eXAI Score
Last updated: February 3, 2026
A score is useful only if it explains what to do next. eXAI Score is a readable layer: evidence → priorities → verification.
What it should tell you
- Which pages carry the core meaning (entity + category definition) and need standardization.
- Which missing sections cause semantic gaps (theme map incompleteness).
- Which fixes are semantic vs technical vs trust, so you don’t “optimize the wrong thing.”
The explanation chain (a practical model)
1) Evidence
What the crawler + modules observed (entities, coverage, intent signals).
2) Priority
What to change first, based on leverage: entity clarity and intent alignment usually outrank markup.
3) Verification
How you confirm the change reduced ambiguity (and improved stability).
How to raise the Semantic pillar (module-aligned checklist)
- Entity clarity: define brand + product; add disambiguation; connect relationships.
- Topic coverage: publish a theme map; cover subtopics and edge cases.
- Intent alignment: split pages by intent (definition vs comparison vs how-to).
- Semantic gaps: add missing answers that engines expect for your category.
- Schema markup: add structured data after the text is clear.
Why a single score is not a strategy
Scores summarize. Strategies reduce uncertainty: clarify entities, match intent, fill theme-map gaps, and back claims with verification.
Related pages
Continue through the AI Visibility ontology with these related nodes.
Use the score like a roadmap
Pick a pillar to improve, ship changes, and verify with re-runs.