Can I use this for backend performance?

Absolutely. It covers Redis caching strategies, backend profiling with tools like py-spy, and bundle analysis for server-side environments.

How does this skill help with Core Web Vitals?

It provides specific implementation patterns for LCP, INP, and CLS, including scheduler.yield for responsiveness and fetchpriority for faster hero element loading.

Does it support the latest React features?

Yes, it includes patterns for React 19, the React Compiler, and TanStack Query v5 for optimized data fetching and prefetching.

What makes the LLM inference section unique?

It provides specialized patterns for vLLM deployment, quantization (AWQ/FP8), and speculative decoding to significantly boost AI model throughput.

Performance Optimization & Inference

Name: Performance Optimization & Inference
Author: yonatangross

byyonatangross

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116

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Analytics & Monitoring

Optimizes full-stack application performance using modern patterns for Core Web Vitals, React rendering, and high-throughput LLM inference.

This skill provides a comprehensive toolkit for developers looking to boost application speed and efficiency across the entire stack. It implements production-ready patterns for frontend metrics like LCP and INP using the latest 2026 standards, optimizes React 19+ rendering with the React Compiler and virtualization, and streamlines backend processes through Redis caching and bundle analysis. Additionally, it features specialized guidance for high-performance AI workloads, covering vLLM deployment, quantization techniques, and speculative decoding to maximize inference throughput while maintaining sustainability through reduced page weights and carbon-efficient UX.

Key Features

01Efficient asset handling through Next.js image optimization and lazy loading patterns.

02Sustainable UX patterns to reduce page weight and digital carbon footprint.

03High-performance LLM inference strategies including vLLM, quantization, and speculative decoding.

04116 GitHub stars

05Core Web Vitals optimization for LCP, INP, and CLS with 2026 threshold compliance.

06React 19+ render optimization using React Compiler, memoization, and virtualization.

Use Cases

01Deploying and optimizing local or private LLMs for maximum inference speed and lower compute costs.

02Debugging and resolving performance bottlenecks in complex React applications and large-scale data lists.

03Improving Lighthouse scores and Core Web Vitals to meet SEO and user experience benchmarks.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yonatangross/orchestkit performance

For use in Claude.ai and ChatGPT

Download Skill