본문으로 건너뛰기
cccskills
무료GitHub에 공개

agent-v3-integration-architect

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills스타 3(GitHub 3 + cccskills 0)

실행 점수 미검증

설치 방법 보기

포함된 파일(1)

  • SKILL.md10.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.


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

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

Automate 2chat tasks via Rube MCP (Composio). Always search tools first for current schemas.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

1password

무료

Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

Build integrated IS/BS/CF financial workbooks in Excel.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

9router

무료

Entry point for 9Router — local/remote AI gateway with OpenAI-compatible REST for chat, image, TTS, embeddings, web search, web fetch. Use when the user mentions 9Router, NINEROUTER_URL, or wants AI without writing provider boilerplate. This skill covers setup + indexes capability skills; fetch the relevant capability SKILL.md from the URLs below when needed.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

karanmrn/karanagentskills32026년 8월 28일 업데이트

karanmrn의 스킬 모두 보기

이 스킬의 문제 신고