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Google PageSpeed Insights Prompt Library
Ready-to-use AI prompts to analyze your Core Web Vitals, benchmark performance and SEO scores across desktop and mobile, and prioritize page-speed fixes. Customize with your page URL, then paste into ChatGPT, Claude, or Gemini.
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Showing 16 prompts
See available Google PageSpeed Insights metrics & breakdowns →Reporting
Core Web Vitals Summary
Get a concise snapshot of your page's Core Web Vitals health.
Pull the Google PageSpeed Insights field data for https://example.com. Show: First contentful paint (FCP), Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), and Time to first byte (TTFB), broken down by Device type. Include the FCP assessment, LCP assessment, INP assessment, CLS assessment, and TTFB assessment for each metric. Highlight any metric that is not in the "Good" range.
Reporting
Full Performance Report
Generate a comprehensive page-speed report across desktop and mobile.
Generate a full Google PageSpeed Insights report for https://example.com. Include: 1) Performance score, Accessibility score, Best practices score, and SEO score for both desktop and mobile (Device type). 2) Largest contentful paint (LCP), Interaction to next paint (INP), and Cumulative layout shift (CLS) by Device type. 3) The LCP assessment, INP assessment, and CLS assessment status for desktop and mobile. 4) A summary paragraph with 3 actionable recommendations.
Reporting
Lighthouse Score Scorecard
Report all four Lighthouse category scores at a glance.
From the Google PageSpeed Insights report for https://example.com, show the Performance score, Accessibility score, Best practices score, and SEO score broken down by Device type. Present each score out of 100, flag any score below 90, and note which category is the weakest on desktop versus mobile.
Reporting
Field Data Vitals Report
Report real-user Core Web Vitals field metrics for the page.
Build a Google PageSpeed Insights field data report for https://example.com. For the Web page Url, show First contentful paint (FCP), Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), and Time to first byte (TTFB), each with its FCP assessment, LCP assessment, INP assessment, CLS assessment, and TTFB assessment. Break out results by Device type and summarize whether the URL passes the Core Web Vitals assessment.
Optimization
LCP Optimization Plan
Identify what is slowing your Largest Contentful Paint and how to fix it.
Analyze the Google PageSpeed Insights data for https://example.com. Focus on Largest contentful paint (LCP) and Largest contentful paint (Lab test result) by Device type, alongside Time to first byte (TTFB) and the LCP assessment. Where LCP is not "Good", explain the likely causes (slow TTFB, render-blocking resources, large images) and recommend a prioritized list of fixes to bring LCP under 2.5s.
Optimization
Interactivity & Blocking Time Optimization
Reduce input delay by tackling INP and total blocking time.
From the Google PageSpeed Insights report for https://example.com, analyze Interaction to next paint (INP) and Total blocking time (Lab test result) by Device type, with the INP assessment. Identify whether the mobile experience is worse than desktop, explain likely JavaScript execution bottlenecks, and recommend concrete steps to lower INP and total blocking time.
Optimization
Layout Stability Optimization
Eliminate layout shifts hurting your CLS score.
Analyze the Google PageSpeed Insights data for https://example.com, focusing on Cumulative layout shift (CLS) and Cumulative layout shift (Lab test result) by Device type with the CLS assessment. Where CLS is not "Good", explain common causes (unsized images, injected content, web fonts) and recommend a prioritized set of fixes to stabilize the layout.
Optimization
Fix Prioritization Roadmap
Turn diagnostics into a ranked, high-impact fix list.
Using the Google PageSpeed Insights diagnostics for https://example.com, review First contentful paint (FCP), Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), and Time to first byte (TTFB) with their FCP assessment, LCP assessment, INP assessment, CLS assessment, and TTFB assessment by Device type. Rank the top improvement opportunities by estimated impact on the Performance score and produce a prioritized optimization roadmap.
Analysis
Desktop vs Mobile Comparison
Compare Core Web Vitals and scores across desktop and mobile.
Analyze the Google PageSpeed Insights data for https://example.com, comparing Device type = desktop versus mobile. For each device, show Performance score, Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), and Time to first byte (TTFB) with their assessments. Quantify the gap between desktop and mobile and explain which experience needs the most urgent attention.
Analysis
Lab vs Field Data Analysis
Reconcile lab results with real-user field measurements.
Compare the lab and field data in the Google PageSpeed Insights report for https://example.com. Put First contentful paint (FCP) next to First contentful paint (Lab test result), Largest contentful paint (LCP) next to Largest contentful paint (Lab test result), and Cumulative layout shift (CLS) next to Cumulative layout shift (Lab test result), broken down by Device type. Explain where lab and field diverge, what that implies about real-user experience, and which signal to trust for each metric.
Analysis
Biggest-Opportunity Analysis
Find the single fix that would lift your Performance score the most.
Analyze the Google PageSpeed Insights results for https://example.com to find the biggest scoring opportunities. Across Performance score, Accessibility score, Best practices score, and SEO score by Device type, identify the lowest-scoring category and the Core Web Vitals metric (Largest contentful paint (LCP), Interaction to next paint (INP), or Cumulative layout shift (CLS)) that is furthest from "Good". Explain what is dragging each down and estimate which single fix would lift the Performance score the most.
Analysis
TTFB & Server Response Analysis
Diagnose how server response time affects downstream metrics.
Using the Google PageSpeed Insights data for https://example.com, analyze Time to first byte (TTFB) by Device type with its TTFB assessment, and correlate it with First contentful paint (FCP) and Largest contentful paint (LCP). Explain how much of the loading experience is bounded by server response time versus front-end rendering, and recommend where to focus investigation.
Audit
Full Page-Speed Health Check
Run a comprehensive health check across all scores and vitals.
Perform a Google PageSpeed Insights health check for https://example.com. Evaluate: 1) Performance score, Accessibility score, Best practices score, and SEO score by Device type. 2) First contentful paint (FCP), Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), and Time to first byte (TTFB) with their assessments. 3) Whether the page passes the Core Web Vitals assessment. Give a health score from 1-10 and list the top 5 improvements.
Audit
SEO Score Audit
Audit the technical SEO signals captured by the SEO score.
Audit the SEO score from the Google PageSpeed Insights report for https://example.com, broken down by Device type. Identify why the SEO score is below 100, note how Largest contentful paint (LCP) and Cumulative layout shift (CLS) may influence search experience, and recommend specific technical SEO fixes for the Web page Url.
Audit
Accessibility Score Audit
Review accessibility gaps flagged by the accessibility score.
Audit the Accessibility score in the Google PageSpeed Insights report for https://example.com, broken down by Device type. Explain the likely accessibility issues dragging the score down (contrast, labels, alt text, focus order), compare desktop versus mobile, and recommend a prioritized remediation plan for the Web page Url.
Audit
Core Web Vitals Pass/Fail Audit
Confirm whether the page passes Core Web Vitals and why.
Audit the Core Web Vitals status in the Google PageSpeed Insights field data for https://example.com. For each Device type, report the Largest contentful paint (LCP) assessment, Interaction to next paint (INP) assessment, and Cumulative layout shift (CLS) assessment, and state whether the Web page Url passes or fails. For every failing metric, list the exact threshold missed and recommend the single highest-impact fix.
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