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技能库 智客分类:Agent 工作流 core-web-vitals

核心网络维度

优化Core Web Virtuals(LCP,INP,CLS),以利用野外和实验室证据改进页面体验. 被请求用于"改进Core Web Vitals","fix LCP","reduce CLS","优化INP","页面体验优化",或"固定布局变换"时使用.

28712 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

优化核心网络维度(LCP、INP、CLS),以利用实地和实验室证据改进页面体验

何时用

要求“改进核心网络维度”、“固定LCP”、“减少CLS”、“优化INP”、“页面体验优化”或“固定布局变化”

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Core Web Vitals optimization、Measure before optimizing、The three metrics、LCP: Largest Contentful Paint、Common LCP issues、LCP optimization checklist。

文件分析

文件分析:除 SKILL.md 外,正文引用了 references/MEASUREMENT.md、references/INP.md、references/CLS.md、references/RUM.md、references/LCP.md,属于带资源的技能包,这些文件按需再读。

官方 description(原文)

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience using field and lab evidence. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".

Core Web Vitals optimizationMeasure before optimizingThe three metricsLCP: Largest Contentful PaintCommon LCP issuesLCP optimization checklistLCP element identificationINP: Interaction to Next PaintCLS: Cumulative Layout ShiftMeasurement sourcesFramework quick fixesNext.js

· 许可:MIT

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
core-web-vitals
description
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience using field and lab evidence. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".
许可
MIT
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。
指令中引用的文件 · 5
  • references/MEASUREMENT.md
  • references/INP.md
  • references/CLS.md
  • references/RUM.md
  • references/LCP.md

以下路径提取自原文;文件是否齐全请以来源仓库中的完整目录为准。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

该技能引用了附属文件,请从来源获取完整目录;仅复制 SKILL.md 可能缺少依赖。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「core-web-vitals」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-166f47e505269d41-%E6%A0%B8%E5%BF%83%E7%BD%91%E7%BB%9C%E7%BB%B4%E5%BA%A6.html
请存为 .cursor/skills/core-web-vitals/SKILL.md 或 .claude/skills/core-web-vitals/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。
该技能还带 scripts/、references/、assets/ 等文件,请从 https://github.com/addyosmani/web-quality-skills 取完整目录,不要只建一个 SKILL.md。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/addyosmani/web-quality-skills' --list

npx skills add 'https://github.com/addyosmani/web-quality-skills' --skill 'core-web-vitals'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版
--- name: core-web-vitals description: Optimize Core Web Vitals (LCP, INP, CLS) for better page experience using field and lab evidence. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts". license: MIT metadata: author: web-quality-skills version: "2.0" --- # Core Web Vitals optimization Targeted optimization for the three Core Web Vitals using field data to identify user impact and browser traces to diagnose causes. ## Measure before optimizing When a runnable URL is available, read [the performance measurement workflow](../performance/references/MEASUREMENT.md). Prefer this sequence: 1. Check page-level CrUX p75 data, with a clearly labeled origin fallback when page data is unavailable. 2. Record a browser performance trace under stated conditions. With Chrome DevTools MCP, trace summaries can include CrUX alongside the observed lab metrics. 3. Analyze only the insights associated with the failing metric, then inspect the implicated code and resources. 4. Re-run equivalent lab measurements after the fix. Do not claim an immediate field improvement; CrUX and first-party RUM need new user visits. If only source code is available, identify likely causes but do not claim that LCP, INP, or CLS is failing without runtime evidence. ## The three metrics | Metric | Measures | Good | Needs work | Poor | |--------|----------|------|------------|------| | **LCP** | Loading | ≤ 2.5s | 2.5s – 4s | > 4s | | **INP** | Interactivity | ≤ 200ms | 200ms – 500ms | > 500ms | | **CLS** | Visual Stability | ≤ 0.1 | 0.1 – 0.25 | > 0.25 | Google measures at the **75th percentile** — 75% of page visits must meet "Good" thresholds. --- ## LCP: Largest Contentful Paint LCP measures when the largest visible content element renders. Usually this is: - Hero image or video - Large text block - Background image - `` element ### Common LCP issues **1. Slow server response (TTFB > 800ms)** ``` Fix: CDN, caching, optimized backend, edge rendering ``` **2. Render-blocking resources** ```html ``` **3. Slow resource load times** ```html
``` Prefer a discoverable `` with `fetchpriority="high"`. Add the preload only when the trace shows that the resource would otherwise be discovered late; duplicate or speculative preloads can compete for bandwidth. **4. Client-side rendering delays** ```javascript // ❌ Content loads after JavaScript useEffect(() => { fetch('/api/hero-text').then(r => r.json()).then(setHeroText); }, []); // ✅ Server-side or static rendering // Use SSR, SSG, or streaming to send HTML with content export async function getServerSideProps() { const heroText = await fetchHeroText(); return { props: { heroText } }; } ``` **5. Make navigations instant with the Speculation Rules API** For sites with predictable same-origin journeys, prerendering a likely next page can make a successful subsequent navigation much faster. Treat this as a measured navigation optimization, not a substitute for fixing the current page's LCP. ```html ``` Current Chrome behavior is specific enough to guide the choice: | `eagerness` | Trigger | |-------------|---------| | `conservative` | Pointer or touch down | | `moderate` | Desktop: 200ms hover, or earlier pointer down; mobile: viewport heuristics | | `eager` | Chrome 143+: desktop 10ms hover; mobile 50ms after the anchor enters the viewport | | `immediate` | As soon as the rules are observed | Start conservatively and measure prediction hit rate, transferred bytes, server load, and navigation improvement before expanding the rules. Recheck [Chrome's maintained eagerness documentation](https://developer.chrome.com/docs/web-platform/prerender-pages#eagerness) before hardcoding timing-sensitive behavior. Caveats: - **Bandwidth/CPU cost.** Each prerender is roughly a full page load. Scope `where` carefully (`href_matches` patterns, exclude logout/checkout) and avoid `immediate` outside small sites. - **Side effects fire early.** Analytics, ads, and any code that runs on load will fire when the prerender starts, not when the user navigates. Gate side effects on the [`prerenderingchange` event](https://developer.chrome.com/docs/web-platform/prerender-pages#detect_when_a_page_is_prerendered_or_used_for_a_full_navigation) or `document.prerendering`. - **Chromium-only.** Safari and Firefox ignore the script — it's a progressive enhancement, never a regression. ### LCP optimization checklist ```markdown - [ ] TTFB < 800ms (use CDN, edge caching) - [ ] LCP resource is discoverable in initial HTML and prioritized; preload only if the trace shows late discovery - [ ] LCP image optimized (WebP/AVIF, correct size) - [ ] Critical CSS inlined (< 14KB) - [ ] No render-blocking JavaScript in - [ ] Fonts don't block text rendering (font-display: swap) - [ ] LCP element in initial HTML (not JS-rendered) - [ ] Speculation Rules added for likely-next navigations (moderate eagerness) ``` ### LCP element identification This snippet diagnoses the current page session. It is not field data. ```javascript // Find your LCP element new PerformanceObserver((list) => { const entries = list.getEntries(); const lastEntry = entries[entries.length - 1]; console.log('LCP element:', lastEntry.element); console.log('LCP time:', lastEntry.startTime); }).observe({ type: 'largest-contentful-paint', buffered: true }); ``` --- ## INP: Interaction to Next Paint INP measures responsiveness across clicks, taps, and key presses during a visit. Diagnose its input delay, processing time, and presentation delay separately; a slow interaction may involve main-thread contention before the handler, expensive application work, or delayed rendering after it. When field INP is poor or a trace identifies a slow interaction, read [the INP reference](references/INP.md) for trace interpretation, yielding patterns, third-party and rendering causes, a single-session observer, and first-party attribution. --- ## CLS: Cumulative Layout Shift CLS measures unexpected layout shifts across a page visit. Use field attribution or a trace to identify the shifted node and the trigger; do not assume the visible victim caused the shift. When field CLS is poor or a trace reports shifts, read [the CLS reference](references/CLS.md) for reserved-space patterns, dynamic content, font and animation fixes, a debugging observer, and a verification checklist. --- ## Measurement sources | Source | Use | |--------|-----| | Browser performance trace (Chrome DevTools MCP: `performance_start_trace`) | Observe one load or interaction and diagnose focused insights; use included CrUX context when available | | CrUX or Search Console | Prioritize aggregated real-user outcomes at p75 | | Lighthouse CLI or PageSpeed Insights | Controlled lab fallback when DevTools tools are unavailable | | First-party RUM | Segment current production experience by route, device, release, and attribution | | Raw `PerformanceObserver` | Inspect one page session during debugging | Do not route performance through Chrome DevTools MCP's `lighthouse_audit`; that capability intentionally covers non-performance Lighthouse categories. Do not compare a single lab value directly with a field p75 as if they were equivalent samples. When adding or reviewing production collection, read [the first-party RUM reference](../performance/references/RUM.md). Prefer the `web-vitals` library because raw browser APIs do not by themselves implement every Core Web Vital's lifecycle and reporting rules. --- ## Framework quick fixes ### Next.js ```jsx // LCP: Use next/image with priority import Image from 'next/image'; // INP: Use dynamic imports const HeavyComponent = dynamic(() => import('./Heavy'), { ssr: false }); // CLS: Image component handles dimensions automatically ``` ### React ```jsx // LCP: Preload in head // INP: Memoize and useTransition const [isPending, startTransition] = useTransition(); startTransition(() => setExpensiveState(newValue)); // CLS: Always specify dimensions in img tags ``` ### Vue/Nuxt ```vue ``` ## References - [Detailed LCP optimization](references/LCP.md) — read when an LCP trace points to discovery, loading, or render delay - [Detailed INP optimization](references/INP.md) — read when a trace or field attribution identifies a slow interaction - [Detailed CLS optimization](references/CLS.md) — read when a trace or field attribution identifies unexpected shifts - [web.dev LCP](https://web.dev/articles/lcp) - [web.dev INP](https://web.dev/articles/inp) - [web.dev CLS](https://web.dev/articles/cls) - [Performance skill](../performance/SKILL.md)

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