optimize-performance

A command for finding and addressing React component performance problems, such as unnecessary re-renders, expensive calculations, large bundles, and slow loading.

In plain words
What is it for?
Use it to apply memoization, code splitting, lazy loading, image improvements, and related React performance patterns.
Why use it?
It provides a structured review of common causes of a sluggish React interface and suggests matching code changes.

Command for Cursor

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 commands/farzannajipour/cursor-react-rules/optimize-performance
Clone the repo
git clone --depth 1 https://github.com/Farzannajipour/cursor-react-rules

Made for: Cursor.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,738 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 $0.00000 $0.01738
Opus 5 $0.00000 $0.00869
Sonnet 5 $0.00000 $0.00348
Haiku 4.5 $0.00000 $0.00174

Measured 2d ago against content hash afff9317fadf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

optimize-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.

.cursor/commands/optimize-performance.md · 292 lines

How it starts

The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Optimize Performance

Overview

Analyze and optimize React component performance with memoization, code splitting, and lazy loading.

Steps

  1. Identify performance issues

    • Check for unnecessary re-renders
    • Find expensive calculations
    • Look for large bundle sizes
    • Identify render bottlenecks
  2. Apply React optimizations

    • Add React.memo() for pure components
    • Use useMemo() for expensive calculations
    • Use useCallback() for function props
    • Optimize context usage
  3. Implement code splitting

    • Use React.lazy() for route-based splitting
    • Use dynamic imports for large components
    • Split vendor bundles
  4. Optimize images and assets

    • Use next/image (Next.js)
    • Implement lazy loading
    • Use proper image formats (WebP)

Optimization Patterns

1. Memoize Components

import { memo } from 'react';

interface ItemProps {
  item: Item;
  onSelect: (id: string) => void;
}

// Memoize to prevent re-renders when props don't change
export const ListItem = memo<ItemProps>(({ item, onSelect }) => {
  console.log('ListItem rendered:', item.id);
  
  return (
    <div onClick={() => onSelect(item.id)}>
      {item.name}
    </div>
  );
});

// Custom comparison function
export const ComplexItem = memo<ItemProps>(
  ({ item, onSelect }) => {
    return <div>{/* ... */}</div>;
  },
  (prevProps, nextProps) => {
    // Return true if props are equal (don't re-render)
    return prevProps.item.id === nextProps.item.id;
  }
);

2. Memoize Expensive Calculations

import { useMemo } from 'react';

function DataTable({ data, filters }: Props) {
  // Expensive filtering and sorting
  const processedData = useMemo(() => {
    console.log('Processing data...');
    
    let result = data.filter(item => 
      filters.every(filter => filter.match(item))
    );
    
    result.sort((a, b) => a.name.localeCompare(b.name));
    
    return result;
  }, [data, filters]); // Only recalculate when these change

  return (
    <table>
      {processedData.map(item => (
        <tr key={item.id}>{/* ... */}</tr>
      ))}
    </table>
  );
}

Read the full file on GitHub · 292 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 · 292 lines · 0 tokens per session scan A afff9317fadf

Subscribe to this mod's changes

optimize-performance is a command published in the GitHub repository Farzannajipour/cursor-react-rules (3 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,738 tokens. 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 2026-08-31.