redis▌

Redis performance optimization across data structures, query engines, vector search, and semantic caching. \n \n Covers 29 prioritized rules across 11 categories including data modeling, memory management, Redis Query Engine (RQE), vector search with RedisVL, and LangCache semantic caching \n Provides structured guidance for connection pooling, JSON document handling, streams, clustering, security (ACLs), and observability \n Each rule includes explanations, correct examples, anti-patterns or us

Implement common Redis patterns for high-performance applications.

Implements API rate limiting and throttling controls using token bucket, sliding window, and fixed window algorithms to protect against brute force attacks, credential stuffing, resource exhaustion, and API abuse. The engineer configures per-user, per-IP, and per-endpoint rate limits using Redis-backed counters, API gateway plugins, or application middleware, and implements proper HTTP 429 responses with Retry-After headers. Activates for requests involving rate limiting implementation, API throttling setup, request quota management, or API abuse prevention.

Redis development best practices for caching, data structures, and high-performance operations. \n \n Covers five core data structures (strings, hashes, lists, sets, sorted sets) plus streams, with command examples and use-case guidance for each \n Includes three caching patterns (cache-aside, write-through, invalidation) with pseudo-code and TTL strategies to prevent thundering herd \n Addresses high availability via replication, Sentinel, and cluster configuration with hash tags for key distri

This directory contains comprehensive guides for using the @upstash/redis SDK. These skill files are designed to help developers and AI assistants understand and use the SDK effectively.