The method rests on three documents kept in the open: a product specification that defines behavior and scoring, a knowledge base that holds every rule with its class, detection logic, reason template, fix and verbatim citation, and a registry of every source the scanner may cite. Code transcribes those documents; it never adds SEO knowledge of its own. An automated check confirms that every stored quote is an exact substring of its live source page before a ruleset ships.
- 01How the score is calculatedWhy the score measures distance from the best documented setup, evidence classes with fixed weights, opportunities, indexing gates, exact rational arithmetic and a worked example.Read
- 02Evidence classes and citationsHow a documented must, a recommendation and a web standard become different classes, and why every finding carries a verbatim quote.Read
- 03Deterministic by constructionWhy the same snapshot always produces the same report: one acquisition, a frozen snapshot, and evaluation as a pure function.Read
- 04The rule catalogEvery rule the scanner evaluates, grouped by category, with its class, weight, gate and the primary source it rests on.Read
- 05What the scanner never scoresThe myth guard: claims that circulate widely and are contradicted, dismissed or unsupported by the primary record.Read
- 06The manual review checklistDocumented requirements that cannot be decided from outside a site, with the reason the scanner cannot judge them.Read
- 07AI crawlers and generative searchHow the scanner reports access for search and AI crawlers without scoring it, using each operator's own documentation.Read
- 08The advisory AI content reviewAn optional, clearly labeled model review of titles, descriptions and answers that never touches the score, and the guidelines that bound it.Read
- 09Source registryEvery primary source the scanner may cite, with its last-updated date and the date its wording was last verified.Read