Framer Performance Tuning

SkillDev tools

'Optimize Framer API performance with caching, batching, and connection

Use Framer Performance Tuning in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Framer Performance Tuning and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the Framer Performance Tuning skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Framer Performance TuningStart free

What this skill tells your AI

The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/framer-performance-tuning/SKILL.md and read by Ahel’s review.

Prerequisites

A staging site, aggregate performance baseline, approved content/assets, a change owner, and rollback path.

Error Handling

Revert changes that harm accessibility, publishing, privacy, or agreed performance thresholds; retain only redacted telemetry for review.

Examples

Optimize a fictional staging page, compare aggregate performance metrics, and roll back if a synthetic form or route check regresses.

Overview

Optimize Framer plugin, component, and Server API performance. Key areas: CMS sync speed, component render performance, and plugin responsiveness.

Instructions

Step 1: Batch CMS Operations

// Process large collections in batches to avoid timeouts
async function batchSync(collection: any, items: any[], batchSize = 50) {
  const total = items.length;
  for (let i = 0; i < total; i += batchSize) {
    await collection.setItems(items.slice(i, i + batchSize));
    const progress = Math.min(i + batchSize, total);
    framer.notify(`Synced ${progress}/${total}`);
  }
}

Step 2: Optimize Code Component Rendering

import { memo, useMemo } from 'react';

// Memoize expensive components
export default memo(function DataGrid({ data, columns }) {
  const processedData = useMemo(() =>
    data.map(row => columns.reduce((acc, col) => ({ ...acc, [col.key]: row[col.key] }), {})),
    [data, columns]
  );

  return (
    <div style={{ display: 'grid', gridTemplateColumns: `repeat(${columns.length}, 1fr)` }}>
      {processedData.map((row, i) => columns.map(col => (
        <div key={`${i}-${col.key}`} style={{ padding: 8 }}>{row[col.key]}</div>
      )))}
    </div>
  );
});

Step 3: Persistent WebSocket Connection

// Reuse Server API connection instead of reconnecting each time
let clientInstance: any = null;

async function getClient() {
  if (!clientInstance) {
    const { framer } = await import('framer-api');
    clientInstance = await framer.connect({
      apiKey: process.env.FRAMER_API_KEY!,
      siteId: process.env.FRAMER_SITE_ID!,
    });
  }
  return clientInstance;
}

Step 4: Image Optimization

// Pre-optimize image URLs before syncing to CMS
function optimizeImageUrl(url: string, width = 800): string {
  // Use image CDN if available
  if (url.includes('cloudinary.com')) {
    return url.replace('/upload/', `/upload/w_${width},q_auto,f_auto/`);
  }
  if (url.includes('imgix.net')) {
    return `${url}?w=${width}&auto=format,compress`;
  }
  return url;
}

Output

  • Batched CMS operations avoiding timeouts
  • Memoized components for render performance
  • Persistent WebSocket connections
  • Image optimization before CMS sync

Resources

Next Steps

For cost optimization, see framer-cost-tuning.

Signals

GitHub stars
3k
Forks
415
Last commit
Oct 2026
Advanced
Item type
skill
Key
framer-performance-tuning
Source
github.com/jeremylongshore/tons-of-skills-marketplace