The TrustScore™ is not another SEO checklist. It is a visibility protocol for a world where AI agents determine relevance, credibility is machine-inferred, and trust is engineered into content, not appended after the fact. This framework gives strategists, content owners, and technical teams a way to evaluate the structural integrity of their outputs, clarity, coherence, attribution, and semantic precision, all through the lens of how machines perceive, summarize, and reuse what we publish.

What content elements do we provide that influence how AI systems parse, resolve, and prioritize our work?

This section captures the essential technical and semantic inputs that shape the foundation of machine visibility. It includes everything from author identity resolution and schema use to canonical URLs and the presence of structured claims.

When content lacks canonical URLs, disambiguated author identities, or proper schema declaration, it fails silently. Not to human readers, but to the machines that now arbitrate knowledge flow. The Inputs audit evaluates these foundations. Is the author linked to a persistent ID (ORCID, Wikidata, LinkedIn)? Is the content marked up with schema.org types that reflect its true purpose, Report, ClaimReview, ScholarlyArticle, not just Article? Are URLs canonicalized? Are claims fingerprinted? These are no longer edge cases. They are core requirements for being seen, cited, and preserved in AI-driven environments.

What signals do machines generate in response to our content, and how do those signals reflect our trust performance?

Here we assess the content’s observable performance: TrustScore™ ratings, summarization resilience, inference alignment, and presence within AI citation and knowledge graph systems.

What we publish is no longer consumed only by humans. It is parsed, recomposed, and reweighted by AI systems that are trained to filter for trust. Outputs give us a mirror, showing how machines interpret our credibility. Here, we measure the TrustScore™ at the page level and at the entity level. We test for epistemic risks: are attributions preserved in summaries? Are claims distorted in paraphrase? We examine AI visibility directly,  do LLMs cite the page when asked about relevant topics? Are we present in knowledge panels, structured summaries, or agent-based responses? This is not theoretical. These signals shape whether our work becomes part of the world’s next answer.

Where are the friction points? What needs to be fixed, improved, or institutionalized to elevate our trust position?

This section translates audit findings into clear, prioritized actions. It differentiates urgent structural gaps from strategic enhancements and forward-looking trust opportunities.

Fixes must be prioritized. A missing author field and broken citation links are not the same as an opportunity to enrich schema or link to ORCID. This section breaks out red-level urgencies from yellow-level enhancements and green-field trust opportunities. The most powerful content teams today work like trust architects: writers, metadata leads, and strategy heads operating with shared language and aligned incentives. The goal is not just to patch what is broken, but to shift upstream, so that trust is baked in by default, not retrofitted on delivery.

How often do we run this audit, and who is responsible for ensuring trust is maintained over time?

Cadence defines the operational rhythm. It sets expectations for quarterly reviews, pre-launch audits, and live dashboard monitoring, while also defining team roles and ownership for each layer of trust infrastructure.

No audit process matters if it is not sustained. TrustScore™ should be part of your organization’s operating rhythm. That means quarterly audits for evergreen content, pre-launch assessments for flagship reports, and monthly reviews of high-visibility assets with live dashboards. Just as product teams have QA and security reviews, knowledge teams need trust reviews. The cadence also defines ownership: who updates metadata, who tests summarization fidelity, who validates schema? Epistemic responsibility is not an individual burden. It is a cross-functional commitment to futureproof credibility.