Overall AI readiness score
A combined result across all audit signals.
Overall AI readiness score
A combined result across all audit signals.
Overall AI readiness assessment
Paragon (paragonagency.com) received an AI-readiness score of 59/100 in an automated technical audit. llms.txt was accessible, llms-full.txt was not found, and ai.txt was not found. The robots.txt analysis found 0 explicitly allowed and 0 blocked AI crawlers, with 3 declared sitemaps. Homepage markup completeness was 0%; no Schema.org types were detected and 0 OpenGraph tags were detected. Results reflect the public site response observed on 2026-09-18T01:33:58.872Z.
llms.txt is accessible and contains 1,624 tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 3. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 31/100, Accessibility 73/100, Best Practices 92/100, SEO 100/100, and experimental Agentic Browsing 35/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.
Performance
Accessibility
Best Practices
Technical SEO
Agentic Browsing
Mobile performance is 31/100, with the largest visible content block appearing in 19.1 s and the browser main thread blocked for 440 ms. Layout shift was 0.823. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.
Accessibility scored 73/100, Best Practices 92/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 35/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.
Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.
Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.
Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.
First content
Main content
Layout stability
Blocking time
Visual speed
Machine-readable files, crawler policy, discovery, and homepage markup.
Full version was not found
ai.txt file was not found
3 sitemaps found
Schema.org markup was not found on the homepage
OpenGraph tags were not found on the homepage
Based on robots.txt analysis
Declared discovery routes for crawlers and agents.
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