What is an AEO page audit? An AEO page audit is a structured analysis of a web page’s technical and content characteristics that predict whether AI answer engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) can crawl, parse, and cite the content. Unlike traditional SEO audits that focus on keyword rankings and backlink profiles, an AEO audit evaluates whether your content is structured for extraction and citation in a zero-click environment.
We built one. It’s free. Try it here.
Why Does This Exist?
In our AEO measurement post, we walked through the full toolkit for tracking whether AI engines are citing your brand. But measurement assumes you’ve already done the structural work. Most businesses haven’t, and the first question is usually simpler: *Is my page even set up for AI to cite it?*
That’s what this tool answers. You paste a URL, we fetch the page (along with your robots.txt and llms.txt), and score it across six categories that map to the structural requirements AI engines look for when selecting sources.
What Are the Six Categories?
Heading Structure (15 points) checks whether your page has a clean heading hierarchy that AI engines can parse into distinct answer segments. This means a single H1, multiple H2 subheadings, question-format headings that match how people query AI assistants, and no skipped levels in the hierarchy. AI engines use heading structure the way a human uses a table of contents: to find the section that answers the question being asked.
Schema Markup (15 points) looks for JSON-LD structured data. Organization or LocalBusiness schema tells AI engines who you are as an entity. Article or BlogPosting schema helps them understand your content’s metadata (author, date, topic). FAQPage and BreadcrumbList schema are high-value citation triggers because they pre-structure your content in the exact format AI engines use to generate answers.
AI Crawler Access (20 points) is the most heavily weighted category because it’s the prerequisite for everything else. If AI crawlers can’t reach your content, nothing else matters. The audit checks your robots.txt for explicit rules about GPTBot, ClaudeBot, PerplexityBot, and Google-Extended. It also checks for the presence of an llms.txt file, which is an emerging standard that tells AI systems what your site is about and which pages are most important.
Content Quality (25 points) is the largest category because content is what actually gets cited. The audit evaluates word count (thin pages rarely get cited), definitive language patterns (“X is Y” statements that AI engines can extract as direct answers), the presence of structured elements like lists and tables, internal and external linking density, and freshness signals like published dates.
Meta & Technical (15 points) covers the metadata layer: meta descriptions, canonical URLs, OpenGraph tags, and semantic HTML elements. These signals help AI engines determine what a page is about before parsing the full content. A page with a clear meta description, proper canonical URL, and semantic HTML (<article>, <section>, <main>) is significantly easier for AI to classify and cite.
Citability Signals (10 points) measures the qualitative factors that push content from "indexed" to "cited": author attribution, specific statistics and data points, and FAQ-style question-answer patterns. AI engines preferentially cite content that has a named author, includes concrete numbers, and answers questions directly.
What Does the Score Mean?
The audit produces a score from 0 to 100 with a letter grade.
85–100 (A): The page is well-structured for AI citation. Focus on keeping content fresh and monitoring your citation share of voice.
70–84 (B): Good foundation with a few gaps. The audit will identify the specific fixes that would have the most impact.
55–69 (C): Some AEO basics are in place but there are clear structural problems. Usually missing schema markup, blocked crawlers, or thin content.
40–54 (D): Significant gaps. AI engines can probably access the page but will struggle to extract citable content from it.
Below 40 (F): This page is largely invisible to AI answer engines. Major structural work needed.
The score is not a guarantee of citation. A perfectly structured page on a topic nobody asks about will still not get cited. But a page that scores below 55 has structural problems that would prevent citation even if the content is exactly what an AI engine needs.
What This Tool Does Not Do
This is a structural audit, not a citation tracker. It tells you whether your page is *set up* to be cited. It does not tell you whether you *are* being cited. For that, you need the measurement framework we outlined in our AEO measurement guide, including tools like HubSpot’s AEO Grader, Microsoft Clarity’s AI Visibility dashboard, and Otterly.ai for ongoing prompt monitoring.
It also does not audit your entire site. It checks one page at a time. For a homepage, that’s usually enough to surface the biggest issues (robots.txt and llms.txt are site-wide). For content-heavy sites, you’ll want to audit your top-performing pages individually.
How to Use It
Go to arrowandbell.com/audit. Paste a URL. Click Audit. You’ll get a score, a breakdown of all six categories, and a prioritized list of quick wins at the bottom.
Start with your homepage. Then audit your most important content pages. If you’re running a blog, audit the posts that cover topics your customers ask AI assistants about. Those are the pages where AEO improvements translate directly into citation visibility.
Arrow & Bell builds AI-native websites and implements AEO strategies that get businesses cited by answer engines. If the audit surfaces issues you want help fixing, book a call.