caching-strategy
>
Works with
---
name: caching-strategy
description: >
license: MIT
---
# Caching Strategy
## Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
## Overview
Implement effective caching strategies to improve application performance, reduce latency, and decrease load on backend systems.
## When to Use
- Reducing database query load
- Improving API response times
- Handling high traffic loads
- Caching expensive computations
- Storing session data
- CDN integration for static assets
- Implementing distributed caching
- Rate limiting and throttling
## Quick Start
Minimal working example:
```typescript
import Redis from "ioredis";
interface CacheOptions {
ttl?: number; // Time to live in seconds
prefix?: string;
}
class CacheService {
private redis: Redis;
private defaultTTL = 3600; // 1 hour
constructor(redisUrl: string) {
this.redis = new Redis(redisUrl, {
retryStrategy: (times) => {
const delay = Math.min(times * 50, 2000);
return delay;
},
maxRetriesPerRequest: 3,
});
this.redis.on("connect", () => {
console.log("Redis connected");
});
this.redis.on("error", (error) => {
// ... (see reference guides for full implementation)
```
## Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents |
|---|---|
| [Redis Cache Implementation (Node.js)](references/redis-cache-implementation-nodejs.md) | Redis Cache Implementation (Node.js) |
| [Cache Decorator (Python)](references/cache-decorator-python.md) | Cache Decorator (Python) |
| [Multi-Level Cache](references/multi-level-cache.md) | Multi-Level Cache |
| [Cache Invalidation Strategies](references/cache-invalidation-strategies.md) | Cache Invalidation Strategies |
| [HTTP Caching Headers](references/http-caching-headers.md) | HTTP Caching Headers |
## Best Practices
### ✅ DO
- Set appropriate TTL values
- Implement cache warming for critical data
- Use cache-aside pattern for reads
- Monitor cache hit rates
- Implement graceful degradation on cache failure
- Use compression for large cached values
- Namespace cache keys properly
- Implement cache stampede prevention
- Use consistent hashing for distributed caching
- Monitor cache memory usage
### ❌ DON'T
- Cache everything indiscriminately
- Use caching as a fix for poor database design
- Store sensitive data without encryption
- Forget to handle cache misses
- Set TTL too long for frequently changing data
- Ignore cache invalidation strategies
- Cache without monitoring
- Store large objects without considerationMore Performance skills
seo-audit
coreyhaines31/marketingskills
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema. For AI search optimization, see ai-seo.
competitor-profiling
coreyhaines31/marketingskills
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.
vercel-optimize
vercel-labs/agent-skills
Use for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.

