Restores the entire .claude/ infrastructure that was accidentally deleted
in commit 1df208d ('feat(timeline): add pulse animation for in-flight drag
mutations'). Recovered via git checkout 1df208d^.
Restored:
- .claude/commands/ (gitlooper, sparc/, github/, automation/, monitoring/,
optimization/, hooks/, plan, implement, research, review, perf, visualaudit)
- .claude/agents/ (core/, github/, sparc/, v3/, swarm/, templates/, ...)
- .claude/helpers/ (41 scripts incl. hook-handler.cjs, statusline.cjs)
- .claude/skills/ (20 skills incl. sparc-methodology, github-*, v3-*)
- .claude/settings.json (hooks configuration)
Also updated all CapaKraken → Nexus references in affected command files.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
259 lines
7.1 KiB
Markdown
259 lines
7.1 KiB
Markdown
---
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name: "V3 Deep Integration"
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description: "Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation."
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---
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# V3 Deep Integration
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## What This Skill Does
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Transforms claude-flow from parallel implementation to specialized extension of agentic-flow@alpha, eliminating massive code duplication while achieving performance improvements and feature parity.
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## Quick Start
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```bash
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# Initialize deep integration
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Task("Integration architecture", "Design agentic-flow@alpha adapter layer", "v3-integration-architect")
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# Feature integration (parallel)
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Task("SONA integration", "Integrate 5 SONA learning modes", "v3-integration-architect")
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Task("Flash Attention", "Implement 2.49x-7.47x speedup", "v3-integration-architect")
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Task("AgentDB coordination", "Setup 150x-12,500x search", "v3-integration-architect")
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```
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## Code Deduplication Strategy
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### Current Overlap → Integration
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```
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┌─────────────────────────────────────────┐
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│ claude-flow agentic-flow │
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├─────────────────────────────────────────┤
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│ SwarmCoordinator → Swarm System │ 80% overlap (eliminate)
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│ AgentManager → Agent Lifecycle │ 70% overlap (eliminate)
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│ TaskScheduler → Task Execution │ 60% overlap (eliminate)
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│ SessionManager → Session Mgmt │ 50% overlap (eliminate)
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└─────────────────────────────────────────┘
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TARGET: <5,000 lines (vs 15,000+ currently)
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```
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## agentic-flow@alpha Feature Integration
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### SONA Learning Modes
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```typescript
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class SONAIntegration {
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async initializeMode(mode: SONAMode): Promise<void> {
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switch (mode) {
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case "real-time": // ~0.05ms adaptation
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case "balanced": // general purpose
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case "research": // deep exploration
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case "edge": // resource-constrained
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case "batch": // high-throughput
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}
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await this.agenticFlow.sona.setMode(mode);
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}
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}
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```
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### Flash Attention Integration
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```typescript
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class FlashAttentionIntegration {
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async optimizeAttention(): Promise<AttentionResult> {
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return this.agenticFlow.attention.flashAttention({
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speedupTarget: "2.49x-7.47x",
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memoryReduction: "50-75%",
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mechanisms: ["multi-head", "linear", "local", "global"],
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});
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}
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}
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```
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### AgentDB Coordination
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```typescript
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class AgentDBIntegration {
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async setupCrossAgentMemory(): Promise<void> {
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await this.agentdb.enableCrossAgentSharing({
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indexType: "HNSW",
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speedupTarget: "150x-12500x",
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dimensions: 1536,
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});
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}
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}
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```
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### MCP Tools Integration
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```typescript
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class MCPToolsIntegration {
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async integrateBuiltinTools(): Promise<void> {
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// Leverage 213 pre-built tools
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const tools = await this.agenticFlow.mcp.getAvailableTools();
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await this.registerClaudeFlowSpecificTools(tools);
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// Use 19 hook types
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const hookTypes = await this.agenticFlow.hooks.getTypes();
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await this.configureClaudeFlowHooks(hookTypes);
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}
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}
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```
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## Migration Implementation
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### Phase 1: Adapter Layer
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```typescript
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import { Agent as AgenticFlowAgent } from "agentic-flow@alpha";
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export class ClaudeFlowAgent extends AgenticFlowAgent {
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async handleClaudeFlowTask(task: ClaudeTask): Promise<TaskResult> {
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return this.executeWithSONA(task);
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}
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// Backward compatibility
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async legacyCompatibilityLayer(oldAPI: any): Promise<any> {
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return this.adaptToNewAPI(oldAPI);
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}
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}
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```
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### Phase 2: System Migration
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```typescript
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class SystemMigration {
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async migrateSwarmCoordination(): Promise<void> {
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// Replace SwarmCoordinator (800+ lines) with agentic-flow Swarm
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const swarmConfig = await this.extractSwarmConfig();
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await this.agenticFlow.swarm.initialize(swarmConfig);
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}
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async migrateAgentManagement(): Promise<void> {
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// Replace AgentManager (1,736+ lines) with agentic-flow lifecycle
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const agents = await this.extractActiveAgents();
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for (const agent of agents) {
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await this.agenticFlow.agent.create(agent);
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}
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}
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async migrateTaskExecution(): Promise<void> {
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// Replace TaskScheduler with agentic-flow task graph
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const tasks = await this.extractTasks();
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await this.agenticFlow.task.executeGraph(this.buildTaskGraph(tasks));
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}
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}
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```
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### Phase 3: Cleanup
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```typescript
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class CodeCleanup {
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async removeDeprecatedCode(): Promise<void> {
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// Remove massive duplicate implementations
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await this.removeFile("src/core/SwarmCoordinator.ts"); // 800+ lines
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await this.removeFile("src/agents/AgentManager.ts"); // 1,736+ lines
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await this.removeFile("src/task/TaskScheduler.ts"); // 500+ lines
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// Total reduction: 10,000+ → <5,000 lines
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}
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}
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```
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## RL Algorithm Integration
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```typescript
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class RLIntegration {
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algorithms = [
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"PPO",
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"DQN",
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"A2C",
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"MCTS",
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"Q-Learning",
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"SARSA",
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"Actor-Critic",
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"Decision-Transformer",
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];
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async optimizeAgentBehavior(): Promise<void> {
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for (const algorithm of this.algorithms) {
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await this.agenticFlow.rl.train(algorithm, {
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episodes: 1000,
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rewardFunction: this.claudeFlowRewardFunction,
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});
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}
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}
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}
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```
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## Performance Integration
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### Flash Attention Targets
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```typescript
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const attentionBenchmark = {
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baseline: "current attention mechanism",
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target: "2.49x-7.47x improvement",
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memoryReduction: "50-75%",
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implementation: "agentic-flow@alpha Flash Attention",
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};
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```
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### AgentDB Search Performance
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```typescript
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const searchBenchmark = {
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baseline: "linear search in current systems",
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target: "150x-12,500x via HNSW indexing",
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implementation: "agentic-flow@alpha AgentDB",
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};
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```
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## Backward Compatibility
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### Gradual Migration
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```typescript
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class BackwardCompatibility {
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// Phase 1: Dual operation
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async enableDualOperation(): Promise<void> {
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this.oldSystem.continue();
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this.newSystem.initialize();
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this.syncState(this.oldSystem, this.newSystem);
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}
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// Phase 2: Feature-by-feature migration
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async migrateGradually(): Promise<void> {
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const features = this.getAllFeatures();
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for (const feature of features) {
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await this.migrateFeature(feature);
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await this.validateFeatureParity(feature);
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}
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}
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// Phase 3: Complete transition
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async completeTransition(): Promise<void> {
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await this.validateFullParity();
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await this.deprecateOldSystem();
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}
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}
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```
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## Success Metrics
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- **Code Reduction**: <5,000 lines orchestration (vs 15,000+)
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- **Performance**: 2.49x-7.47x Flash Attention speedup
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- **Search**: 150x-12,500x AgentDB improvement
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- **Memory**: 50-75% usage reduction
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- **Feature Parity**: 100% v2 functionality maintained
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- **SONA**: <0.05ms adaptation time
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- **Integration**: All 213 MCP tools + 19 hook types available
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## Related V3 Skills
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- `v3-memory-unification` - Memory system integration
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- `v3-performance-optimization` - Performance target validation
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- `v3-swarm-coordination` - Swarm system migration
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- `v3-security-overhaul` - Secure integration patterns
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