Udit TakkarandGitHub
7a9fdd5a0c
## What does this PR do? This PR adds https://vercel.com/blog/introducing-react-best-practices for your coding agent using `npx add-skill vercel-labs/agent-skills` command The skills are added to `.claude/`, `.cursor/`, and `.opencode/` directories to provide React and Next.js performance optimization guidance for AI-assisted workflows. ## Updates since last revision Addressed Cubic AI review feedback for issues with confidence >= 9/10: - **rerender-dependencies.md** - Replaced `console.log(user.id)` with `fetchUserDetails(user.id)` to avoid logging sensitive information - **server-after-nonblocking.md** - Removed `sessionCookie` from `logUserAction` call to avoid logging sensitive authentication data, added `await` to async call - **bundle-conditional.md** - Added `loadError` state and `setLoadError` setter to fix undefined `setEnabled` reference - **advanced-event-handler-refs.md** - Updated `useWindowEvent` handler signature to accept `Event` parameter and forward it to the stored handler - **rerender-derived-state.md** - Closed `<nav>` elements in both examples for valid JSX Fixes applied to both `.claude` and `.cursor` skill directories for consistency. ## Mandatory Tasks (DO NOT REMOVE) - [x] I have self-reviewed the code (A decent size PR without self-review might be rejected). - [x] N/A I have updated the developer docs in /docs if this PR makes changes that would require a [documentation change](https://cal.com/docs). If N/A, write N/A here and check the checkbox. - [x] N/A, I confirm automated tests are in place that prove my fix is effective or that my feature works. ## How should this be tested? These are documentation files for AI coding agents. No runtime testing required - review the markdown files to verify the example code snippets are correct. ## Checklist for human review - [ ] Verify example code snippets in the skill files are syntactically correct - [ ] Confirm the fixes don't introduce new issues in the documentation examples - [ ] Check that `.claude` and `.cursor` directories have consistent content --- Link to Devin run: https://app.devin.ai/sessions/f7f7e67fdeea4b22a4817d63ed9e1759 Requested by: unknown ()
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title, impact, impactDescription, tags
| title | impact | impactDescription | tags |
|---|---|---|---|
| Cross-Request LRU Caching | HIGH | caches across requests | 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 query
Use when sequential user actions hit multiple endpoints needing the same data within seconds.
With Vercel's 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