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Agent Skill · 研究检索

web-performance-optimization(网络性能优化)

web-performance-optimization 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

web-performance-optimization 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 69,971。

总安装 214周安装 9GitHub Stars 652下载 75核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:web-performance-optimization(网络性能优化)
来源仓库:https://github.com/fcakyon/claude-codex-settings
仓库路径:skills/web-performance-optimization
安装命令:
npx skills add https://github.com/fcakyon/claude-codex-settings --skill web-performance-optimization
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/fcakyon/claude-codex-settings --skill web-performance-optimization

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

web-performance-optimization 提供 Web Vitals 指标与性能审计工具链,支持 Lighthouse 与 DevTools 集成。适用于识别渲染阻塞、资源加载瓶颈与优化关键请求路径以提升评分。

通过 npx skills add 命令安装,优先调用 Retrieval MCP 工具获取最新阈值与建议。优化前应在 staging 环境验证变更,避免因激进策略导致功能异常或可用性下降。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/web-performance-optimization

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/fcakyon/claude-codex-settings --skill web-perf…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

web-performance-optimization 怎么安装?

在终端执行 npx skills add https://github.com/fcakyon/claude-codex-settings --skill web-performance-op…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

web-performance-optimization 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

web-performance-optimization 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

web-performance-optimization 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

web-performance-optimization 用的人多吗?

公开数据是累计安装 214 次,近一周安装 9 次,下载 75 次,GitHub 652 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

web-performance-optimization 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
web-performance-optimization

网络性能优化 · 本页

214652操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Web Performance Audit

Your knowledge of web performance metrics, thresholds, and tooling APIs may be outdated. Prefer retrieval over pre-training when citing specific numbers or recommendations.

Retrieval Sources

SourceHow to retrieveUse for
web.devhttps://web.dev/articles/vitalsCore Web Vitals thresholds, definitions
Chrome DevTools docshttps://developer.chrome.com/docs/devtools/performanceTooling APIs, trace analysis
Lighthouse scoringhttps://developer.chrome.com/docs/lighthouse/performance/performance-scoringScore weights, metric thresholds

FIRST: Verify MCP Tools Available

Run this before starting. Try calling navigate_page or performance_start_trace. If unavailable, STOP—the chrome-devtools MCP server isn't configured.

Ask the user to add this to their MCP config:

"chrome-devtools": {
  "type": "local",
  "command": ["npx", "-y", "chrome-devtools-mcp@latest"]
}

Key Guidelines

  • Be assertive: Verify claims by checking network requests, DOM, or codebase—then state findings definitively.
  • Verify before recommending: Confirm something is unused before suggesting removal.
  • Quantify impact: Use estimated savings from insights. Don't prioritize changes with 0ms impact.
  • Skip non-issues: If render-blocking resources have 0ms estimated impact, note but don't recommend action.
  • Be specific: Say "compress hero.png (450KB) to WebP" not "optimize images".
  • Prioritize ruthlessly: A site with 200ms LCP and 0 CLS is already excellent—say so.

Quick Reference

TaskTool Call
Load pagenavigate_page(url: "...")
Start traceperformance_start_trace(autoStop: true, reload: true)
Analyze insightperformance_analyze_insight(insightSetId: "...", insightName: "...")
List requestslist_network_requests(resourceTypes: ["Script", "Stylesheet",...])
Request detailsget_network_request(reqid: <id>)
A11y snapshottake_snapshot(verbose: true)

Workflow

Copy this checklist to track progress:

Audit Progress:
- [ ] Phase 1: Performance trace (navigate + record)
- [ ] Phase 2: Core Web Vitals analysis (includes CLS culprits)
- [ ] Phase 3: Network analysis
- [ ] Phase 4: Accessibility snapshot
- [ ] Phase 5: Codebase analysis (skip if third-party site)

Phase 1: Performance Trace

  1. Navigate to the target URL: navigate_page(url: "<target-url>")
  2. Start a performance trace with reload to capture cold-load metrics: performance_start_trace(autoStop: true, reload: true)
  3. Wait for trace completion, then retrieve results.

Troubleshooting:

  • If trace returns empty or fails, verify the page loaded correctly with navigate_page first
  • If insight names don't match, inspect the trace response to list available insights

Phase 2: Core Web Vitals Analysis

Use performance_analyze_insight to extract key metrics.

Note: Insight names may vary across Chrome DevTools versions. If an insight name doesn't work, check the insightSetId from the trace response to discover available insights.

Common insight names:

MetricInsight NameWhat to Look For
LCPLCPBreakdownTime to largest contentful paint; breakdown of TTFB, resource load, render delay
CLSCLSCulpritsElements causing layout shifts (images without dimensions, injected content, font swaps)
Render BlockingRenderBlockingCSS/JS blocking first paint
Document LatencyDocumentLatencyServer response time issues
Network DependenciesNetworkRequestsDepGraphRequest chains delaying critical resources

Example:

performance_analyze_insight(insightSetId: "<id-from-trace>", insightName: "LCPBreakdown")

Key thresholds (good/needs-improvement/poor):

  • TTFB: < 800ms / < 1.8s / > 1.8s
  • FCP: < 1.8s / < 3s / > 3s
  • LCP: < 2.5s / < 4s / > 4s
  • INP: < 200ms / < 500ms / > 500ms
  • TBT: < 200ms / < 600ms / > 600ms
  • CLS: < 0.1 / < 0.25 / > 0.25
  • Speed Index: < 3.4s / < 5.8s / > 5.8s

Phase 3: Network Analysis

List all network requests to identify optimization opportunities:

list_network_requests(resourceTypes: ["Script", "Stylesheet", "Document", "Font", "Image"])

Look for:

  1. Render-blocking resources: JS/CSS in <head> without async/defer/media attributes
  2. Network chains: Resources discovered late because they depend on other resources loading first (e.g., CSS imports, JS-loaded fonts)
  3. Missing preloads: Critical resources (fonts, hero images, key scripts) not preloaded
  4. Caching issues: Missing or weak Cache-Control, ETag, or Last-Modified headers
  5. Large payloads: Uncompressed or oversized JS/CSS bundles
  6. Unused preconnects: If flagged, verify by checking if ANY requests went to that origin. If zero requests, it's definitively unused—recommend removal. If requests exist but loaded late, the preconnect may still be valuable.

For detailed request info:

get_network_request(reqid: <id>)

Phase 4: Accessibility Snapshot

Take an accessibility tree snapshot:

take_snapshot(verbose: true)

Flag high-level gaps:

  • Missing or duplicate ARIA IDs
  • Elements with poor contrast ratios (check against WCAG AA: 4.5:1 for normal text, 3:1 for large text)
  • Focus traps or missing focus indicators
  • Interactive elements without accessible names

Phase 5: Codebase Analysis

Skip if auditing a third-party site without codebase access.

Analyze the codebase to understand where improvements can be made.

Detect Framework & Bundler

Search for configuration files to identify the stack:

ToolConfig Files
Webpackwebpack.config.js, webpack.*.js
Vitevite.config.js, vite.config.ts
Rolluprollup.config.js, rollup.config.mjs
esbuildesbuild.config.js, build scripts with esbuild
Parcel.parcelrc, package.json (parcel field)
Next.jsnext.config.js, next.config.mjs
Nuxtnuxt.config.js, nuxt.config.ts
SvelteKitsvelte.config.js
Astroastro.config.mjs

Also check package.json for framework dependencies and build scripts.

Tree-Shaking & Dead Code

  • Webpack: Check for mode: 'production', sideEffects in package.json, usedExports optimization
  • Vite/Rollup: Tree-shaking enabled by default; check for treeshake options
  • Look for: Barrel files (index.js re-exports), large utility libraries imported wholesale (lodash, moment)

Unused JS/CSS

  • Check for CSS-in-JS vs. static CSS extraction
  • Look for PurgeCSS/UnCSS configuration (Tailwind's content config)
  • Identify dynamic imports vs. eager loading

Polyfills

  • Check for @babel/preset-env targets and useBuiltIns setting
  • Look for core-js imports (often oversized)
  • Check browserslist config for overly broad targeting

Compression & Minification

  • Check for terser, esbuild, or swc minification
  • Look for gzip/brotli compression in build output or server config
  • Check for source maps in production builds (should be external or disabled)

Output Format

Present findings as:

  1. Core Web Vitals Summary - Table with metric, value, and rating (good/needs-improvement/poor)
  2. Top Issues - Prioritized list of problems with estimated impact (high/medium/low)
  3. Recommendations - Specific, actionable fixes with code snippets or config changes
  4. Codebase Findings - Framework/bundler detected, optimization opportunities (omit if no codebase access)

平台分布

Codex

33.53%
按下载量换算25

Claude

28.35%
按下载量换算21

Cursor

20.1%
按下载量换算15

Gemini CLI

10.36%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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