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The Technical Audit checks your website for technical problems that stop AI engines from finding and recommending your content. It covers both traditional SEO basics and AI-specific readiness.
How to run an audit
Go to Audit in the Optimize section
Enter a page URL for a single page audit, or your domain for a site-wide audit
Click Run Audit
Results appear in minutes
What it checks
6 HTML categories (traditional SEO health)
Meta Title: Is it between 50–60 characters? Does it include your target keyword?
Meta Description: Is it between 150–160 characters? Does it describe the page clearly?
Schema Markup: Do you have JSON-LD structured data? Which types?
Images: Do your images have alt text?
Links: Do you have internal links (3+)? External links? Any broken links?
Overall Score: Average of all 5 categories, 0–100
7-category LLM Readiness Score (AI-specific)
This is the important one. Shown as a radar chart with weighted categories:
Structured Data (25%): JSON-LD schema present and properly configured
Content Clarity (20%): Clear H1, multiple H2s, well-structured paragraphs
Authority Signals (15%): Author info, canonical URL, datePublished
Citation-Friendly Format (15%): Lists, tables, FAQ sections that AI can easily extract
Technical Accessibility (10%): No noindex tags blocking AI, viewport set, language declared
Internal Linking (10%): Enough internal links pointing to and from the page
Freshness (5%): dateModified and datePublished present in schema
Framework detection
GRRO automatically detects if your site runs on Next.js, WordPress, Gatsby, Nuxt, or static HTML.
Fix recommendations include framework-specific instructions. For example, if you're on Next.js, it'll tell you to set meta tags in generateMetadata() in your layout.tsx.
Site-wide audits
For a full site audit, GRRO crawls your sitemap and audits every page. Results show in a sortable table so you can prioritize the worst-scoring pages first.
Exporting results
Export your audit in 5 formats:
Copy Prompt: Copies a structured prompt to paste into AI tools for fix suggestions
Markdown: Downloadable
.mdfilePDF Report: Branded PDF with scores, tables, and color-coded issues
Slide Deck (PPTX): Presentation-ready slides for sharing with your team
Spreadsheet (CSV): One row per issue for tracking fixes
Tips
Fix LLM Readiness issues first — these directly affect whether AI can recommend you.
Re-audits run automatically every Sunday. Check back weekly to track improvement.
If your overall LLM Readiness Score is below 50, focus on Structured Data and Content Clarity first — they carry the most weight.