rate-limiting

Name: rate-limiting
Availability: InStock
Author: VibeKit

Implement token bucket rate limiting across distributed systems with Redis or middleware options.

Updated Aug 27, 2026

Search Tags:#redis #rate-limiting #gateway #sliding-window #token-bucket #http-headers #api-throttling

Ready to run

npx skills add https://github.com/vibekit-apps/skills-registry --skill rate-limiting-vibekit-apps

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: rate-limiting
Source: https://github.com/vibekit-apps/skills-registry/tree/main/skills/rate-limiting
Command: npx skills add https://github.com/vibekit-apps/skills-registry --skill rate-limiting-vibekit-apps

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rate limiting protects APIs from abuse, ensures fair usage, and helps gateways manage load during traffic bursts.

Core Features & Use Cases

Token Bucket, Leaky Bucket, Fixed Window, Sliding Window patterns and hybrid approaches for distributed systems.
Implementation options include in-memory, Redis, API gateway, or per-service middleware with per-IP, per-user, and per-endpoint scoping.
Use Case: Prevent abuse on a public API while preserving a good user experience by allowing controlled bursts and providing clear 429 guidance.

Quick Start

Configure a per-IP rate limit using a token bucket strategy to protect a public API.

Frequently Asked Questions about rate-limiting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I implement rate limiting to protect my API from abuse?▼

API rate limiting protects APIs from abuse by applying strategies like token bucket or sliding window. You can implement throttling across distributed systems using in-memory stores, Redis, or middleware to enforce fair usage.

What is the difference between token bucket and sliding window rate limiting?▼

Token bucket rate limiting allows controlled traffic bursts by accumulating tokens over time, whereas sliding window limits requests within a moving time frame. Both strategies manage API throttling but handle traffic bursts differently.

Can I use Redis for distributed rate limiting across multiple services?▼

Redis supports distributed rate limiting across multiple services. The implementation options include Redis alongside in-memory and API gateway approaches, enabling per-IP, per-user, and per-endpoint scoping for distributed systems.

How should API throttling handle HTTP headers and 429 responses?▼

API throttling should define standard HTTP headers and provide clear 429 response guidance. This ensures clients understand rate limits and handle throttling gracefully, preserving user experience during traffic bursts.

What is the best way to apply rate limiting per-user and per-endpoint?▼

The best way to apply rate limiting per-user and per-endpoint is using middleware or API gateway configurations. These allow precise scoping to prevent abuse on public APIs while maintaining controlled bursts and fair usage.