Framer Rate Limits
SkillDev tools'Implement Framer rate limiting, backoff, and idempotency patterns.
Use Framer Rate Limits in Claude, ChatGPT or Ahel Desktop
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the Framer Rate Limits skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/framer-rate-limits/SKILL.md and read by Ahel’s review.
Prerequisites
Confirmed provider limits, bounded concurrency/retry policy, approved integration owner, and synthetic staging requests.
Output
Record policy version, aggregate throttles, retry/queue outcome, owner, and manual disposition without visitor data or credentials.
Examples
Simulate a throttled staging request, honor the retry bound under an opaque operation ID, and route repeated failures to review instead of replaying publish actions.
Overview
Handle Framer API rate limits for Server API and plugin operations. The Server API uses WebSocket, so rate limits apply per-connection. CMS operations are limited by collection size and concurrent writes.
Rate Limit Reference
| Operation | Limit | Notes |
|---|---|---|
| Server API connections | 1 per site | WebSocket, persistent |
| CMS setItems | ~100 items/call | Batch larger sets |
| CMS getItems | No hard limit | Returns all items |
| Plugin API calls | Debounced | Framer throttles internally |
| Publish | ~1/minute | Site publishing |
| Image upload | Concurrent limit | Via CMS image fields |
Instructions
Step 1: Batch CMS Writes
async function batchSetItems(collection: any, items: any[], batchSize = 100) {
for (let i = 0; i < items.length; i += batchSize) {
const batch = items.slice(i, i + batchSize);
await collection.setItems(batch);
console.log(`Synced ${Math.min(i + batchSize, items.length)}/${items.length}`);
if (i + batchSize < items.length) {
await new Promise(r => setTimeout(r, 1000)); // 1s between batches
}
}
}
Step 2: Debounced Plugin Operations
// Debounce rapid plugin UI interactions
function debounce<T extends (...args: any[]) => any>(fn: T, ms = 300) {
let timer: NodeJS.Timeout;
return (...args: Parameters<T>) => {
clearTimeout(timer);
timer = setTimeout(() => fn(...args), ms);
};
}
const debouncedSync = debounce(async () => {
await syncCollection();
}, 500);
Step 3: Retry for Server API
async function withRetry<T>(fn: () => Promise<T>, maxRetries = 3): Promise<T> {
for (let i = 0; i <= maxRetries; i++) {
try {
return await fn();
} catch (err: any) {
if (i === maxRetries) throw err;
const delay = 1000 * Math.pow(2, i);
console.log(`Retry ${i + 1} in ${delay}ms`);
await new Promise(r => setTimeout(r, delay));
}
}
throw new Error('Unreachable');
}
Error Handling
| Error | Cause | Solution |
|---|---|---|
| WebSocket disconnected | Connection timeout | Reconnect with backoff |
| setItems slow | Large batch | Split into chunks of 100 |
| Publish rate limited | Too frequent | Wait 60s between publishes |
Resources
Next Steps
For security, see framer-security-basics.
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
framer-rate-limits- Source
- github.com/jeremylongshore/tons-of-skills-marketplace