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api-rate-limiting

tessl install github:secondsky/claude-skills --skill api-rate-limiting

github.com/secondsky/claude-skills

Implements API rate limiting using token bucket, sliding window, and Redis-based algorithms to protect against abuse. Use when securing public APIs, implementing tiered access, or preventing denial-of-service attacks.

Review Score

89%

Validation Score

13/16

Implementation Score

80%

Activation Score

100%

API Rate Limiting

Protect APIs from abuse using rate limiting algorithms with per-user and per-endpoint strategies.

Algorithms

Algorithm	Pros	Cons
Token Bucket	Handles bursts, smooth	Memory per user
Sliding Window	Accurate	Memory intensive
Fixed Window	Simple	Boundary spikes

Token Bucket (Node.js)

class TokenBucket {
  constructor(capacity, refillRate) {
    this.capacity = capacity;
    this.tokens = capacity;
    this.refillRate = refillRate; // tokens per second
    this.lastRefill = Date.now();
  }

  consume() {
    this.refill();
    if (this.tokens >= 1) {
      this.tokens--;
      return true;
    }
    return false;
  }

  refill() {
    const now = Date.now();
    const elapsed = (now - this.lastRefill) / 1000;
    this.tokens = Math.min(this.capacity, this.tokens + elapsed * this.refillRate);
    this.lastRefill = now;
  }
}

Express Middleware

const rateLimit = require('express-rate-limit');

const limiter = rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100,
  standardHeaders: true,
  message: { error: 'Too many requests, try again later' }
});

app.use('/api/', limiter);

Response Headers

X-RateLimit-Limit: 100
X-RateLimit-Remaining: 45
X-RateLimit-Reset: 1705320000
Retry-After: 60

Tiered Limits

Tier	Requests/Hour
Free	100
Pro	1,000
Enterprise	10,000

Best Practices

Use Redis for distributed rate limiting
Include proper headers in responses
Return 429 status with Retry-After
Implement tiered limits for different plans
Monitor rate limit metrics
Test under load