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React Best Practices

Community
henkisdabro
react-best-practices

Comprehensive React and Next.js performance optimisation guide with 40+ rules for eliminating waterfalls, optimising bundles, and improving rendering. Use when optimising React or Next.js apps, reviewing performance, refactoring components, hunting wasteful re-renders, reducing bundle size, debugging client/server data-fetching, or tightening rendering paths. Do NOT use for non-React frameworks (Vue, Svelte, Solid, Angular), React Native, or general JavaScript performance unrelated to React.

Overview

Publisherhenkisdabro
Repositorywookstar-claude-plugins
Skill namereact-best-practices
Stars
88
Forks
12
Bundled files
47
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 47 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by henkisdabro on GitHub. Read the source before you install it.

Installation

Install the React Best Practices AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/henkisdabro/wookstar-claude-plugins.git /tmp/wookstar-claude-plugins
mkdir -p .claude/skills
cp -r /tmp/wookstar-claude-plugins/plugins/react-best-practices/skills/react-best-practices .claude/skills/react-best-practices
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable React Best Practices in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads React Best Practices on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so React Best Practices is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

React Best Practices - Performance Optimisation

Comprehensive performance optimisation guide for React and Next.js applications with 40+ rules organised by impact level. Designed to help developers eliminate performance bottlenecks and follow best practices.

Quick reference

Critical priorities

  1. Defer await until needed - Move awaits into branches where they're used
  2. Use Promise.all() - Parallelize independent async operations
  3. Avoid barrel imports - Import directly from source files
  4. Dynamic imports - Lazy-load heavy components
  5. Strategic Suspense - Stream content while showing layout

Common patterns

Parallel data fetching:

typescript
const [user, posts, comments] = await Promise.all([
  fetchUser(),
  fetchPosts(),
  fetchComments()
])

Direct imports:

tsx
// ❌ Loads entire library
import { Check } from 'lucide-react'

// ✅ Loads only what you need
import Check from 'lucide-react/dist/esm/icons/check'

Dynamic components:

tsx
import dynamic from 'next/dynamic'

const MonacoEditor = dynamic(
  () => import('./monaco-editor'),
  { ssr: false }
)

Using the guidelines

The guidelines live in the references folder at two depths - pick the one that fits the task:

  • references/react-performance-guidelines.md: the complete guide with all rules, code examples, and impact analysis. Read this for a full review or audit.
  • references/rules/: one file per rule, named <category>-<rule>.md (e.g. async-parallel.md, bundle-barrel-imports.md). Read individual files when working on a specific problem - the category pointers below map each rule to its file.

Each rule includes:

  • Incorrect/correct code comparisons
  • Specific impact metrics
  • When to apply the optimisation
  • Real-world examples

Categories overview

1. Eliminating Waterfalls (CRITICAL)

Waterfalls are the #1 performance killer. Each sequential await adds full network latency. Rules: references/rules/async-*.md

2. Bundle Size Optimisation (CRITICAL)

Reducing initial bundle size improves Time to Interactive and Largest Contentful Paint. Rules: references/rules/bundle-*.md

3. Server-Side Performance (HIGH)

Optimise server-side rendering and data fetching. Rules: references/rules/server-*.md

4. Client-Side Data Fetching (MEDIUM-HIGH)

Automatic deduplication and efficient data fetching patterns. Rules: references/rules/client-*.md

5. Re-render Optimisation (MEDIUM)

Reduce unnecessary re-renders to minimize wasted computation. Rules: references/rules/rerender-*.md

6. Rendering Performance (MEDIUM)

Optimise the browser rendering process. Rules: references/rules/rendering-*.md

7. JavaScript Performance (LOW-MEDIUM)

Micro-optimisations for hot paths. Rules: references/rules/js-*.md

8. Advanced Patterns (LOW)

Specialized techniques for edge cases. Rules: references/rules/advanced-*.md

Implementation approach

When optimising a React application:

  1. Profile first: Use React DevTools Profiler and browser performance tools to identify bottlenecks
  2. Focus on critical paths: Start with eliminating waterfalls and reducing bundle size
  3. Measure impact: Verify improvements with metrics (LCP, TTI, FID)
  4. Apply incrementally: Don't over-optimise prematurely
  5. Test thoroughly: Ensure optimisations don't break functionality

Key metrics to track

  • Time to Interactive (TTI): When page becomes fully interactive
  • Largest Contentful Paint (LCP): When main content is visible
  • First Input Delay (FID): Responsiveness to user interactions
  • Cumulative Layout Shift (CLS): Visual stability
  • Bundle size: Initial JavaScript payload
  • Server response time: TTFB for server-rendered content

Common pitfalls to avoid

Don't:

  • Use barrel imports from large libraries
  • Block parallel operations with sequential awaits
  • Re-render entire trees when only part needs updating
  • Load analytics/tracking in the critical path
  • Mutate arrays with .sort() instead of .toSorted()
  • Create RegExp or heavy objects inside render

Do:

  • Import directly from source files
  • Use Promise.all() for independent operations
  • Memoize expensive components
  • Lazy-load non-critical code
  • Use immutable array methods
  • Hoist static objects outside components

Resources

Version history

v0.1.0 (January 2026)

  • Initial release from Vercel Engineering
  • 40+ performance rules across 8 categories
  • Comprehensive code examples and impact analysis

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the React Best Practices AI skill do?

Comprehensive React and Next.js performance optimisation guide with 40+ rules for eliminating waterfalls, optimising bundles, and improving rendering. Use when optimising React or Next.js apps, reviewing performance, refactoring components, hunting wasteful re-renders, reducing bundle size, debugging client/server data-fetching, or tightening rendering paths. Do NOT use for non-React frameworks (Vue, Svelte, Solid, Angular), React Native, or general JavaScript performance unrelated to React.

Why use React Best Practices on TypingMind?

Because you install it once and use it with any model. React Best Practices is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install React Best Practices in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/henkisdabro/wookstar-claude-plugins/tree/main/plugins/react-best-practices/skills/react-best-practices. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use React Best Practices?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with React Best Practices?

As many as you like. As long as a model supports skills, you can use React Best Practices with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the React Best Practices AI skill free?

It is published on GitHub by henkisdabro. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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