What is Author-authority audit?

An author-authority audit is the systematic review of a site’s credibility layer for AI search — checking, page by page, whether the bylines resolve to real author entities, whether the claimed expertise is externally corroborated, whether the content carries first-hand experience, and whether the body has the expertise density its byline promises — run before adding more content on top of an unaccountable foundation.

Its stages are byline resolution (does each key page’s byline resolve to Person schema, an author page, and a credential graph, or is it a bare name string or an anonymous ‘by Marketing Team’ floor to fix first), credential corroboration (do the author’s external profiles exist, cohere, and actually corroborate the expertise), experience inventory (scoring each page for original media, first-party data, and process language, and flagging pure-synthesis pages), a density check (reading the body as a practitioner would — specific and complete, or hedged and generic), and computing a credibility gap against the sources actually cited on the target queries. The audit is the detection layer beneath a credibility program: it identifies whether the thinnest signal is the author entity, the experience, or the density, so the program fixes the binding constraint rather than adding volume to an unaccountable base.