Technology & Engineering14 skills

Caching Services skills for AI agents

14 practitioner-grade caching services skills, each a focused Markdown document your agent loads into context on demand. Search them from Claude Desktop, Cursor or any MCP client, or pull one with the CLI.

$ npx skilldb search "caching services"

All 14 skills

Apache Ignite
Integrate Apache Ignite, a high-performance, fault-tolerant distributed in-memory data grid. Leverage its capabilities for caching, database, and processing to achieve extreme scalability and low-latency data access in demanding web applications, making it ideal for real-time analytics, transactional systems, and compute-intensive tasks.
258 lines
Cloudflare Kv
Integrate Cloudflare Workers KV for globally distributed edge key-value storage. Implement eventually consistent caching, static asset serving, and configuration management in Cloudflare Workers and Pages Functions.
189 lines
Dragonfly
Integrate Dragonfly, a high-performance, in-memory data store compatible with Redis and Memcached APIs. Leverage its efficiency for caching, real-time data, and session management, reducing resource consumption and improving throughput for demanding web applications.
264 lines
Garnet
Integrate Garnet, Microsoft's high-performance, open-source remote cache and storage system. Leverage its Redis-compatible API for extreme throughput and low-latency data access in demanding web applications, making it ideal for caching, session management, and real-time data needs.
321 lines
Hazelcast
Hazelcast is an open-source in-memory data grid (IMDG) that provides distributed caching, data partitioning, and stream processing capabilities. It's ideal for high-performance, low-latency applications requiring scalable data storage and processing across a cluster, offering both client-server and embedded deployment options.
248 lines
Keydb
Integrate KeyDB, a high-performance, multi-threaded in-memory data store compatible with the Redis API. Leverage its architecture for enhanced vertical scalability, caching, and real-time data processing in demanding web applications, making optimal use of modern multi-core CPUs.
227 lines
Memcached
Integrate Memcached for high-performance, distributed in-memory caching. Configure connection pooling, consistent hashing, and expiration policies for reducing database load in read-heavy applications.
167 lines
Next Cache
Implement Next.js built-in caching strategies including ISR, data cache, full route cache, revalidation, and cache tags. Optimize performance using the App Router's caching layers without external services.
168 lines
React Query Cache
Implement TanStack React Query for client-side caching and server state management. Configure stale times, cache invalidation, optimistic updates, and prefetching for responsive data-driven React applications.
198 lines
Redis
Integrate Redis caching into Node.js/TypeScript applications using ioredis. Apply cache-aside patterns, TTL strategies, pub/sub messaging, and connection pooling for high-performance data access layers.
166 lines
Swr
Implement SWR (stale-while-revalidate) for lightweight client-side data fetching and caching in React applications. Configure revalidation strategies, mutations, and global settings for responsive UIs with minimal boilerplate.
207 lines
Upstash Redis
Integrate Upstash serverless Redis for edge and serverless applications. Use the HTTP-based REST API for Vercel Edge Functions, Cloudflare Workers, and other environments without persistent TCP connections.
168 lines
Valkey
Integrate Valkey, a high-performance, open-source in-memory data structure store. Leverage its versatile data structures and Redis-compatible API for lightning-fast caching, real-time analytics, session management, and message brokering in demanding web applications.
208 lines
Vercel Kv
Integrate Vercel KV (Redis-based) for caching and data storage in Next.js applications. Use the built-in SDK for edge-compatible key-value operations, rate limiting, and session management on Vercel's platform.
176 lines