القائمة
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
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| name | geo-content |
| description | Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure |
| version | 1.0.0 |
| author | geo-seo-claude |
| tags | ["geo","content-quality","eeat","citability","ai-content","topical-authority"] |
AI search platforms do not just find content — they evaluate whether content deserves to be cited. The primary framework for this evaluation is E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), which per Google's December 2025 Quality Rater Guidelines update now applies to ALL competitive queries, not just YMYL topics. Content that scores high on E-E-A-T is dramatically more likely to be cited by AI platforms.
Two lenses:
signals.mdscoring.mdsignals.md)scoring.md)GEO-CONTENT-ANALYSIS.md using the template in templates.mdsignals.md — per-signal scoring rubrics for all 4 E-E-A-T dimensions, plus AI content quality signals (low/high)scoring.md — word count benchmarks, readability, paragraph/heading/linking rules, freshness scoring, topical authority modifiertemplates.md — GEO-CONTENT-ANALYSIS.md output template| Component | Weight | Max points |
|---|---|---|
| Experience | 25% | 25 |
| Expertise | 25% | 25 |
| Authoritativeness | 25% | 25 |
| Trustworthiness | 25% | 25 |
| Subtotal | 100 | |
| Topical Authority Modifier | +10 to -5 | |
| Final Score | Capped at 100 |
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