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vercel-cost-tuningVercel cost tuning 命令行

Agent Skill

vercel-cost-tuning 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

987

周安装

33

GitHub Stars

2,114

下载量

261
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:vercel-cost-tuning(Vercel cost tuning 命令行)
来源仓库:https://github.com/jeremylongshore/claude-code-plugins-plus-skills
仓库路径:skills/vercel-cost-tuning
安装命令:
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill vercel-cost-tuning
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill vercel-cost-tuning

简介

用于优化 Vercel 部署成本,提供命令行工具辅助分析资源使用与费用。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中处理仓库状态、代码变更或协作事项时调用。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。
  • vercel-cost-tuning 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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.

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.94%
按下载量换算96

Claude

33.42%
按下载量换算87

Cursor

17.28%
按下载量换算45

Gemini CLI

9.91%
按下载量换算26

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权限和风险

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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