Figma Rate Limits
SkillMedia'Handle Figma REST API rate limits with exponential backoff and request
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Details
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What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/figma-rate-limits/SKILL.md and read by ahel’s review.
Overview
Figma uses a leaky bucket algorithm for rate limiting. When the bucket is full, the API returns 429 with a Retry-After header. Limits vary by plan tier, seat type, and endpoint tier.
Prerequisites
- Figma REST API integration working
- Understanding of async/await patterns
Instructions
Step 1: Understand the Rate Limit Model
Endpoint tiers (limits are per-user, per-minute):
| Tier | Endpoints | Typical Limit |
|---|---|---|
| Tier 1 | GET /v1/files, GET /v1/images | Higher quota |
| Tier 2 | GET /v1/files/:key/comments, GET /v1/files/:key/variables/local | Moderate quota |
| Tier 3 | GET /v1/teams/:id/components, GET /v1/teams/:id/styles | Lower quota |
429 response headers:
| Header | Type | Meaning |
|---|---|---|
Retry-After | Integer (seconds) | Wait this long before retrying |
X-Figma-Plan-Tier | String | Your Figma plan level |
X-Figma-Rate-Limit-Type | String | "low" or "high" rate limit |
X-Figma-Upgrade-Link | String | URL to upgrade for higher limits |
Step 2: Implement Exponential Backoff
async function figmaFetchWithRetry(
path: string,
token: string,
maxRetries = 5
): Promise<any> {
for (let attempt = 0; attempt <= maxRetries; attempt++) {
const res = await fetch(`https://api.figma.com${path}`, {
headers: { 'X-Figma-Token': token },
});
if (res.status === 429) {
const retryAfter = parseInt(res.headers.get('Retry-After') || '60');
const limitType = res.headers.get('X-Figma-Rate-Limit-Type') || 'unknown';
if (attempt === maxRetries) {
throw new Error(`Rate limited after ${maxRetries} retries (${limitType})`);
}
// Use the Retry-After header -- Figma tells you exactly how long to wait
const jitter = Math.random() * 1000;
const delay = retryAfter * 1000 + jitter;
console.warn(`429 (${limitType}). Waiting ${(delay/1000).toFixed(1)}s (attempt ${attempt + 1})`);
await new Promise(r => setTimeout(r, delay));
continue;
}
if (res.status >= 500 && attempt < maxRetries) {
// Server errors: exponential backoff without Retry-After
const delay = Math.min(1000 * Math.pow(2, attempt), 30000);
await new Promise(r => setTimeout(r, delay));
continue;
}
if (!res.ok) {
throw new Error(`Figma API error: ${res.status} ${await res.text()}`);
}
return res.json();
}
}
Step 3: Request Queue with Concurrency Control
import PQueue from 'p-queue';
// Limit concurrent requests to avoid bursting the bucket
const figmaQueue = new PQueue({
concurrency: 3, // max 3 parallel requests
interval: 1000, // per second
intervalCap: 5, // max 5 requests per second
});
async function queuedFigmaRequest<T>(
path: string,
token: string
): Promise<T> {
return figmaQueue.add(() => figmaFetchWithRetry(path, token));
}
// Usage -- all requests are automatically queued and throttled
const [file, comments, images] = await Promise.all([
queuedFigmaRequest(`/v1/files/${fileKey}`, token),
queuedFigmaRequest(`/v1/files/${fileKey}/comments`, token),
queuedFigmaRequest(`/v1/images/${fileKey}?ids=0:1&format=svg`, token),
]);
Step 4: Rate Limit Monitor
class FigmaRateLimitMonitor {
private requestLog: number[] = [];
private windowMs = 60_000; // 1 minute window
recordRequest() {
this.requestLog.push(Date.now());
// Trim old entries
const cutoff = Date.now() - this.windowMs;
this.requestLog = this.requestLog.filter(t => t > cutoff);
}
getRequestsInWindow(): number {
const cutoff = Date.now() - this.windowMs;
return this.requestLog.filter(t => t > cutoff).length;
}
shouldThrottle(safetyMargin = 0.8): boolean {
// If we've used 80% of a conservative estimate, slow down
const estimatedLimit = 30; // Conservative estimate
return this.getRequestsInWindow() > estimatedLimit * safetyMargin;
}
}
const monitor = new FigmaRateLimitMonitor();
// Wrap every request
async function monitoredFigmaFetch(path: string, token: string) {
if (monitor.shouldThrottle()) {
console.warn('Approaching rate limit, adding delay');
await new Promise(r => setTimeout(r, 2000));
}
monitor.recordRequest();
return figmaFetchWithRetry(path, token);
}
Step 5: Batch Node Requests
// Instead of N individual /v1/files/:key/nodes requests,
// batch node IDs into fewer requests
async function batchFetchNodes(
fileKey: string,
nodeIds: string[],
batchSize = 50,
token: string
) {
const results: Record<string, any> = {};
for (let i = 0; i < nodeIds.length; i += batchSize) {
const batch = nodeIds.slice(i, i + batchSize);
const ids = encodeURIComponent(batch.join(','));
const data = await queuedFigmaRequest(
`/v1/files/${fileKey}/nodes?ids=${ids}`,
token
);
Object.assign(results, data.nodes);
}
return results;
}
Output
- Automatic retry with
Retry-Afterheader compliance - Request queue preventing burst overload
- Rate limit monitoring with proactive throttling
- Batch operations reducing total request count
Error Handling
| Scenario | Detection | Response |
|---|---|---|
| Single 429 | Retry-After header | Wait exactly that duration |
| Repeated 429s | Multiple retries exhausted | Log, alert, back off longer |
low rate limit type | X-Figma-Rate-Limit-Type: low | Consider upgrading Figma plan |
| Batch too large | 400 Bad Request | Reduce batch size to 50 IDs |
Examples
Reproduce a 429 and read the headers that drive every pattern in this skill (Step 1):
for i in $(seq 1 60); do
curl -s -o /dev/null -D - -H "X-Figma-Token: ${FIGMA_PAT}" \
"https://api.figma.com/v1/files/${FIGMA_FILE_KEY}?depth=1" | /usr/bin/grep -iE '^(HTTP|retry-after)'
done | sort | uniq -c
54 HTTP/2 200
6 HTTP/2 429
6 retry-after: 30
Collapse N per-node calls into one batched request (Step 5) — the single biggest budget win:
curl -s -H "X-Figma-Token: ${FIGMA_PAT}" \
"https://api.figma.com/v1/files/${FIGMA_FILE_KEY}/nodes?ids=1:2,1:5,1:9,2:14" | jq '.nodes | keys'
Backoff implementation and the queue: references/implement-exponential-backoff.md, references/request-queue-with-concurrency-control.md.
Resources
Next Steps
For security configuration, see figma-security-basics.
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
ahel review
S4info
community integration, published by jeremylongshore, not figma
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
figma-rate-limits- Source
- github.com/jeremylongshore/tons-of-skills-marketplace