ruvnet/ruflo1 file

Agent V3 Integration Architect

Agent skill for v3-integration-architect - invoke with $agent-v3-integration-architect

Specification
Skill ID
ruvnet/ruflo/agent-v3-integration-architect
Publisher
ruvnet
Repository
ruflo
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

ruvnet/ruflo/agent-v3-integration-architectInstalls these files
  • SKILL.md

What this skill tells the agent


name: v3-integration-architect version: "3.0.0-alpha" updated: "2026-01-04" description: V3 Integration Architect for deep agentic-flow@alpha integration. Implements ADR-001 to eliminate 10,000+ duplicate lines and build claude-flow as specialized extension rather than parallel implementation. color: green metadata: v3_role: "architect" agent_id: 10 priority: "high" domain: "integration" phase: "integration" hooks: pre_execution: | echo "🔗 V3 Integration Architect starting agentic-flow@alpha deep integration..."

# Check agentic-flow status npx agentic-flow@alpha --version 2>$dev$null | head -1 || echo "⚠️ agentic-flow@alpha not available"

echo "🎯 ADR-001: Eliminate 10,000+ duplicate lines" echo "📊 Current duplicate functionality:" echo " • SwarmCoordinator vs Swarm System (80% overlap)" echo " • AgentManager vs Agent Lifecycle (70% overlap)" echo " • TaskScheduler vs Task Execution (60% overlap)" echo " • SessionManager vs Session Mgmt (50% overlap)"

# Check integration points ls -la services$agentic-flow-hooks/ 2>$dev$null | wc -l | xargs echo "🔧 Current hook integrations:"

post_execution: | echo "🔗 agentic-flow@alpha integration milestone complete"

# Store integration patterns npx agentic-flow@alpha memory store-pattern \ --session-id "v3-integration-$(date +%s)" \ --task "Integration: $TASK" \ --agent "v3-integration-architect" \ --code-reduction "10000+" 2>$dev$null || true ---

V3 Integration Architect

🔗 agentic-flow@alpha Deep Integration & Code Deduplication Specialist

Core Mission: ADR-001 Implementation

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.

Integration Strategy

Current Duplication Analysis

┌─────────────────────────────────────────┐
│         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)

Integration Architecture

// 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);
  }
}

agentic-flow@alpha Feature Integration

SONA Learning Modes

interface 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);
  }
}

Flash Attention Integration

// 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']
    });
  }
}

AgentDB Coordination

// 150x-12,500x faster search via HNSW
class AgentDBIntegration {
  async setupCrossAgentMemory(): Promise<void> {
    await this.agentdb.enableCrossAgentSharing({
      indexType: 'HNSW',
      dimensions: 1536,
      speedupTarget: '150x-12500x'
    });
  }
}

MCP Tools Integration

// 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);
  }
}

RL Algorithm Integration

// 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
      });
    }
  }
}

Migration Implementation Plan

Phase 1: Foundation Adapter (Week 7)

// 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)
  }
}

Phase 2: Core Migration (Week 8-9)

// 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);
    }
  }
}

Phase 3: Optimization (Week 10)

// 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
  }
}

Performance Integration Targets

Flash Attention Optimization

// 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'
};

AgentDB Search Performance

// 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'
};

SONA Learning Performance

// Target: <0.05ms adaptation
const sonaBenchmark = {
  baseline: 'no real-time learning',
  target: '<0.05ms adaptation time',

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