What problem does it solve? Teams often optimize code blindly, wasting effort on micro-tweaks while missing the real bottlenecks. This Skill enforces a disciplined, evidence-based optimization workflow so every change targets the metrics that actually matter. ## Core Features & Use Cases - Metric Definition & Baselines: Identify the right metrics (latency, throughput, memory, CPU, cost) and build repeatable benchmarks before changing code. - Bottleneck Attribution: Instrument the system with ad hoc inspection and logged measurements to trace where time and resources go across the full execution path. - Static Analysis & Prioritization: Catch wrong asymptotic complexity, poor algorithm choices, and architectural inefficiencies, then apply macro-optimizations before micro-optimizations. - Use Case: A backend API has slow response times. Use this Skill to define a latency target, reproduce the baseline, profile the request path, discover an N+1 query pattern, fix it, and verify the improvement with before/after measurements. ## Quick Start Use the optimization skill to find and fix the performance bottleneck in my API endpoint, starting with baseline latency measurements.
