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Get Started Free →Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
.claude/skills/v3-performance-optimization/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-17 | ✗→✓ | ▲ Improved | — | — |
| case-15 | ✗→✓ | ▲ Improved | — | — |
| case-13 | ✗→✓ | ▲ Improved | — | — |
| case-11 | ✗→✓ | ▲ Improved | — | — |
| case-02 | ✗→✓ | ▲ Improved | — | — |
Validates and optimizes claude-flow v3 to achieve industry-leading performance through Flash Attention, AgentDB HNSW indexing, and comprehensive system optimization with continuous benchmarking.
bash# Initialize performance optimization Task("Performance baseline", "Establish v2 performance benchmarks", "v3-performance-engineer") # Target validation (parallel) Task("Flash Attention", "Validate 2.49x-7.47x speedup target", "v3-performance-engineer") Task("Search optimization", "Validate 150x-12,500x search improvement", "v3-performance-engineer") Task("Memory optimization", "Achieve 50-75% memory reduction", "v3-performance-engineer")
┌─────────────────────────────────────────┐
│ FLASH ATTENTION │
├─────────────────────────────────────────┤
│ Baseline: Standard attention │
│ Target: 2.49x - 7.47x speedup │
│ Memory: 50-75% reduction │
│ Latency: Sub-millisecond processing │
└─────────────────────────────────────────┘┌─────────────────────────────────────────┐
│ SEARCH OPTIMIZATION │
├─────────────────────────────────────────┤
│ Current: O(n) linear search │
│ Target: 150x - 12,500x improvement │
│ Method: HNSW indexing │
│ Latency: <100ms for 1M+ entries │
└─────────────────────────────────────────┘typescriptclass StartupBenchmarks { async benchmarkColdStart(): Promise<BenchmarkResult> { const startTime = performance.now(); await this.initializeCLI(); await this.initializeMCPServer(); await this.spawnTestAgent(); const totalTime = performance.now() - startTime; return { total: totalTime, target: 500, // ms achieved: totalTime < 500 }; } }
typescriptclass MemoryBenchmarks { async benchmarkVectorSearch(): Promise<SearchBenchmark> { const queries = this.generateTestQueries(10000); // Baseline: Current linear search const baselineTime = await this.timeOperation(() => this.currentMemory.searchAll(queries) ); // Target: HNSW search const hnswTime = await this.timeOperation(() => this.agentDBMemory.hnswSearchAll(queries) ); const improvement = baselineTime / hnswTime; return { baseline: baselineTime, hnsw: hnswTime, improvement, targetRange: [150, 12500], achieved: improvement >= 150 }; } async benchmarkMemoryUsage(): Promise<MemoryBenchmark> { const baseline = process.memoryUsage().heapUsed; await this.loadTestDataset(); const withData = process.memoryUsage().heapUsed; await this.enableOptimization(); const optimized = process.memoryUsage().heapUsed; const reduction = (withData - optimized) / withData; return { baseline, withData, optimized, reductionPercent: reduction * 100, targetReduction: [50, 75], achieved: reduction >= 0.5 }; } }
typescriptclass SwarmBenchmarks { async benchmark15AgentCoordination(): Promise<SwarmBenchmark> { const agents = await this.spawn15Agents(); // Coordination latency const coordinationTime = await this.timeOperation(() => this.coordinateSwarmTask(agents) ); // Task decomposition const decompositionTime = await this.timeOperation(() => this.decomposeComplexTask() ); // Consensus achievement const consensusTime = await this.timeOperation(() => this.achieveSwarmConsensus(agents) ); return { coordination: coordinationTime, decomposition: decompositionTime, consensus: consensusTime, agentCount: 15, efficiency: this.calculateEfficiency(agents) }; } }
typescriptclass AttentionBenchmarks { async benchmarkFlashAttention(): Promise<AttentionBenchmark> { const sequences = this.generateSequences([512, 1024, 2048, 4096]); const results = []; for (const sequence of sequences) { // Baseline attention const baselineResult = await this.benchmarkStandardAttention(sequence); // Flash attention const flashResult = await this.benchmarkFlashAttention(sequence); results.push({ sequenceLength: sequence.length, speedup: baselineResult.time / flashResult.time, memoryReduction: (baselineResult.memory - flashResult.memory) / baselineResult.memory, targetSpeedup: [2.49, 7.47], achieved: this.checkTarget(flashResult, [2.49, 7.47]) }); } return { results, averageSpeedup: this.calculateAverage(results, 'speedup'), averageMemoryReduction: this.calculateAverage(results, 'memoryReduction') }; } }
typescriptclass SONABenchmarks { async benchmarkAdaptationTime(): Promise<SONABenchmark> { const scenarios = [ 'pattern_recognition', 'task_optimization', 'error_correction', 'performance_tuning' ]; const results = []; for (const scenario of scenarios) { const startTime = performance.hrtime.bigint(); await this.sona.adapt(scenario); const endTime = performance.hrtime.bigint(); const adaptationTimeMs = Number(endTime - startTime) / 1000000; results.push({ scenario, adaptationTime: adaptationTimeMs, target: 0.05, // ms achieved: adaptationTimeMs <= 0.05 }); } return { scenarios: results, averageTime: results.reduce((sum, r) => sum + r.adaptationTime, 0) / results.length, successRate: results.filter(r => r.achieved).length / results.length }; } }
typescriptclass PerformanceMonitor { async collectMetrics(): Promise<PerformanceSnapshot> { return { timestamp: Date.now(), flashAttention: await this.measureFlashAttention(), searchPerformance: await this.measureSearchSpeed(), memoryUsage: await this.measureMemoryEfficiency(), startupTime: await this.measureStartupLatency(), sonaAdaptation: await this.measureSONASpeed(), swarmCoordination: await this.measureSwarmEfficiency() }; } async generateReport(): Promise<PerformanceReport> { const snapshot = await this.collectMetrics(); return { summary: this.generateSummary(snapshot), achievements: this.checkTargetAchievements(snapshot), trends: this.analyzeTrends(), recommendations: this.generateOptimizations(), regressions: await this.detectRegressions() }; } }
typescriptclass PerformanceRegression { async detectRegressions(): Promise<RegressionReport> { const current = await this.runFullBenchmark(); const baseline = await this.getBaseline(); const regressions = []; for (const [metric, currentValue] of Object.entries(current)) { const baselineValue = baseline[metric]; const change = (currentValue - baselineValue) / baselineValue; if (change < -0.05) { // 5% regression threshold regressions.push({ metric, baseline: baselineValue, current: currentValue, regressionPercent: change * 100, severity: this.classifyRegression(change) }); } } return { hasRegressions: regressions.length > 0, regressions, recommendations: this.generateRegressionFixes(regressions) }; } }
typescriptclass MemoryOptimization { async optimizeMemoryUsage(): Promise<OptimizationResult> { // Implement memory pooling await this.setupMemoryPools(); // Enable garbage collection tuning await this.optimizeGarbageCollection(); // Implement object reuse patterns await this.setupObjectPools(); // Enable memory compression await this.enableMemoryCompression(); return this.validateMemoryReduction(); } }
typescriptclass CPUOptimization { async optimizeCPUUsage(): Promise<OptimizationResult> { // Implement worker thread pools await this.setupWorkerThreads(); // Enable CPU-specific optimizations await this.enableSIMDInstructions(); // Implement task batching await this.optimizeTaskBatching(); return this.validateCPUImprovement(); } }
typescriptclass PerformanceGates { async validateAllTargets(): Promise<ValidationReport> { const results = await Promise.all([ this.validateFlashAttention(), // 2.49x-7.47x this.validateSearchPerformance(), // 150x-12,500x this.validateMemoryReduction(), // 50-75% this.validateStartupTime(), // <500ms this.validateSONAAdaptation() // <0.05ms ]); return { allTargetsAchieved: results.every(r => r.achieved), results, overallScore: this.calculateOverallScore(results), recommendations: this.generateRecommendations(results) }; } }
v3-integration-deep - Performance integration with agentic-flowv3-memory-unification - Memory performance optimizationv3-swarm-coordination - Swarm performance coordinationv3-security-overhaul - Secure performance patternsbash# Full performance suite npm run benchmark:v3 # Specific target validation npm run benchmark:flash-attention npm run benchmark:agentdb-search npm run benchmark:memory-optimization # Continuous monitoring npm run monitor:performance
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-14 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | 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 19 counted toward the lift figure. The other 3 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 +77 percentage points is the difference between those two pass rates over the 19 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.