caching-strategy

name	caching-strategy
description	Adds caching to expensive operations - Redis, in-memory, HTTP cache headers
argument-hint	["file-or-endpoint"]
user-invocable	true
allowed-tools	Read Grep Glob Edit
effort	medium

Caching Strategy

Target: $1 (or analyze top bottlenecks if not specified)

1. Identify cacheable operations:

grep -rn "db\.\|prisma\.\|fetch\|axios" ${1:-src/} --include="*.ts" | grep -v "test\|spec" | head -20

What's cacheable?

• Query results that change infrequently (user profile, product catalog)
• Expensive computations (aggregations, reports)
• External API responses (weather, exchange rates)

What's NOT cacheable?

• User-specific real-time data
• Transactional operations
• Anything that must be consistent

2. Choose caching layer by use case:

   • Redis: shared across instances, TTL, pub/sub invalidation
   • In-memory (Map): single instance, fastest, lost on restart
   • HTTP Cache-Control: browser/CDN caching for GET responses
   • React Query / SWR: client-side data caching

3. Implement with proper cache keys:

const cacheKey = `user:${userId}:profile`
const cached = await redis.get(cacheKey)
if (cached) return JSON.parse(cached)

const result = await db.user.findUnique(...)
await redis.set(cacheKey, JSON.stringify(result), 'EX', 300) // 5min TTL

4. Add cache invalidation on mutations.

5. Show estimated performance improvement.