Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
ruvnet avatar

Agent V3 Integration Architect

  • 997 installs
  • 67k repo stars
  • Updated August 4, 2026
  • ruvnet/ruflo

agent-v3-integration-architect is an agent skill at version 3.0.0-alpha that architects deep integrations between agentic systems and eliminates large-scale code duplication for developers consolidating multi-agent frame

About

agent-v3-integration-architect is a Ruflo V3 architect agent skill at version 3.0.0-alpha updated 2026-01-04 for deep agentic-flow@alpha integration. The skill implements ADR-001 to eliminate 10,000+ duplicate lines and positions claude-flow as a specialized extension rather than a parallel implementation. Developers reach for agent-v3-integration-architect when multiple agentic codebases overlap and need a unified integration boundary instead of forked maintenance. The agent carries architect role metadata with agent_id 10, high priority, and integration-phase hooks that start agentic-flow deep integration on execution.

  • Implements ADR-001 to eliminate 10,000+ duplicate lines of agent code
  • Maps and consolidates overlapping components such as SwarmCoordinator vs Swarm System (80% overlap)
  • Performs pre-execution environment checks for agentic-flow@alpha availability
  • Stores reusable integration patterns in memory after successful execution
  • Provides structured v3_role architect guidance for agentic-flow@alpha deep integration

Agent V3 Integration Architect by the numbers

  • 997 all-time installs (skills.sh)
  • +3 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #1,085 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Security screen: HIGH risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/ruvnet/ruflo --skill agent-v3-integration-architect

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs997
repo stars67k
Security audit1 / 3 scanners passed
Last updatedAugust 4, 2026
Repositoryruvnet/ruflo

How do you integrate multiple agentic frameworks without duplication?

Architect clean, deep integrations between multiple agentic systems while eliminating massive code duplication.

Who is it for?

Developers merging ruflo, agentic-flow, or claude-flow codebases who need ADR-driven integration architecture instead of parallel forks.

Skip if: Developers building a greenfield single-agent CLI with no overlapping agent framework code to consolidate.

When should I use this skill?

Multiple agentic systems share duplicated code, agentic-flow@alpha integration is required, or ADR-level architecture decisions are needed.

What you get

ADR-001 integration plans, deduplicated module boundaries, agentic-flow extension architecture, and consolidated claude-flow integration designs.

  • Integration architecture design
  • ADR-001 implementation plan
  • Deduplicated module boundaries

By the numbers

  • Targets elimination of 10,000+ duplicate lines per ADR-001
  • Version 3.0.0-alpha with agent_id 10 in ruflo metadata

Files

SKILL.mdMarkdownGitHub ↗

--- 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',
  modes: ['real-time', 'balanced', 'research', 'edge', 'batch']
};

Backward Compatibility Strategy

Gradual Migration Approach

class 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();
  }
}

Success Metrics & Validation

Code Reduction Targets

  • [ ] Total Lines: <5,000 orchestration (vs 15,000+)
  • [ ] SwarmCoordinator: Eliminated (800+ lines)
  • [ ] AgentManager: Eliminated (1,736+ lines)
  • [ ] TaskScheduler: Eliminated (500+ lines)
  • [ ] Duplicate Logic: <5% remaining

Performance Targets

  • [ ] Flash Attention: 2.49x-7.47x speedup validated
  • [ ] Search Performance: 150x-12,500x improvement
  • [ ] Memory Usage: 50-75% reduction
  • [ ] SONA Adaptation: <0.05ms response time

Feature Parity

  • [ ] 100% Feature Compatibility: All v2 features available
  • [ ] API Compatibility: Backward compatible interfaces
  • [ ] Performance: No regression, ideally improvement
  • [ ] Documentation: Migration guide complete

Coordination Points

Memory Specialist (Agent #7)

  • AgentDB integration coordination
  • Cross-agent memory sharing setup
  • Performance benchmarking collaboration

Swarm Specialist (Agent #8)

  • Swarm system migration from claude-flow to agentic-flow
  • Topology coordination and optimization
  • Agent communication protocol alignment

Performance Engineer (Agent #14)

  • Performance target validation
  • Benchmark implementation for improvements
  • Regression testing for migration phases

Risk Mitigation

RiskLikelihoodImpactMitigation
agentic-flow breaking changesMediumHighPin version, maintain adapter
Performance regressionLowMediumContinuous benchmarking
Feature limitationsMediumMediumContribute upstream features
Migration complexityHighMediumPhased approach, compatibility layer

Related skills

How it compares

Choose this over generic refactoring skills when the goal is framework-level ADR integration across agentic systems rather than local file cleanup.

FAQ

What duplication does agent-v3-integration-architect target?

agent-v3-integration-architect implements ADR-001 to eliminate 10,000+ duplicate lines between agentic-flow and claude-flow implementations. The skill designs claude-flow as a specialized extension rather than maintaining parallel codepaths.

What version is the V3 integration architect skill?

agent-v3-integration-architect is version 3.0.0-alpha updated 2026-01-04 in the ruflo roster. The agent carries architect role metadata with agent_id 10 and high priority for integration-phase work.

Is Agent V3 Integration Architect safe to install?

skills.sh reports 1 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

AI & Agent Buildingagentsautomation

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.