlow.sona.setMode(mode); await this.configureAdaptationRate(mode); } }
typescript// Target: 2.49x-7.47x speedup class FlashAttentionIntegration { async optimizeAttention(): Promise<AttentionResult> { return this.agenticFlow.attention.flashAttention({ speedupTarget: '2.49x-7.47x', memoryReduction: '50-75%', mechanisms: ['multi-head', 'linear', 'local', 'global'] }); } }
typescript// 150x-12,500x faster search via HNSW class AgentDBIntegration { async setupCrossAgentMemory(): Promise<void> { await this.agentdb.enableCrossAgentSharing({ indexType: 'HNSW', dimensions: 1536, speedupTarget: '150x-12500x' }); } }
typescript// Leverage 213 pre-built tools + 19 hook types class MCPToolsIntegration { async integrateBuiltinTools(): Promise<void> { const tools = await this.agenticFlow.mcp.getAvailableTools(); // 213 tools available await this.registerClaudeFlowSpecificTools(tools); } async setupHookTypes(): Promise<void> { const hookTypes = await this.agenticFlow.hooks.getTypes(); // 19 hook types: pre$post execution, error handling, etc. await this.configureClaudeFlowHooks(hookTypes); } }
typescript// Multiple RL algorithms for optimization class RLIntegration { algorithms = [ 'PPO', 'DQN', 'A2C', 'MCTS', 'Q-Learning', 'SARSA', 'Actor-Critic', 'Decision-Transformer', 'Curiosity-Driven' ]; async optimizeAgentBehavior(): Promise<void> { for (const algorithm of this.algorithms) { await this.agenticFlow.rl.train(algorithm, { episodes: 1000, learningRate: 0.001, rewardFunction: this.claudeFlowRewardFunction }); } } }
typescript// Create compatibility layer class AgenticFlowAdapter { constructor(private agenticFlow: AgenticFlowCore) {} // Migrate SwarmCoordinator → Swarm System async migrateSwarmCoordination(): Promise<void> { const swarmConfig = await this.extractSwarmConfig(); await this.agenticFlow.swarm.initialize(swarmConfig); // Deprecate old SwarmCoordinator (800+ lines) } // Migrate AgentManager → Agent Lifecycle async migrateAgentManagement(): Promise<void> { const agents = await this.extractActiveAgents(); for (const agent of agents) { await this.agenticFlow.agent.create(agent); } // Deprecate old AgentManager (1,736 lines) } }
typescript// Migrate task execution class TaskExecutionMigration { async migrateToTaskGraph(): Promise<void> { const tasks = await this.extractTasks(); const taskGraph = this.buildTaskGraph(tasks); await this.agenticFlow.task.executeGraph(taskGraph); } } // Migrate session management class SessionMigration { async migrateSessionHandling(): Promise<void> { const sessions = await this.extractActiveSessions(); for (const session of sessions) { await this.agenticFlow.session.create(session); } } }
typescript// Remove compatibility layer class CompatibilityCleanup { async removeDeprecatedCode(): Promise<void> { // Remove old implementations await this.removeFile('src$core/SwarmCoordinator.ts'); // 800+ lines await this.removeFile('src$agents/AgentManager.ts'); // 1,736 lines await this.removeFile('src$task/TaskScheduler.ts'); // 500+ lines // Total code reduction: 10,000+ lines → <5,000 lines } }
typescript// Target: 2.49x-7.47x speedup const attentionBenchmark = { baseline: 'current attention mechanism', target: '2.49x-7.47x improvement', memoryReduction: '50-75%', implementation: 'agentic-flow@alpha Flash Attention' };
typescript// Target: 150x-12,500x improvement const searchBenchmark = { baseline: 'linear search in current memory systems', target: '150x-12,500x via HNSW indexing', implementation: 'agentic-flow@alpha AgentDB' };
typescript// Target: <0.05ms adaptation const sonaBenchmark = { baseline: 'no real-time learning', target: '<0.05ms adaptation time', modes: ['real-time', 'balanced', 'research', 'edge', 'batch'] };
typescriptclass BackwardCompatibility { // Phase 1: Dual operation (old + new) async enableDualOperation(): Promise<void> { this.oldSystem.continue(); this.newSystem.initialize(); this.syncState(this.oldSystem, this.newSystem); } // Phase 2: Gradual switchover async migrateGradually(): Promise<void> { const features = this.getAllFeatures(); for (const feature of features) { await this.migrateFeature(feature); await this.validateFeatureParity(feature); } } // Phase 3: Complete migration async completeTransition(): Promise<void> { await this.validateFullParity(); await this.deprecateOldSystem(); } }
| Risk | Likelihood | Impact | Mitigation | |------|------------|--------|------------| | agentic-flow breaking changes | Medium | High | Pin version, maintain adapter | | Performance regression | Low | Medium | Continuous benchmarking | | Feature limitations | Medium | Medium | Contribute upstream features | | Migration complexity | High | Medium | Phased approach, compatibility layer |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 20 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +64 percentage points is the difference between those two pass rates over the 20 comparable cases.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.