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The E-E-A-T score for AI assistants

ContentAuthority Score

Composite score of authority signals in a piece of content - byline credentials, source quality, citation density and factual anchoring.

Paste content

153 words

Authority score
A

93

Byline credentials

×25%100

Who wrote it, and does the author carry expertise?

  • Named author
  • Credentials (PhD, MD, etc)
  • Author bio / expertise
  • Peer / editor review

Source quality

×30%75

Which external authorities back the claims?

  • External URLs
  • 'According to' sourcing
  • Named institutions cited
  • Studies / reports referenced

Citation density

×20%100

How often are claims backed up?

  • At least 3 citations
  • At least 5 citations
  • At least 1 citation per 500 words
  • Mix of citation forms

Factual anchoring

×25%100

Are claims grounded in specific numbers?

  • Fact density ≥ 3 per 100 words
  • Fact density ≥ 5 per 100 words
  • At least 3 percentages
  • Specific year references
  • Numerical ranges or dollar values

How it works

Paste your content. The scorer runs four authority pillars in parallel: byline credentials, source quality, citation density and factual anchoring. Each pillar has 4-5 specific checks; each check is pass/fail. The final score is weighted 25/30/20/25 across the four pillars.

The four pillars

  • Byline credentials (25%) - named author, credentials, bio, peer review.
  • Source quality (30%) - external URLs, named institutions, studies, "according to" patterns.
  • Citation density (20%) - citations per 500 words, mix of citation forms.
  • Factual anchoring (25%) - fact density, percentages, specific years, numerical ranges.

Pair with

For the full view, run the Trust Signal Analyzer (signal-level) and the Citation Probability Calculator (outcome-level). Authority is also wrapped in structured data - make sure your Article schema declares author and datePublished. Full scoring logic: how assistants choose citations.

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