Core Web Vitals
Addy OsmaniCommunityCreated by web-quality-skillsDistributed by Addy Osmani
- Skill
- Guidelines
- Software development
- MIT
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured approach to improving web performance by focusing on the three Core Web Vitals: Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS). It emphasizes a data-driven methodology, requiring users to measure performance using field data (CrUX) and lab traces before applying optimizations. The guide includes specific diagnostic techniques, common pitfalls, and framework-specific fixes for Next.js, React, and Vue, ensuring that performance improvements are based on evidence rather than assumptions.
What it does
- Provides a measurement-first workflow for identifying performance bottlenecks.
- Offers diagnostic steps for LCP, INP, and CLS issues using browser traces.
- Includes code patterns to resolve common performance regressions.
- Details how to use the Speculation Rules API for faster navigations.
- Provides framework-specific optimization advice for React, Next.js, and Vue.
- Supplies verification checklists to ensure fixes are effective.
When to use it
- When you need to improve Core Web Vitals scores for a website.
- When you are tasked with fixing specific LCP, INP, or CLS issues.
- When you need to optimize page experience based on real-user data.
- When you need to diagnose the cause of layout shifts or slow interactions.
Advantages
- Promotes evidence-based optimization over guesswork.
- Provides clear thresholds for 'Good', 'Needs work', and 'Poor' metrics.
- Includes actionable code snippets for common performance problems.
- Helps distinguish between field data and lab measurement limitations.
Usage examples
- “How can I improve my site's LCP score?”
- The agent will guide you through measuring your current LCP, identifying if the issue is server response time or resource loading, and applying fixes like preloading hero images or inlining critical CSS.
- “My page has a high CLS score. How do I fix it?”
- The agent will help you identify the shifted elements using a performance observer, suggest reserving space for dynamic content, and provide CSS patterns to stabilize layout shifts.
- “How do I diagnose a slow interaction on my site?”
- The agent will explain how to break down the INP into input delay, processing time, and presentation delay, and suggest techniques like yielding to the main thread.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/addyosmani/core-web-vitals/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip core-web-vitals.zip -d .agents/skills
Documentation by web-quality-skills
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. Prefer this sequence:
Check page-level CrUX p75 data, with a clearly labeled origin fallback when page data is unavailable.
Record a browser performance trace under stated conditions. With Chrome DevTools MCP, trace summaries can include CrUX alongside the observed lab metrics.
Analyze only the insights associated with the failing metric, then inspect the implicated code and resources.
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
<svg>element
Common LCP issues
1. Slow server response (TTFB > 800ms)
Fix: CDN, caching, optimized backend, edge rendering2. Render-blocking resources
<!-- ❌ Blocks rendering -->
<link rel="stylesheet" href="/all-styles.css">
<!-- ✅ Critical CSS inlined, rest deferred -->
<style>/* Critical above-fold CSS */</style>
<link rel="preload" href="/styles.css" as="style"
onload="this.onload=null;this.rel='stylesheet'">3. Slow resource load times
<!-- ❌ LCP image is discovered only after a stylesheet loads -->
<div class="hero"></div>
<!-- ✅ Discoverable in initial HTML and prioritized -->
<link rel="preload" href="/hero.webp" as="image" fetchpriority="high">
<img src="/hero.webp" alt="Hero" fetchpriority="high">Prefer a discoverable <img> 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
// ❌ 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.
<script type="speculationrules">
{
"prerender": [{
"where": { "href_matches": "/*" },
"eagerness": "moderate"
}]
}
</script>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 before hardcoding timing-sensitive behavior.
Caveats:
Bandwidth/CPU cost. Each prerender is roughly a full page load. Scope
wherecarefully (href_matchespatterns, exclude logout/checkout) and avoidimmediateoutside 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
prerenderingchangeevent ordocument.prerendering.Chromium-only. Safari and Firefox ignore the script — it's a progressive enhancement, never a regression.
LCP optimization checklist
- [ ] 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 <head>
- [ ] 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.
// 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 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 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. 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
// LCP: Use next/image with priority
import Image from 'next/image';
<Image src="/hero.jpg" priority fill alt="Hero" />
// INP: Use dynamic imports
const HeavyComponent = dynamic(() => import('./Heavy'), { ssr: false });
// CLS: Image component handles dimensions automaticallyReact
// LCP: Preload in head
<link rel="preload" href="/hero.jpg" as="image" fetchpriority="high" />
// INP: Memoize and useTransition
const [isPending, startTransition] = useTransition();
startTransition(() => setExpensiveState(newValue));
// CLS: Always specify dimensions in img tagsVue/Nuxt
<!-- LCP: Use nuxt/image with preload -->
<NuxtImg src="/hero.jpg" preload loading="eager" />
<!-- INP: Use async components -->
<component :is="() => import('./Heavy.vue')" />
<!-- CLS: Use aspect-ratio CSS -->
<img :style="{ aspectRatio: '16/9' }" />References
Detailed LCP optimization — read when an LCP trace points to discovery, loading, or render delay
Detailed INP optimization — read when a trace or field attribution identifies a slow interaction
Detailed CLS optimization — read when a trace or field attribution identifies unexpected shifts
Performance skill
Files
- ATTRIBUTION.mdAdded by AutoGineer928 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md9.5 KiB
- references/CLS.md3.9 KiB
- references/INP.md4.3 KiB
- references/LCP.md5.0 KiB
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Node.js
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- web-quality-skills
- Publisher
- Addy Osmani (Community)
- Distributed by
- Addy Osmani
- Source
- addyosmani/web-quality-skills · skills/core-web-vitals · commit afa8da9
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by web-quality-skills or Addy Osmani.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download core-web-vitals.zip