Paste a URL. Get the fixes blocking AI visibility.
Enter one public URL, run the audit, and review the crawl, metadata, schema, and rendering fixes blocking visibility.
Paste the target URL and review the fix list below.
Best for product pages, comparison pages, docs, glossaries, or resource hubs you expect AI systems to cite.
Use the URL that should win for the target query, not just the homepage or the broadest landing page.
Fix crawlability, metadata, schema, and rendering blockers before assuming the issue is only content quality.
The point is not the number alone. The score tells you whether to fix mechanics, sharpen answer structure, or widen the supporting content surface.
Quick Scan validates presence, AEO Audit diagnoses the page, and Citation Gap prioritizes the proof or content still missing.
Use the exact product, comparison, docs, or glossary page that should be getting cited.
The tool resolves the request and prepares a runnable audit against the public URL.
Discovery, structure, content, technical, and rendering checks execute against the page.
Use blockers and fast wins to route the next work item to engineering, SEO, or content.
What is Answer Engine Optimization (AEO)?
Answer Engine Optimization is the practice of structuring your web content so AI models — ChatGPT, Perplexity, Gemini, Copilot, and others — can discover, understand, and cite it in their generated responses. While traditional SEO focuses on ranking in search engine result pages, AEO focuses on being the source that AI models pull information from.
AI models select sources based on crawlability, structured data, content clarity, authority signals, and technical rendering. A page that ranks well in Google may still be invisible to AI answer engines if it relies on client-side JavaScript rendering or lacks structured markup.
What the audit checks
The AEO Audit runs 17 checks across five categories:
Discovery — Can AI crawlers find your page? Checks robots.txt permissions, llms.txt presence, sitemap.xml inclusion, and canonical URL configuration.
Structure — Is your content machine-readable? Checks Schema.org/JSON-LD markup, heading hierarchy (H1-H6 nesting), and internal link density.
Content — Is your content formatted for AI extraction? Checks for BLUF (Bottom Line Up Front) patterns, FAQ sections, definition lists, and concise paragraph length.
Technical — Are there technical barriers? Checks page load time, HTTPS, mobile viewport, meta robots tags, and canonical consistency.
Rendering — Can AI crawlers see your content? Detects excessive client-side rendering, JavaScript dependency, and content that only appears after hydration.
Priority fixes for most sites
Based on thousands of audits, the three highest-impact fixes are:
1. Add an llms.txt file— This is the equivalent of robots.txt for AI crawlers. It tells AI models what your site is about and which pages are most important. Most sites don't have one yet, making this a fast competitive advantage.
2. Add Schema.org JSON-LD — Structured data helps AI models understand entities, relationships, and facts on your page. Organization, Article, FAQ, HowTo, and Product schemas have the biggest impact.
3. Use BLUF content structure — Put the answer first, then the explanation. AI models strongly prefer content that leads with a clear, extractable statement rather than burying the answer after context.