What problem does it solve?
It solves performance bottlenecks by turning guesswork optimization into a measurement-driven workflow that improves load time, responsiveness, and stability without adding unnecessary complexity.
Core Features & Use Cases
- Measure before optimizing: Establish baselines using synthetic tools (Lighthouse/DevTools) and validate with real-user metrics (Web Vitals/RUM).
- Identify the real bottleneck: Diagnose whether the slowdown comes from rendering, network/TTFB, JavaScript long tasks, backend query patterns (e.g., N+1), caching gaps, or oversized payloads.
- Fix, verify, and guard against regressions: Apply targeted fixes (bundle splitting, pagination, image optimization, caching, profiling) and re-measure to confirm improvement, then add monitoring/tests to prevent backsliding.
Example use case: You notice a regression after a release—use this Skill to profile the page, find whether the issue is an LCP image, a slow API/TTFB, or a backend N+1 query, then verify that Core Web Vitals improve.
Quick Start
Use performance-optimization to profile your application, identify the specific bottleneck causing the slowdown, implement the targeted fix, and verify the improvement with before-and-after measurements.