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Methodology & sources

The provenance behind every audit.

Every audit ends with a link to this page. It shows what we checked, where each rule comes from, and how confident we are in it. Forward this when you want to send the framework — not a specific run — to a client or developer.

Methodology last reviewed: 2026-05-16.

What the audit checks and why.

Three rollups, ten check categories. Each finding maps to a source and a confidence level you'll see on the right of every report.

01

Can AI find your site?

We check robots.txt, sitemap discovery, and whether your CDN/WAF is letting documented AI crawlers reach your pages.

02

Can AI understand your content?

We check headings and page structure, structured data, and whether the main content is reachable without running JavaScript.

03

Will AI cite you as a source?

We check trust signals (HTTPS, author markup, outbound citations, freshness) and content shape that nudge an AI assistant toward picking you when it answers.

Where these recommendations come from.

We don't make up rules. Every check is grounded in one of four source types. Findings link back to the exact doc they came from.

Official documentation from AI companies

Definitive

Crawler names, user agents, and opt-out mechanisms come straight from each provider's own documentation.

Emerging standards

Emerging

Worth knowing about, but not yet officially adopted. We surface these as low-effort possible-future wins, not as critical fixes.

Research and industry observation

Definitive

Content-structure recommendations and trust-signal heuristics lean on published research and reporting from infrastructure providers, not provider docs.

How confident we are in each finding.

Every finding carries one of three confidence levels so you can tell at a glance which recommendations are based on documented standards and which are based on observed behaviour or emerging practice.

Definitive
Based on standards or official documentation.
Examples: robots.txt blocks GPTBot; no JSON-LD Article schema present.
Suggestive
Based on observed behaviour, not conclusive.
Example: CDN appears to block GPTBot — our audit IP received 403, but real GPTBot uses published IP ranges that may be treated differently.
Emerging best practice
Based on early signals or recent research, not established standards.
Example: llms.txt is recommended but not yet required by major AI providers.

About this audit run.

We record exact provenance with every report so anyone receiving it can re-run, verify, or just trust where the numbers came from.

Reproducibility metadata

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