正在浏览:

CJHarmath

Performance optimization for React web applications. Use when optimizing renders, implementing virtualization, memoizing components, or debugging performance issues.

sahuadarsh0

Debug and optimize Android/Gradle build performance. Use when builds are slow, investigating CI/CD performance, analyzing build scans, or identifying compilation bottlenecks.

thinhtt264

Debug and optimize Android/Gradle build performance. Use when builds are slow, investigating CI/CD performance, analyzing build scans, or identifying compilation bottlenecks.

juanfranem

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

diegoknsk

Guia para otimização de performance — Span<T>, Memory<T>, ArrayPool, ValueTask, compiled queries e técnicas avançadas. Use quando a tarefa envolver performance, otimização, alocações, memory pooling ou hot paths.

elsolal

Audit de performance du code et de lapplication. Analyse Lighthouse, bundle size, Core Web Vitals, et optimisations. Utiliser après limplémentation, avant une release, ou quand lutilisateur dit performance, slow, optimize, bundle size.

JochenYang

Performance bottleneck identification and optimization. Handles database query optimization, caching strategies, algorithm improvements, and Core Web Vitals tuning (LCP/FID/CLS). Use when user asks to optimize performance, improve speed, fix slow queries, or tune web vitals.

deadronos

Performance optimization playbook (measure → diagnose → fix → verify) for this repo (React + R3F + Three.js + Vite). Use when asked to improve FPS, reduce jank, lower draw calls, optimize loading/bundle size, or investigate CPU/GPU/memory bottlenecks.

infodungeon

Enforces Vercel-standard performance optimizations for React and Next.js applications.

adebold

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

Pama-Lee

Ordo JIT compilation and performance optimization guide. Includes Schema-aware JIT, TypedContext derive macro, Cranelift compilation, performance tuning. Use for optimizing rule execution performance, reducing latency, increasing throughput.

Pama-Lee

Ordo rule engine Rust development guide. Helps create RuleSet, Step, conditional branches, terminal results. Use for writing rule definitions, understanding Step Flow model, creating Decision/Action/Terminal steps.