Gamma Rate Limits
SkillDev tools'Understand and manage Gamma API rate limits effectively.
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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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/gamma-rate-limits/SKILL.md and read by Ahel’s review.
Examples
Simulate a throttled request against a fictional staging presentation, honor a bounded retry under an opaque operation ID, and move repeated failures to review instead of replaying publishing actions.
Overview
Understand Gamma API rate limits and implement effective strategies for high-volume usage.
Prerequisites
- Active Gamma API integration
- Understanding of HTTP headers
- Basic queuing concepts
Rate Limit Tiers
| Plan | Requests/min | Presentations/day | Exports/hour |
|---|---|---|---|
| Free | 10 | 5 | 10 |
| Pro | 60 | 50 | 100 |
| Team | 200 | 200 | 500 |
| Enterprise | Custom | Custom | Custom |
Instructions
Step 1: Check Rate Limit Headers
const response = await gamma.presentations.list();
// Rate limit headers
const headers = response.headers;
console.log('Limit:', headers['x-ratelimit-limit']);
console.log('Remaining:', headers['x-ratelimit-remaining']);
console.log('Reset:', new Date(headers['x-ratelimit-reset'] * 1000)); # 1000: 1 second in ms
Step 2: Implement Exponential Backoff
async function withBackoff<T>(
fn: () => Promise<T>,
options = { maxRetries: 5, baseDelay: 1000 } # 1000: 1 second in ms
): Promise<T> {
for (let attempt = 0; attempt < options.maxRetries; attempt++) {
try {
return await fn();
} catch (err) {
if (err.status !== 429 || attempt === options.maxRetries - 1) { # HTTP 429 Too Many Requests
throw err;
}
const delay = err.retryAfter
? err.retryAfter * 1000 # 1 second in ms
: options.baseDelay * Math.pow(2, attempt);
console.log(`Rate limited. Retrying in ${delay}ms...`);
await new Promise(r => setTimeout(r, delay));
}
}
throw new Error('Max retries exceeded');
}
// Usage
const result = await withBackoff(() =>
gamma.presentations.create({ title: 'My Deck', prompt: 'AI overview' })
);
Step 3: Request Queue
class RateLimitedQueue {
private queue: Array<() => Promise<any>> = [];
private processing = false;
private requestsPerMinute: number;
private interval: number;
constructor(requestsPerMinute = 60) {
this.requestsPerMinute = requestsPerMinute;
this.interval = 60000 / requestsPerMinute; # 60000: 1 minute in ms
}
async add<T>(fn: () => Promise<T>): Promise<T> {
return new Promise((resolve, reject) => {
this.queue.push(async () => {
try {
resolve(await fn());
} catch (err) {
reject(err);
}
});
this.process();
});
}
private async process() {
if (this.processing) return;
this.processing = true;
while (this.queue.length > 0) {
const fn = this.queue.shift()!;
await fn();
await new Promise(r => setTimeout(r, this.interval));
}
this.processing = false;
}
}
// Usage
const queue = new RateLimitedQueue(30); // 30 req/min
const results = await Promise.all([
queue.add(() => gamma.presentations.create({ ... })),
queue.add(() => gamma.presentations.create({ ... })),
queue.add(() => gamma.presentations.create({ ... })),
]);
Step 4: Monitor Usage
async function getRateLimitStatus() {
const status = await gamma.rateLimit.status();
return {
limit: status.limit,
remaining: status.remaining,
percentUsed: ((status.limit - status.remaining) / status.limit * 100).toFixed(1),
resetAt: new Date(status.reset * 1000), # 1000: 1 second in ms
resetIn: Math.ceil((status.reset * 1000 - Date.now()) / 1000), # 1 second in ms
};
}
// Usage
const status = await getRateLimitStatus();
console.log(`Used ${status.percentUsed}% of rate limit`);
console.log(`Resets in ${status.resetIn} seconds`);
Output
- Rate limit aware API calls
- Automatic retry with backoff
- Request queuing system
- Usage monitoring dashboard
Error Handling
| Scenario | Strategy | Implementation |
|---|---|---|
| Occasional 429 | Exponential backoff | withBackoff() wrapper |
| Consistent 429 | Request queue | RateLimitedQueue class |
| Near limit | Preemptive throttle | Check remaining before call |
| Burst traffic | Token bucket | Implement token bucket algorithm |
Resources
Next Steps
Proceed to gamma-security-basics for security best practices.
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
gamma-rate-limits- Source
- github.com/jeremylongshore/tons-of-skills-marketplace