Does it support memory management?

Yes, it includes strategies for detecting leaks via heap snapshots and provides fixes for common issues like uncleared event listeners and timers.

What frontend metrics does it focus on?

It specifically targets Core Web Vitals including Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS).

Can this skill help with database performance?

Yes, it provides specific patterns for detecting N+1 queries, adding correct indexes, and implementing connection pooling and caching.

How does the Performance Optimizer skill identify bottlenecks?

The skill uses a 'measure first' approach, guiding Claude to use tools like Lighthouse, APMs, and SQL EXPLAIN to find the 20% of code causing 80% of the slowness.

Performance Optimizer

Name: Performance Optimizer
Author: nguyenthienthanh

bynguyenthienthanh

•

Analíticas y Monitorización

Identifies and resolves software performance bottlenecks through systematic profiling, measurement, and targeted code optimization across the full stack.

The Performance Optimizer skill equips Claude Code with a structured methodology for auditing and enhancing application speed. It moves beyond guesswork by enforcing a 'measure first' approach, providing specialized strategies for frontend Core Web Vitals, backend API latency, database query analysis, and memory leak detection. Whether you are debugging slow SQL queries, improving Lighthouse scores, or managing complex caching layers, this skill provides the implementation patterns and checklists needed to build high-performance, scalable software.

Características Principales

01Automated identification of common backend bottlenecks like N+1 queries and sync blocking.

02Full-stack profiling strategies covering Frontend, Backend, Database, and Memory layers.

03Targeted Core Web Vitals optimization for LCP, FID, and CLS metrics.

041 GitHub stars

05Comprehensive database indexing and query execution plan analysis patterns.

06Memory leak detection and cleanup strategies for both Node.js and browser environments.

Casos de Uso

01Optimizing database-heavy applications by identifying missing indexes and refactoring inefficient queries.

02Improving web application performance to meet Google Lighthouse and SEO benchmarks.

03Identifying and fixing memory leaks in long-running JavaScript or TypeScript processes.

Características Principales

01Automated identification of common backend bottlenecks like N+1 queries and sync blocking.

02Full-stack profiling strategies covering Frontend, Backend, Database, and Memory layers.

03Targeted Core Web Vitals optimization for LCP, FID, and CLS metrics.

041 GitHub stars

05Comprehensive database indexing and query execution plan analysis patterns.

06Memory leak detection and cleanup strategies for both Node.js and browser environments.

Casos de Uso

01Optimizing database-heavy applications by identifying missing indexes and refactoring inefficient queries.

02Improving web application performance to meet Google Lighthouse and SEO benchmarks.

03Identifying and fixing memory leaks in long-running JavaScript or TypeScript processes.