V3 Performance Optimization

What problem does it solve? Validating that claude-flow v3 actually meets its aggressive performance targets (2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvement, 50-75% memory reduction) requires systematic benchmarking rather than guesswork, and regressions can slip in unnoticed without continuous monitoring. ## Core Features & Use Cases - Comprehensive Benchmark Suites: TypeScript benchmark classes for startup time, vector search, memory usage, swarm coordination, Flash Attention, and SONA adaptation speed. - Target Validation Gates: A PerformanceGates framework that checks every metric against its target range and reports an overall score with recommendations. - Regression Detection: Continuous comparison of current benchmarks against baselines with a 5% regression threshold and severity classification. - Use Case: Before shipping a v3 release, run the full benchmark suite to confirm Flash Attention speedup, HNSW search latency under 100ms for 1M+ entries, and sub-500ms cold starts, then wire the monitor into CI to catch regressions. ## Quick Start Ask the AI to establish a v2 performance baseline and then validate the Flash Attention, search, and memory optimization targets in parallel using the v3-performance-engineer agent.