Core Web Vitals

SkillMedia

Diagnose and improve Largest Contentful Paint, Interaction to Next Paint, and Cumulative Layout Shift in this repository's Next.js App Router frontends. Use when auditing Core Web Vitals, investigating LCP, INP, or CLS regressions, or changing frontend loading, responsiveness, image, font, or layout behavior for performance.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Core Web Vitals skill

What this skill tells your AI

The instructions your AI receives, as published by theopenco/llmgateway in .agents/skills/core-web-vitals/SKILL.md and read by ahel’s review.

Measure the affected route before changing it. Do not apply generic performance advice without identifying the actual LCP element, slow interaction, or layout shift.

Targets and evidence

Use Google's current thresholds at the 75th percentile:

MetricGoodPoor
LCP≤ 2.5 s> 4 s
INP≤ 200 ms> 500 ms
CLS≤ 0.1> 0.25

Field data and lab data answer different questions. Check CrUX or PageSpeed Insights for user impact, then reproduce locally with Chrome DevTools or a repeatable browser trace. Lighthouse reports LCP and CLS, but cannot measure INP without real interaction; use its Total Blocking Time only as a lab proxy.

Official references:

Diagnose

  1. Identify the affected app and route. Read its page, layout, loading boundary, client components, data queries, images, fonts, and third-party scripts.
  2. Record a baseline on a production build with the same viewport, throttling, cache state, and interaction sequence used for the final comparison.
  3. Use the trace to identify the cause:
    • LCP: server delay, resource discovery, resource load, or render delay.
    • INP: input delay, event-handler work, or presentation delay.
    • CLS: the shifting element and the element that changed its geometry.
  4. Change the smallest cause supported by the trace.

Repository-specific fixes

These apps use Next.js 16 App Router. Prefer Server Components and existing TanStack Query patterns over client-side useEffect fetching.

For LCP:

  • Keep above-the-fold content in the initial server-rendered response when possible. Use a nearby loading boundary only when streaming improves the observed route.
  • Use next/image with correct width and height, or fill with a sized parent and an accurate sizes value.
  • Next.js 16 deprecates the Image priority prop; use preload only for the measured LCP image. Do not preload multiple competing images.
  • Remove request waterfalls and late client-only discovery shown in the trace.

For INP:

  • Trace the exact slow click, keypress, or tap. Reduce synchronous work in that path and avoid rerendering unrelated subtrees.
  • Provide immediate visual feedback, then defer only work that is not required for the next paint.
  • Virtualize or paginate large rendered collections when the trace shows DOM or reconciliation cost. Do not add memoization without a measured benefit.

For CLS:

  • Reserve dimensions for images, video, embeds, skeletons, banners, and async content before they load.
  • Keep loading and loaded states geometrically compatible.
  • Animate transform and opacity when possible instead of layout dimensions.
  • Inspect font fallback metrics before changing font-display; a blanket value is not a CLS fix.

Verify

Build the affected app through Turbo, run the same trace again, and compare the before/after measurements. Test relevant responsive breakpoints and both themes when layout or assets differ.

Run pnpm format and the full pnpm build before handoff. Report the measured baseline, the measured result, the route and conditions, and any field-data gap that cannot be validated locally.

Signals

GitHub stars
2k
Forks
181
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
core-web-vitals-theopenco
Source
github.com/theopenco/llmgateway