Single Page Audit

Single Page Audit ("Single URL · 50 checks") is the zoomed-in counterpart to Domain-Wide Audit. Instead of scoring every page on your site at once, it runs a 50-item LLM citation-readiness check, spanning content quality, structure, trust signals, and page performance, against one URL at a time, plus a PageSpeed Insights pass.

What it's for

Use it once Domain-Wide Audit has told you which URL is underperforming, and you need to know exactly why. Rather than a single score and letter grade, it breaks the audit down section-by-section and check-by-check against that one page's actual structure, so you can make precise, targeted fixes instead of guessing.

Running a check

• URL field + Check Page: enter the page to audit and run the 50-item check.
• Download PDF: export the full result as a shareable report.

Score summary

• Score / Grade: an overall score out of 100, mapped to a letter grade.
• Passed / Failed / Warnings / Manual: how the 50 checks broke down. Manual checks are ones the tool can't fully verify automatically and flags for you to confirm by hand.

Score by section

A bar chart showing the score for each of the audit's sections side by side, so you can immediately spot which sections are dragging the overall score down versus which are already solid.

Section checklist

Below the chart, each section is listed with its own pass/fail/warning counts and score percentage. Use the All / Passed / Failed / Warnings / Manual filter to narrow the list, and expand a section (▶) to see its individual checks.

• Content clarity: how directly the page states its point, plain language over dense jargon. Why it matters: a model summarizing or quoting your page is more likely to lift a clear, self-contained sentence than untangle a convoluted one.
• Structure & scannability: headings, lists, and section breaks that make the page easy to parse. Why it matters: models extract specific chunks of a page rather than reading it end to end; poor structure makes the right chunk harder to isolate even when the content itself is good.
• Entity & fact signals: concrete data points, named entities, dates, and attributions. Why it matters: specific, checkable facts are what make a page useful as a citation instead of just a mention.
• Trust & authority signals: author information, credentials, and licensing. Why it matters: this is part of how an AI system judges whether a source is credible enough to cite, not just relevant.
• Schema signals: structured data markup on the page. Why it matters: schema gives machines an explicit description of the page instead of forcing them to infer it, reducing misinterpretation.
• Semantic answer coverage: whether the page's content actually answers the kinds of questions it's likely to be matched against. Why it matters: a page can rank on topic relevance and still fail to get cited if it never states a direct answer to the question being asked.