How does this skill help with database performance?

It provides standardized protocols for detecting N+1 queries, interpreting EXPLAIN ANALYZE results, and selecting optimal index types like B-tree or HNSW for vector searches.

What frontend metrics does it focus on?

The skill targets Core Web Vitals including Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS) to improve UX.

Does it support backend profiling?

Yes, it includes frameworks for using py-spy, cProfile, and memory_profiler to identify CPU and memory bottlenecks in Python-based backends.

Can it help reduce LLM API costs?

Yes, it includes specialized caching strategies such as prompt caching and Redis-based semantic caching that can reduce LLM overhead by up to 95%.

Performance Optimization Pro

Name: Performance Optimization Pro
Author: yonatangross

byyonatangross

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Analytics & Monitoring

Analyzes and resolves application bottlenecks across the full stack, from database queries to frontend bundle sizes and Core Web Vitals.

This skill provides comprehensive frameworks and production-ready patterns for diagnosing and fixing performance regressions in modern applications. It empowers Claude to perform deep-dive profiling of backend systems using tools like py-spy, optimize database interactions through index selection and N+1 query remediation, and streamline frontend delivery using React 19 concurrent features and bundle analysis. Whether you are scaling for high traffic, reducing LLM API costs through semantic caching, or improving user experience scores, this skill provides the systematic diagnostic logic and implementation templates required for high-performance engineering.

Key Features

01Full-stack profiling using py-spy, Lighthouse, and pg_stat_statements

02Frontend bundle analysis and optimization via code-splitting and virtualization

03Multi-level caching strategies for Redis, CDNs, and LLM semantic caching

04Database query optimization including index selection and N+1 fixes

0569 GitHub stars

06Core Web Vitals auditing and remediation for LCP, INP, and CLS

Use Cases

01Implementing cost-saving LLM response caching to reduce token usage and latency

02Reducing frontend bundle sizes and improving Lighthouse scores for React applications

03Identifying and fixing slow database queries and N+1 problems in FastAPI/SQLAlchemy

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yonatangross/orchestkit performance-optimization

For use in Claude.ai and ChatGPT

Download Skill