SEEN/.blackbox/skills/seo/references/eeat-framework.md

E-E-A-T Evaluation Framework

Use this rubric to evaluate content quality for competitive queries.

Dimensions

Score each dimension from 0 to 5:

Dimension	What to Check
Experience	First-hand evidence, practical examples, real usage context
Expertise	Subject competence, technical accuracy, depth, specialist language used correctly
Authoritativeness	Reputation signals, citations, recognized brand/person entities
Trustworthiness	Accuracy, transparency, policy clarity, editorial rigor, safety disclosures

Query Stakes Classification

Classify intent before scoring:

• YMYL-high: finance, health, legal, safety
• Commercial-high: high-ticket buying decisions
• Informational-competitive: dense SERP competition with strong entities
• Informational-low: low-risk, basic educational intent

Raise trust requirements for higher-stakes intents.

Evidence Checklist

Review per template:

1. Authorship clarity:
   • named author
   • credentials or role
   • updated timestamp
2. Source quality:
   • primary sources cited
   • external corroboration
   • quote/context integrity
3. Editorial quality:
   • original analysis (not paraphrased commodity text)
   • internal consistency across pages
   • clear claims with evidence
4. Trust assets:
   • about page and editorial policy
   • contact and business identity
   • privacy and terms links
5. User value:
   • intent match
   • completeness
   • actionable depth

Risk Flags

Flag as high risk when you find:

• anonymous or credential-free expert claims on high-stakes pages
• copied or near-duplicate boilerplate across key landing pages
• medical/financial/legal recommendations without sourcing
• exaggerated claims without verifiable proof

Scoring Output Format

Return:

1. Overall content quality score (0-100)
2. Per-dimension scores mapped from rubric
3. Top 3 trust risks
4. Fastest high-impact remediation actions

Remediation Patterns

• Add expert-reviewed blocks with named reviewers on high-stakes pages.
• Replace generic intros with first-hand evidence and data-backed claims.
• Add citation discipline: primary sources first, then secondary context.
• Standardize author bylines, update dates, and revision ownership.