smithery/jeremylongshore

gamma-rate-limits

Understand and manage Gamma API rate limits effectively. Use when hitting rate limits, optimizing API usage, or implementing request queuing systems. Trigger with phrases like "gamma rate limit", "gamma quota", "gamma 429", "gamma throttle", "gamma request limits". '

Installation

$ npx skills add smithery/jeremylongshore --skill gamma-rate-limits

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.13.0
LicenseMIT
CompatibilityDesigned for Claude Code
Allowed toolsRead, Write, Edit
Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,034 B
  • docs SUMMARY.md 294 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Gamma Rate Limits

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.