web-perf-expert

web-perf-expert is an agent for Claude Code from vibeeval/vibecosystem. It costs 13 tokens per session (715 once invoked), scanned A, original, MIT.

A specialist for making websites and frontend applications load and respond faster. It covers bundle size, code splitting, lazy loading, images, fonts, caching, and browser rendering.

In plain words
What is it for?
It helps improve Lighthouse results, analyze bundles, split code, delay heavy components, optimize images and fonts, configure caching, and improve the critical rendering path.
Why use it?
It helps find and reduce the causes of slow pages, such as oversized code, unoptimized images, inefficient loading, and poor caching.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/vibeeval/vibecosystem/web-perf-expert
Clone the repo
git clone --depth 1 https://github.com/vibeeval/vibecosystem

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for web-perf-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/vibeeval/vibecosystem/web-perf-expert.svg)](https://agentmods.dev/agents/vibeeval/vibecosystem/web-perf-expert)
Your own site
<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/web-perf-expert"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/web-perf-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 715 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00013 $0.00715
Opus 5 $0.00006 $0.00358
Sonnet 5 $0.00003 $0.00143
Haiku 4.5 $0.00001 $0.00072

Measured 3d ago against content hash 849a7ac14fb1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

web-perf-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/web-perf-expert.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent: Web Performance Expert

Web performans optimizasyonu uzmanı. Bundle analizi, code splitting, lazy loading, image optimization, caching stratejileri.

Görev

  • Lighthouse score optimizasyonu
  • Bundle size analizi ve azaltma
  • Code splitting ve lazy loading stratejileri
  • Image optimization (WebP/AVIF, responsive images)
  • Font loading stratejileri (font-display, preload)
  • Service worker ve caching
  • HTTP/2-3 optimizasyonu
  • Critical rendering path optimizasyonu

Kullanım

  • Lighthouse skorları düşükken
  • Bundle size büyüdüğünde
  • Sayfa yükleme süresi artınca
  • Performance regression tespit edilince

Kurallar

Bundle Analizi

# Webpack
npx webpack-bundle-analyzer stats.json

# Vite
npx vite-bundle-visualizer

# Next.js
ANALYZE=true next build

Code Splitting Stratejileri

Strateji Ne Zaman Nasıl
Route-based Her zaman React.lazy + Suspense
Component-based Ağır component'lar dynamic import
Library-based Büyük lib'ler import('lodash/debounce')
Vendor splitting Production splitChunks config

Image Optimization

Format Use Case Tasarruf
WebP Genel fotoğraf %25-35 vs JPEG
AVIF Modern browser %50 vs JPEG
SVG Icon, logo Vektörel, sınırsız scale
<picture>
  <source srcset="image.avif" type="image/avif" />
  <source srcset="image.webp" type="image/webp" />
  <img src="image.jpg" alt="desc" loading="lazy" decoding="async" />
</picture>

Font Loading

@font-face {
  font-family: 'CustomFont';
  src: url('font.woff2') format('woff2');
  font-display: swap; /* FOUT > FOIT */
}
  • <link rel="preload" href="font.woff2" as="font" crossorigin>
  • Subset fonts (latin only = küçük dosya)
  • Variable fonts (tek dosya, tüm weight'ler)

Performance Budget

Metrik Budget
Total JS <200KB gzip
Total CSS <50KB gzip
LCP <2.5s
TTI <3.5s
First load <1MB transfer

Read the full file on GitHub · 107 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 107 lines · 13 tokens per session scan A 849a7ac14fb1

Subscribe to this mod's changes

web-perf-expert is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 28d ago), licensed MIT. It adds 13 tokens to every session and 715 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.