gamma-rate-limits
Best practices for handling Gamma API rate limits, including implementing request queuing and exponential backoff.
Install
mkdir -p .claude/skills/gamma-rate-limits && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4734" && unzip -o skill.zip -d .claude/skills/gamma-rate-limits && rm skill.zipInstalls to .claude/skills/gamma-rate-limits
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Understand and manage Gamma API rate limits effectively.Key capabilities
- →Monitor rate limit headers
- →Build request queuing systems
- →Track usage percentage against plan limits
How it works
It manages API throughput by inspecting rate limit headers and implementing retry logic with exponential backoff or request queuing to prevent 429 errors.
Inputs & outputs
When to use gamma-rate-limits
- →Implement exponential backoff for 429 errors
- →Monitor API request headers for usage tracking
- →Build a request queuing system
- →Optimize request frequency for specific plans
About this skill
Gamma Rate Limits
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.
When not to use it
- →When traffic is consistently below free tier limits
Prerequisites
Limitations
- →Requires integration of custom queue logic
- →Backoff strategies must be tuned to avoid blocking application threads
How it compares
It provides a programmatic queue and backoff wrapper rather than relying on manual request spacing.
Compared to similar skills
gamma-rate-limits side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| gamma-rate-limits (this skill) | 1 | 25d | No flags | Intermediate |
| mcp-builder | 136 | 3mo | Review | Advanced |
| telegram-mini-app | 62 | 6mo | Review | Advanced |
| stripe-integration | 48 | 2mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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