optimizing-react-performance

A guide to finding and reducing unnecessary rendering in React, a JavaScript library for building user interfaces. It uses the React DevTools Profiler and explains React.memo, useCallback, and useMemo.

In plain words
What is it for?
Use it to investigate slow React components, prevent avoidable child renders, keep function references stable, and avoid repeating expensive calculations.
Why use it?
It helps identify the parts of an interface that actually cause slow interactions before changing the code.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/porcupine-md/jonggrang/optimizing-react-performance
Any agent
npx skills add porcupine-md/jonggrang --skill optimizing-react-performance
Clone the repo
git clone --depth 1 https://github.com/porcupine-md/jonggrang

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 885 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.00885
Opus 5 $0.00010 $0.00443
Sonnet 5 $0.00004 $0.00177
Haiku 4.5 $0.00002 $0.00089

Measured 2d ago against content hash 48890dd4223b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

optimizing-react-performance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/library/frontend/optimizing-react-performance/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Profile First — Never Optimize Blindly

// 1. Enable React DevTools Profiler
// 2. Record the slow interaction
// 3. Find components with long render times

// Rule: Only optimize what the profiler shows as slow

The Three Memoization Tools

React.memo — Prevent Child Re-renders

// Without memo: re-renders whenever parent re-renders (even same props)
const ExpensiveList = React.memo(({ items, onItemClick }) => {
  return items.map(item => (
    <Item key={item.id} item={item} onClick={onItemClick} />
  ));
});

// Only re-renders when items or onItemClick reference changes

useCallback — Stable Function References

// Without useCallback: new function reference every render → breaks React.memo
const Parent = () => {
  const [count, setCount] = useState(0);

  // BAD: new reference every render
  const handleClick = (id) => console.log(id);

  // GOOD: stable reference (only changes if count changes)
  const handleClick = useCallback((id) => {
    console.log(id, count);
  }, [count]);

  return <ExpensiveList onItemClick={handleClick} />;
};

useMemo — Expensive Computations

// Only use useMemo for genuinely expensive calculations
const sortedAndFilteredItems = useMemo(() => {
  return items
    .filter(item => item.active)
    .sort((a, b) => b.priority - a.priority);
}, [items]); // only recalculate when items changes

Anti-Patterns

// Anti-pattern 1: Premature optimization
const name = useMemo(() => `${first} ${last}`, [first, last]);
// String concatenation is instant — useMemo adds overhead here

// Anti-pattern 2: Object in deps breaks memoization
const options = { limit: 10 };
const result = useMemo(() => fetchData(options), [options]);
// options is a new object every render! Memoization is pointless.

// Fix: primitives in deps
const result = useMemo(() => fetchData({ limit }), [limit]);

Virtualization for Long Lists

// Don't render 10,000 items in the DOM
import { FixedSizeList } from 'react-window';

const VirtualList = ({ items }) => (
  <FixedSizeList height={600} width="100%" itemCount={items.length} itemSize={50}>
    {({ index, style }) => (
      <div style={style}>{items[index].name}</div>
    )}
  </FixedSizeList>
);

Read the full file on GitHub · 131 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 131 lines · 21 tokens per session scan A 48890dd4223b

Subscribe to this mod's changes

optimizing-react-performance is a skill published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 6d ago), licensed MIT. It adds 21 tokens to every session and 885 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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