server-cache-lru
`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
$ npx -y skills add calcom/cal.com --agent claude-codeHow it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
Agent definition
server-cache-lru.mdtitle: Cross-Request LRU Caching impact: HIGH impactDescription: caches across requests tags: server, cache, lru, cross-request
Cross-Request LRU Caching
`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
**Implementation:**
import { LRUCache } from 'lru-cache'
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000 // 5 minutes
})
export async function getUser(id: string) {
const cached = cache.get(id)
if (cached) return cached
const user = await db.user.findUnique({ where: { id } })
cache.set(id, user)
return user
}
// Request 1: DB query, result cached
// Request 2: cache hit, no DB queryUse when sequential user actions hit multiple endpoints needing the same data within seconds.
**With Vercel's [Fluid Compute](https://vercel.com/docs/fluid-compute):** LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)
Repo: calcom/cal.com
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This file contains domain knowledge about the Cal.diy product and codebase. For coding guidelines and rules, see [`rules/`](rules/).
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