# Jeremylongshore Claude Code Plugins Plus Skills Vercel Performance Tuning

> Vercel Performance Tuning

- Skill: `tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-vercel-perfo` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-vercel-perfo`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-vercel-perfo/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-vercel-perfo

---

# Vercel Performance Tuning

## Overview
Optimize Vercel deployment performance across four levers: edge caching, bundle size reduction, serverless function cold start elimination, and Core Web Vitals improvement. Uses real Vercel cache headers, ISR, and Edge Functions for maximum performance.

## Prerequisites
- Vercel project deployed with accessible URL
- Access to Vercel Analytics (dashboard)
- Bundle analyzer available (`@next/bundle-analyzer` or similar)

## Instructions

### Step 1: Establish Performance Baseline
```bash
# Check deployment size and function count
vercel inspect https://my-app.vercel.app

# Run Lighthouse via CLI
npx lighthouse https://my-app.vercel.app --output=json --quiet \
  | jq '{performance: .categories.performance.score, lcp: .audits["largest-contentful-paint"].numericValue, cls: .audits["cumulative-layout-shift"].numericValue}'

# Check bundle size (Next.js)
ANALYZE=true npx next build
# Opens bundle analyzer report in browser
```

Enable Vercel Analytics in the dashboard under **Analytics** tab for ongoing monitoring.

### Step 2: Configure Edge Caching
```typescript
// api/cached-data.ts — cache API responses at the edge
import type { VercelRequest, VercelResponse } from '@vercel/node';

export default function handler(req: VercelRequest, res: VercelResponse) {
  // Cache at Vercel edge for 60s, serve stale for 300s while revalidating
  res.setHeader('Cache-Control', 's-maxage=60, stale-while-revalidate=300');
  res.json({ data: fetchData(), cachedAt: new Date().toISOString() });
}
```

```json
// vercel.json — cache static assets aggressively
{
  "headers": [
    {
      "source": "/static/(.*)",
      "headers": [
        { "key": "Cache-Control", "value": "public, max-age=31536000, immutable" }
      ]
    },
    {
      "source": "/api/public-data",
      "headers": [
        { "key": "Cache-Control", "value": "s-maxage=3600, stale-while-revalidate=86400" }
      ]
    }
  ]
}
```

Cache header reference:
| Header | Effect |
|--------|--------|
| `s-maxage=N` | Cache at Vercel edge for N seconds |
| `stale-while-revalidate=N` | Serve stale while revalidating in background |
| `max-age=N` | Cache in browser for N seconds |
| `immutable` | Never revalidate (use with content-hashed filenames) |
| `no-cache` | Always revalidate (edge still caches) |
| `no-store` | Never cache anywhere |

### Step 3: Incremental Static Regeneration (ISR)
```typescript
// app/products/[id]/page.tsx (Next.js App Router)
export const revalidate = 60; // Revalidate every 60 seconds

export default async function ProductPage({ params }) {
  const product = await fetchProduct(params.id);
  return <ProductView product={product} />;
}

// Generate static pages at build time, regenerate on-demand
export async function generateStaticParams() {
  const products = await fetchTopProducts(100);
  return products.map(p => ({ id: p.id }));
}
```

On-demand revalidation via API route:
```typescript
// api/revalidate.ts
import type { VercelRequest, VercelResponse } from '@vercel/node';

export default async function handler(req: VercelRequest, res: VercelResponse) {
  const secret = req.query.secret;
  if (secret !== process.env.REVALIDATION_SECRET) {
    return res.status(401).json({ error: 'Invalid secret' });
  }

  const path = req.query.path as string;
  await res.revalidate(path);
  res.json({ revalidated: true, path });
}
// Trigger: POST /api/revalidate?secret=xxx&path=/products/123
```

### Step 4: Reduce Cold Starts
```typescript
// Lazy initialization — don't import heavy modules at top level
// BAD: Cold start loads everything
import { PrismaClient } from '@prisma/client';
const prisma = new PrismaClient(); // Runs on every cold start

// GOOD: Lazy singleton — only connects when first used
let prisma: PrismaClient | null = null;
function getDb(): PrismaClient {
  if (!prisma) {
    prisma = new PrismaClient();
  }
  return prisma;
}

export default async function handler(req, res) {
  const users = await getDb().user.findMany();
  res.json(users);
}
```

Move latency-critical paths to Edge Functions (zero cold starts):
```typescript
// api/fast.ts
export const config = { runtime: 'edge' };

export default function handler(request: Request) {
  return Response.json({ fast: true }); // No cold start, runs globally
}
```

### Step 5: Bundle Size Optimization
```javascript
// next.config.js — tree-shaking and optimization
module.exports = {
  experimental: {
    optimizePackageImports: ['lodash', '@mui/material', '@mui/icons-material'],
  },
  // Exclude server-only deps from client bundle
  webpack: (config, { isServer }) => {
    if (!isServer) {
      config.resolve.fallback = { fs: false, net: false, tls: false };
    }
    return config;
  },
};
```

```bash
# Find large dependencies
npx depcheck
npx cost-of-modules

# Replace heavy libraries with lighter alternatives
# moment.js (300KB) → dayjs (2KB)
# lodash (72KB) → lodash-es with tree-shaking
# axios (29KB) → native fetch
```

### Step 6: Image Optimization
```typescript
// Use Vercel's built-in image optimization
import Image from 'next/image';

// Automatic: resizes, converts to WebP/AVIF, caches at edge
<Image
  src="/hero.jpg"
  width={1200}
  height={600}
  alt="Hero"
  priority  // Preload for LCP
  sizes="(max-width: 768px) 100vw, 1200px"
/>
```

```json
// vercel.json — configure image optimization
{
  "images": {
    "sizes": [640, 750, 828, 1080, 1200],
    "domains": ["images.example.com"],
    "formats": ["image/avif", "image/webp"],
    "minimumCacheTTL": 86400
  }
}
```

## Performance Budget Reference

| Metric | Target | Vercel Tool |
|--------|--------|-------------|
| LCP | < 2.5s | Vercel Analytics |
| FID/INP | < 200ms | Vercel Analytics |
| CLS | < 0.1 | Vercel Analytics |
| TTFB | < 200ms | Edge caching |
| Function cold start | < 500ms | Lazy init / Edge Functions |
| Bundle size (gzipped) | < 200KB JS | Bundle analyzer |

## Output
- Edge caching configured with optimal cache-control headers
- ISR or on-demand revalidation for dynamic pages
- Cold starts eliminated via lazy initialization and Edge Functions
- Bundle size reduced through tree-shaking and import optimization
- Image optimization configured

## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Cache not hitting | Missing `s-maxage` header | Add to response or vercel.json headers |
| ISR page always stale | `revalidate` set too high | Lower the revalidation interval |
| Large bundle warning | Importing entire library | Use specific imports: `import { map } from 'lodash-es'` |
| Cold start > 1s | Heavy top-level imports | Move to lazy initialization pattern |
| Images not optimized | External domain not whitelisted | Add to `images.domains` in config |

## Resources
- [Vercel Caching](https://vercel.com/docs/edge-network/caching)
- [ISR Documentation](https://vercel.com/docs/incremental-static-regeneration)
- [Vercel Analytics](https://vercel.com/docs/analytics)
- [Image Optimization](https://vercel.com/docs/image-optimization)
- [Function Configuration](https://vercel.com/docs/functions/configuring-functions)

## Next Steps
For cost optimization, see `vercel-cost-tuning`.

---
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<!-- tomevault:4.0:skill_md:2026-04-11 -->