Agent skill · data analytics · aj-geddes
query-caching-strategies
Implement query caching strategies to improve performance. Use when setting up caching layers, configuring Redis, or optimizing database query response times.
Why this skill is useful
Provides specific caching strategies and code examples for implementing Redis and Memcached that the AI wouldn't reliably generate on its own.
What it needs
Requires redis installed locally. About 1k tokens when loaded. Last updated 2026-03-04. 307 stars on the source repository.
What this skill does
Query Caching Strategies Table of Contents Overview When to Use Quick Start Reference Guides Best Practices Overview Implement multi-level caching strategies using Redis, Memcached, and database-level caching. Covers cache invalidation, TTL strategies, and cache warming patterns. When to Use Query result caching High-read workload optimization Reducing database load Improving response time Cache layer selection Cache invalidation patterns Distributed cache setup Quick Start Minimal working example: Reference Guides Detailed implementations in the references/ directory: Guide Contents --- --- Redis Caching with PostgreSQL Redis Caching with PostgreSQL Memcached Caching Memcached Caching PostgreSQL Query Cache PostgreSQL Query Cache MySQL Query Cache MySQL Query Cache Event-Based Invalidation Event-Based Invalidation Time-Based Invalidation Time-Based Invalidation, LRU Cache Eviction Best Practices ✅ DO Follow established patterns and conventions Write clean, maintainable code Add appropriate documentation Test thoroughly before deploying ❌ DON'T Skip testing or validation Ignore error handling Hard-code configuration values
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aj-geddes/query-caching-strategies