performance▌

'Astro-specific performance optimizations for 95+ Lighthouse scores. Covers critical CSS inlining, compression, font loading, and LCP optimization. Use when optimizing Astro site performance, improving Astro Lighthouse scores, or configuring astro-critters. Do NOT use for non-Astro sites (use perf-web-optimization or core-web-vitals) or running Lighthouse audits (use perf-lighthouse).'

Comprehensive Next.js performance optimization covering Core Web Vitals, modern React patterns, and production-grade techniques. \n \n Covers Core Web Vitals optimization (LCP, INP, CLS), image/font optimization with next/image and next/font , and caching strategies using unstable_cache and revalidateTag \n Guides conversion of Client Components to Server Components, implementation of Suspense streaming for progressive loading, and bundle size reduction through code splitting \n Includes Next.js

WordPress performance optimization guidelines across database, caching, assets, and plugin architecture. \n \n 34 rules organized by impact across 8 categories: database optimization, caching strategies, asset management, theme performance, plugin architecture, media optimization, API/AJAX, and advanced patterns \n Covers critical areas including WP_Query optimization, transient and object cache usage, proper asset enqueueing, and REST API caching \n Designed for code review and generation workf

Backend-only WordPress performance profiling and optimization using WP-CLI, Query Monitor, and targeted diagnostics. \n \n Detects and measures performance bottlenecks via WP-CLI doctor/profile commands, Server-Timing headers, and Query Monitor REST API integration without requiring browser access \n Covers five optimization categories: database query reduction, autoloaded options cleanup, object cache configuration, cron task optimization, and remote HTTP call management \n Includes safe verifi

Tests in real browsers using Chrome DevTools MCP for debugging and inspecting web applications.

Apply when optimizing GSAP animations for smooth 60fps, reducing layout/paint cost, or when the user asks about performance, jank, or best practices for fast animations.

Optimize JVM performance through profiling, GC tuning, and memory analysis.

Memoization, code splitting, and virtualization patterns for optimizing React application performance. \n \n Covers four core optimization techniques: memoization (React.memo, useMemo, useCallback), code splitting with lazy/Suspense, virtualization for large lists, and state management strategies to minimize render cascades \n Includes React 18+ concurrent features (useTransition, useDeferredValue) for improved responsiveness and perceived performance \n Provides profiling workflow using React D

Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and IR-level debugging. Use when asked to "optimize cutile kernel", "improve kernel perf", "tune cutile performance", "make kernel faster", or iteratively benchmark and refine a cuTile GPU kernel in the TileGym project.

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