performance▌

Identifies and eliminates performance bottlenecks in Flutter apps through systematic profiling and targeted optimization. \n \n Provides a decision tree to diagnose jank on UI thread, Raster (GPU) thread, or both, with specific fixes for each \n Includes integration test templates using traceAction and TimelineSummary to establish performance baselines and measure frame budgets \n Covers UI optimization (localizing state, const constructors, StringBuffer usage) and Raster optimization (replacing

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. \n \n Covers CPU profiling with cProfile, line-by-line profiling with line_profiler, memory tracking with memory_profiler, and production profiling with py-spy \n Includes 20+ optimization patterns: list comprehensions, generators, string concatenation, dictionary lookups, NumPy vectorization, caching, multiprocessing, and async I/O \n Provides database optimization techniques including batch opera

Comprehensive performance optimization guide for Expo React Native applications. Contains 42 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

Scan C#/.NET code for performance anti-patterns and produce prioritized findings with concrete fixes. Patterns sourced from the official .NET performance blog series, distilled to customer-actionable guidance.

Caches configuration phase across builds (AGP 8.0+):

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

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

'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).'

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

Diagnose and fix SwiftUI performance issues through code review and Instruments profiling guidance. \n \n Classifies symptoms (slow rendering, janky scrolling, CPU spikes, memory growth, hangs, excessive view updates) and performs code-first review against common anti-patterns like invalidation storms, unstable list identity, and layout thrash. \n Guides users through Instruments profiling when code review alone is inconclusive, with structured intake checklists and trace analysis. \n Provides r