This covers the three main rate limiting algorithms you'll actually use: token bucket for smooth traffic shaping, sliding window for precision, and fixed window when you need something simple. The reference guides include Redis implementations, which is what you want for any production system that runs on multiple servers. It also handles the tiered limits scenario, so you can give paying customers higher quotas. The code examples are JavaScript and Python/Flask, and it reminds you to include the standard rate limit headers in responses. One thing to know: the best practices correctly warn against in-memory storage in production, but the quick start example is in-memory, so you'll need to jump to the Redis guide for real deployments.
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill api-rate-limiting