Intelligent media optimization with automated workflows for images, videos, and SVGs. Includes decision trees that detect LCP images (triggers format/lazy-loading/priority analysis), identify layout shift risks (missing dimensions), and flag lazy loading issues (above-fold lazy or below-fold eager). Features workflows for complete media audit, LCP image investigation, video performance (poster optimization), and SVG embedded bitmap detection. Cross-skill integration with Core Web Vitals (LCP/CLS impact) and Loading (priority hints, resource preloading). Provides performance budgets and format recommendations based on content type. Use when the user asks about image optimization, LCP is an image/video, layout shifts from media, or media loading strategy. Compatible with Chrome DevTools MCP.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
JavaScript snippets for measuring web performance in Chrome DevTools.
mcp__chrome-devtools__evaluate_script and read the object it returns. The scripts have no console output, so the returned object is the result: script, status and the metric data (value, rating, details, items, issues), as described in references/schema.md.status is "tracking", the script keeps observing the page. After the interactions, call the function named in getDataFn with another mcp__chrome-devtools__evaluate_script call, for example getINP(), and read the object it returns.status is "error" or "unsupported", read error: the page may not have loaded yet, or the browser lacks the API.Without Chrome DevTools MCP, run the same snippet with the webperf-snippets CLI, which loads the page in headless Chromium and prints the same result objects: npx webperf-snippets <url> --snippet <Name> --json, where <Name> is the script name without .js. It needs Playwright and Chromium (npm install --save-dev webperf-snippets playwright, then npx playwright install chromium), and tracking snippets take --interact-script <file> to drive the interactions.
scripts/Image-Element-Audit.js — Image element auditscripts/Oversized-Images.js — Oversized imagesscripts/SVG-Embedded-Bitmap-Analysis.js — SVG embedded bitmap analysisscripts/Video-Element-Audit.js — Video element auditWhen the user asks for media optimization or "audit images and videos":
When the user asks "optimize images" or "check image performance":
When the user asks about images larger than needed, wasted bytes, blurry images, or srcset/sizes problems:
srcset usage of the flagged imagesWhen the user asks "optimize videos" or "check video performance":
When LCP is an image and needs optimization:
When CLS is caused by images without dimensions:
When the user asks about SVG performance or file sizes are large:
Use this decision tree to automatically run follow-up snippets based on results:
If images missing width/height attributes → Layout shift risk, run:
If images using wrong format (JPEG for graphics, PNG for photos) → Recommend:
If images much larger than display size → Recommend:
If above-the-fold images are lazy-loaded → Run:
If LCP image lacks fetchpriority="high" → Run:
If below-the-fold images are NOT lazy-loaded → Run:
If images have both loading="lazy" AND fetchpriority="high" → Run:
If images competing with critical resources → Run:
If images missing alt text → Accessibility issue, recommend adding descriptive alt text
If oversized images found → Recommend:
srcset with several widths and an accurate sizes attributeIf an oversized image is the LCP element → Run webperf-core-web-vitals:LCP.js and LCP-Subparts.js (large files inflate resource load duration)
If undersized (blurry) images found → Recommend a source with at least the needed pixels and a 2x candidate for high-density screens
If skipped images are lazy-loaded → Scroll to the end of the page and run the snippet again
If video is LCP candidate → Run:
If video missing poster → Recommend:
If video uses preload="auto" → Bandwidth concern, evaluate:
If autoplay video without muted → Browser will block, recommend:
If video missing multiple formats → Recommend:
If large video files (>5MB) → Recommend:
If bitmap images found in SVGs → Recommend:
If large embedded bitmaps (>100KB) → Critical inefficiency:
If multiple small bitmaps in SVG → Consider:
Use these thresholds to trigger recommendations:
Image File Sizes:
Image Formats:
Image Dimensions:
Video File Sizes:
Lazy Loading:
Priority Hints:
references/snippets.md — Descriptions and thresholds for each scriptreferences/schema.md — Return value schema for interpreting script outputまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Web performance measurement and debugging toolkit. Use when the user asks about web performance, wants to audit a page, or says "analyze performance", "debug lcp", "check ttfb", "measure core web vitals", "audit images", or similar.
日本語の概要は準備中です。原文の説明を表示しています。
Intelligent Core Web Vitals analysis with automated workflows and decision trees. Measures LCP, CLS, INP with guided debugging that automatically determines follow-up analysis based on results. Includes workflows for LCP deep dive (5 phases), CLS investigation (loading vs interaction), INP debugging (latency breakdown + attribution), and cross-skill integration with loading, interaction, and media skills. Use when the user asks about Core Web Vitals, LCP optimization, layout shifts, or interaction responsiveness. Compatible with Chrome DevTools MCP.
日本語の概要は準備中です。原文の説明を表示しています。
Intelligent interaction performance analysis with automated workflows for INP debugging, scroll jank investigation, and main thread blocking. Includes decision trees that automatically run script attribution when long frames detected, break down input latency phases, and correlate layout shifts with interactions. Features workflows for complete interaction audit, third-party script impact analysis, and animation performance debugging. Cross-skill integration with Core Web Vitals (INP/CLS correlation) and Loading (script execution analysis). Use when the user asks about slow interactions, janky scrolling, unresponsive pages, or INP optimization. Compatible with Chrome DevTools MCP.
日本語の概要は準備中です。原文の説明を表示しています。
Intelligent loading performance analysis with automated workflows for TTFB investigation (DNS/connection/server breakdown), render-blocking detection, script performance deep dive (first vs third-party attribution), font optimization, and resource hints validation. Includes decision trees that automatically analyze TTFB sub-parts when slow, detect script loading anti-patterns (async/defer/preload conflicts), identify render-blocking resources, and validate resource hints usage. Features workflows for complete loading audit (6 phases), backend performance investigation, and priority optimization. Cross-skill integration with Core Web Vitals (LCP resource loading), Interaction (script execution blocking), and Media (lazy loading strategy). Use when the user asks about TTFB, FCP, render-blocking, slow loading, font performance, script optimization, or resource hints. Compatible with Chrome DevTools MCP.
日本語の概要は準備中です。原文の説明を表示しています。
Intelligent network quality analysis with adaptive loading strategies. Detects connection type (2g/3g/4g), bandwidth, RTT, and save-data mode, then automatically triggers appropriate optimization workflows. Includes decision trees that recommend image compression for slow connections, critical CSS inlining for high RTT, and save-data optimizations (disable autoplay, reduce quality). Features connection-aware performance budgets (500KB for 2g, 1.5MB for 3g, 3MB for 4g+) and adaptive loading implementation guides. Cross-skill integration with Loading (TTFB impact), Media (responsive images), and Core Web Vitals (connection impact on LCP/INP). Use when the user asks about slow connections, mobile optimization, save-data support, or adaptive loading strategies. Compatible with Chrome DevTools MCP.
日本語の概要は準備中です。原文の説明を表示しています。