VE

vercel-cost-tuning

Tunes Vercel project configurations to optimize costs and manage resource usage.

Install

mkdir -p .claude/skills/vercel-cost-tuning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8500" && unzip -o skill.zip -d .claude/skills/vercel-cost-tuning && rm skill.zip

Installs to .claude/skills/vercel-cost-tuning

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Optimize Vercel costs through plan selection, function efficiency, and
70 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Analyze Vercel billing and cost drivers
  • Right-size serverless function memory allocation
  • Implement edge caching to reduce function invocations
  • Configure spend management and budget alerts
  • Optimize image usage and bandwidth consumption

How it works

It use the Fluid Compute pricing model by identifying high-cost drivers like function execution time and bandwidth, then applying caching and resource-sizing optimizations.

Inputs & outputs

You give it
Vercel usage data and billing metrics
You get back
Cost optimization strategy and configuration

When to use vercel-cost-tuning

  • Analyze current Vercel monthly billing
  • Reduce serverless function execution costs
  • Configure spend management and budget alerts
  • Optimize image usage to save costs

About this skill

Vercel Cost Tuning

Overview

Optimize Vercel costs by understanding the Fluid Compute pricing model, reducing function execution time, leveraging edge caching to avoid function invocations, and configuring spend management. Covers plan comparison, cost drivers, and monitoring.

Prerequisites

  • Access to Vercel billing dashboard
  • Understanding of current deployment architecture
  • Access to Vercel Analytics for usage patterns

Instructions

Step 1: Understand the Pricing Model

Vercel uses Fluid Compute pricing (for new projects):

ResourceHobby (Free)Pro ($20/member/mo)Enterprise
Bandwidth100 GB1 TB includedCustom
Serverless Execution100 GB-hrs1000 GB-hrs includedCustom
Edge Function invocations500K1M includedCustom
Edge Middleware invocations1M1M includedCustom
Image Optimizations10005000 includedCustom
Builds per day60006000Custom
Concurrent builds11 (more available)Custom

Fluid Compute billing breakdown:

  • Active CPU time: charged per ms of actual CPU usage
  • Provisioned memory: charged per GB-second of allocated memory
  • Benefit: you pay for actual work, not idle waiting (e.g., waiting for a database response)

Step 2: Identify Cost Drivers

# Check usage via API
curl -s -H "Authorization: Bearer $VERCEL_TOKEN" \
  "https://api.vercel.com/v2/usage" | jq .

# Top cost drivers on Vercel:
# 1. Serverless function execution time (CPU + memory)
# 2. Bandwidth (large responses, unoptimized images)
# 3. Edge Middleware invocations (runs on EVERY request)
# 4. Image optimizations (each unique transform costs)
# 5. Build minutes (frequent deploys or slow builds)

Step 3: Reduce Function Execution Costs

// 1. Right-size function memory — don't over-allocate
// vercel.json
{
  "functions": {
    "api/lightweight.ts": { "memory": 128 },    // Simple JSON responses
    "api/standard.ts": { "memory": 512 },       // Database queries
    "api/heavy.ts": { "memory": 1024 }          // Image processing
  }
}

// 2. Move read-only endpoints to Edge Functions (cheaper, no cold starts)
// api/config.ts
export const config = { runtime: 'edge' };
export default function handler() {
  return Response.json({ features: ['a', 'b'] });
}

// 3. Cache function responses at the edge
// Eliminates function invocations entirely for cached routes
export default function handler(req, res) {
  res.setHeader('Cache-Control', 's-maxage=3600, stale-while-revalidate=86400');
  res.json(data);
}

Step 4: Reduce Bandwidth Costs

// vercel.json — compress and cache aggressively
{
  "headers": [
    {
      "source": "/static/(.*)",
      "headers": [
        { "key": "Cache-Control", "value": "public, max-age=31536000, immutable" }
      ]
    }
  ],
  "images": {
    "sizes": [640, 750, 1080],
    "formats": ["image/avif", "image/webp"],
    "minimumCacheTTL": 86400
  }
}

Key bandwidth reducers:

  • Use Vercel's image optimization (auto WebP/AVIF conversion)
  • Set aggressive cache headers on static assets
  • Use ISR to serve static HTML instead of SSR
  • Compress API responses (Vercel auto-compresses with Brotli)

Step 5: Optimize Middleware Costs

Middleware runs on every matched request. Minimize its scope:

// middleware.ts — scope to specific paths only
export const config = {
  matcher: [
    // Only run middleware on API routes and protected pages
    '/api/:path*',
    '/dashboard/:path*',
    // Skip static files, images, and public assets
    '/((?!_next/static|_next/image|favicon.ico|public).*)',
  ],
};

export function middleware(request) {
  // Keep logic minimal — this runs on every matched request
  // Avoid: database queries, external API calls, heavy computation
  // Good: cookie checks, header modifications, redirects
}

Step 6: Configure Spend Management

In the Vercel dashboard under Settings > Billing > Spend Management:

Default budget: $200/month on-demand usage
Options:
- Set custom budget limit
- Enable hard limit (pauses all projects when reached)
- Configure email alerts at 50%, 75%, 90%, 100%
# Check current usage against budget via API
curl -s -H "Authorization: Bearer $VERCEL_TOKEN" \
  "https://api.vercel.com/v2/usage?teamId=team_xxx" \
  | jq '{period: .period, bandwidth: .bandwidth, execution: .serverlessFunctionExecution}'

Cost Optimization Checklist

ActionImpactEffort
Add s-maxage cache headersHigh — eliminates function invocationsLow
Use Edge Functions for simple endpointsMedium — cheaper than serverlessLow
Right-size function memoryMedium — reduces GB-hr costLow
Scope middleware matcherMedium — reduces edge invocationsLow
Enable image optimizationMedium — reduces bandwidthLow
Use ISR instead of SSRHigh — serves cached HTMLMedium
Optimize build speedLow — reduces build minutesMedium
Set spend management alertsSafety — prevents surprise billsLow

Output

  • Function memory right-sized per endpoint
  • Edge caching reducing function invocations
  • Middleware scoped to minimize invocations
  • Spend management configured with budget alerts
  • Usage monitoring via API

Error Handling

ErrorCauseSolution
Unexpected bill spikeUncached high-traffic endpointAdd s-maxage to the response
Projects pausedHard spending limit reachedIncrease limit or optimize usage
Image optimization quota exceededToo many unique image transformsReduce sizes array, increase cache TTL
Build minutes exceededSlow builds or too many deploysUse ignoreCommand to skip non-code changes

Resources

Next Steps

For reference architecture, see vercel-reference-architecture.

When not to use it

  • Optimizing costs for non-Vercel infrastructure
  • Reducing costs for projects not using Fluid Compute

Prerequisites

Access to Vercel billing dashboardUnderstanding of current deployment architectureAccess to Vercel Analytics

Limitations

  • Hard spending limits pause all projects when reached
  • Image optimization quota is based on unique transforms

How it compares

It focuses on Vercel-specific resource optimization techniques rather than general cloud cost-cutting strategies.

Compared to similar skills

vercel-cost-tuning side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
vercel-cost-tuning (this skill)027dReviewIntermediate
model-usage52moReviewBeginner
monitoring-whale-activity327dReviewIntermediate
klingai-cost-controls127dReviewBeginner

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