RA

rate-limiting-apis

Provides infrastructure and logic for protecting APIs with sophisticated rate limiting strategies.

Install

mkdir -p .claude/skills/rate-limiting-apis && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3843" && unzip -o skill.zip -d .claude/skills/rate-limiting-apis && rm skill.zip

Installs to .claude/skills/rate-limiting-apis

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.

Implement sophisticated rate limiting with sliding windows, token buckets,
74 charsno explicit “when” trigger
Advanced

Key capabilities

  • Configure per-endpoint, per-user, and per-API-key limits
  • Implement sliding window, token bucket, and fixed window counter algorithms
  • Add burst allowance to handle traffic spikes
  • Set standard rate limit response headers
  • Return 429 Too Many Requests with Retry-After header
  • Implement rate limit bypass for internal service-to-service calls

How it works

This skill implements rate limiting middleware that extracts client identifiers and checks them against configured limits using Redis-backed distributed state. It applies algorithms like sliding window or token bucket to manage API traffic.

Inputs & outputs

You give it
API endpoint traffic patterns and desired rate limit policies
You get back
Rate limiting middleware, configuration, Redis-backed counter, response header injection, and tests

When to use rate-limiting-apis

  • Preventing API abuse
  • Enforcing per-user quotas
  • Implementing sliding window rate limiting
  • Managing burst capacity for APIs

About this skill

Rate Limiting APIs

Overview

Implement sophisticated rate limiting using sliding window, token bucket, and fixed window counter algorithms with Redis-backed distributed state. Configure per-endpoint, per-user, and per-API-key limits with tiered quotas, burst allowances, and standard response headers that communicate limit status to API consumers.

Prerequisites

  • Redis 6+ for distributed rate limit state (required for multi-instance deployments)
  • Rate limiting library: rate-limiter-flexible (Node.js), slowapi (Python/FastAPI), or Bucket4j (Java)
  • API key or user identification mechanism for per-consumer tracking
  • Monitoring for rate limit hit rates and rejected request metrics
  • Documentation system for publishing rate limit policies to API consumers

Instructions

  1. Analyze endpoint traffic patterns using Read and Grep on access logs or metrics to determine appropriate rate limits per endpoint category (read-heavy, write-heavy, resource-intensive).
  2. Select the rate limiting algorithm per endpoint: token bucket for bursty traffic allowance, sliding window log for precise per-second limits, or fixed window counter for simple quota enforcement.
  3. Implement rate limiting middleware that extracts the client identifier (API key from header, user ID from JWT, or IP address as fallback) and checks against the configured limit.
  4. Configure tiered rate limits per API consumer plan: Free (100 req/min), Pro (1000 req/min), Enterprise (10000 req/min) with per-endpoint overrides for expensive operations.
  5. Add burst allowance using token bucket: allow 2x the sustained rate for 10 seconds to handle legitimate traffic spikes without penalizing well-behaved clients.
  6. Set standard rate limit response headers on every response: X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset (Unix timestamp), and RateLimit-Policy (draft IETF standard).
  7. Return 429 Too Many Requests with Retry-After header (seconds until next allowed request) and a JSON body explaining the limit, current usage, and reset time.
  8. Implement rate limit bypass for internal service-to-service calls using shared secret or mutual TLS identification to prevent internal traffic from consuming consumer quotas.
  9. Write tests that verify rate limits engage at exact thresholds, headers reflect correct remaining counts, and limits reset at the configured window boundary.

See ${CLAUDE_SKILL_DIR}/references/implementation.md for the full implementation guide.

Output

  • ${CLAUDE_SKILL_DIR}/src/middleware/rate-limiter.js - Rate limiting middleware with algorithm selection
  • ${CLAUDE_SKILL_DIR}/src/config/rate-limits.js - Per-endpoint and per-tier rate limit configuration
  • ${CLAUDE_SKILL_DIR}/src/utils/rate-limit-store.js - Redis-backed distributed counter implementation
  • ${CLAUDE_SKILL_DIR}/src/middleware/rate-limit-headers.js - Standard rate limit response header injection
  • ${CLAUDE_SKILL_DIR}/tests/rate-limiting/ - Rate limit threshold verification tests
  • ${CLAUDE_SKILL_DIR}/docs/rate-limits.md - Consumer-facing rate limit documentation

Error Handling

ErrorCauseSolution
429 Too Many RequestsClient exceeded configured rate limit for the endpointReturn Retry-After header with seconds until reset; include limit details in JSON body
Redis connection failureRate limit state store unavailableFail open (allow requests) or fail closed (reject all) based on security posture; alert immediately
Clock skew between instancesDistributed rate limit windows misaligned across serversUse Redis server time (TIME command) as canonical clock; avoid relying on application server clocks
Inconsistent countsRace condition in read-check-increment cycleUse Redis MULTI/EXEC transaction or Lua script for atomic increment-and-check operations
Bypass abuseInternal bypass mechanism exploited by external clientValidate bypass credentials per-request; restrict bypass to specific IP ranges or mTLS certificates

Refer to ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error patterns.

Examples

Sliding window with Redis: Implement a sliding window rate limiter using Redis sorted sets, where each request adds a timestamped entry and the window count is computed by ZRANGEBYSCORE over the last 60 seconds.

Tiered SaaS quotas: Free tier gets 100 requests/minute with no burst, Pro tier gets 1000 requests/minute with 2x burst for 10 seconds, Enterprise tier gets 10000 requests/minute with custom per-endpoint overrides.

Login endpoint protection: Apply strict rate limit of 5 attempts per minute per IP on /auth/login to prevent brute force attacks, with progressive lockout (15 min, 1 hour, 24 hours) after repeated violations.

See ${CLAUDE_SKILL_DIR}/references/examples.md for additional examples.

Resources

Prerequisites

Redis 6+Rate limiting libraryAPI key or user identification mechanismMonitoring for rate limit hit rates and rejected request metrics

Limitations

  • Redis connection failure can lead to failing open or closed
  • Clock skew between instances can misalign distributed rate limit windows
  • Race conditions can cause inconsistent counts in read-check-increment cycles

How it compares

This skill automates the setup of various rate-limiting algorithms and distributed state management, unlike manual implementation which requires custom code for each algorithm and state synchronization.

Compared to similar skills

rate-limiting-apis side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
rate-limiting-apis (this skill)127dReviewAdvanced
bullmq-specialist256moNo flagsIntermediate
prisma-connection-pool-exhaustion16moReviewIntermediate
senior-backend147moReviewAdvanced

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