Geo Content

GEO Content Quality & E-E-A-T Assessment

Purpose

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 (Your Money Your Life) topics. Content that scores high on E-E-A-T is dramatically more likely to be cited by AI platforms.

This skill evaluates content through two lenses:

1. E-E-A-T signals — does the content demonstrate real expertise and trust?
2. AI citability — is the content structured so AI platforms can extract and cite specific claims?

How to Use This Skill

1. Fetch the target page(s) — homepage, key blog posts, service/product pages
2. Evaluate E-E-A-T across the 4 dimensions (25% each)
3. Assess content quality metrics (structure, readability, depth)
4. Check for AI content quality signals
5. Evaluate topical authority across the site
6. Score and generate GEO-CONTENT-ANALYSIS.md

E-E-A-T Framework (100 points total)

Experience — 25 points

First-hand knowledge and direct involvement with the topic. AI platforms increasingly distinguish between content that reports on a topic and content from someone who has DONE it.

Signals to evaluate:

What to flag as weak Experience:

• Content that only summarizes what other sources say without adding new perspective
• Generic advice that could apply to any situation ("It depends on your needs")
• No mention of actual usage, testing, or direct involvement
• Hedging language that suggests lack of direct knowledge ("reportedly", "supposedly", "some say")

Expertise — 25 points

Demonstrated knowledge depth and professional competence in the subject matter.

Signals to evaluate:

What to flag as weak Expertise:

• Claims without supporting evidence or sources
• Surface-level coverage of complex topics
• Misuse of technical terminology
• No visible author or author without relevant credentials
• Content that is broad and generic rather than deep and specific

Authoritativeness — 25 points

Recognition by others as a credible source on the topic.

Signals to evaluate:

What to flag as weak Authoritativeness:

• Single-topic site with no depth of coverage
• No external validation of expertise claims
• No backlinks from authoritative sources
• Claims of authority without evidence (self-proclaimed "expert")

Trustworthiness — 25 points

Signals that the content and its publisher are reliable and transparent.

Signals to evaluate:

What to flag as weak Trustworthiness:

• No contact information or physical address
• Missing privacy policy or terms
• Undisclosed affiliate links or sponsored content
• Claims that are verifiably false or misleading
• No way to contact the publisher for corrections

Content Quality Metrics

Word Count Benchmarks

These are floors, not targets. More words does not mean better content. The benchmark is the minimum length to adequately cover a topic for AI citability.

Readability Assessment

• Target Flesch Reading Ease: 60-70 (8th-9th grade level)
• This is NOT a direct ranking factor but affects citability — AI platforms prefer content that is clear and unambiguous
• Overly academic writing (score < 30) reduces citability for general queries
• Overly simple writing (score > 80) may lack the depth needed for expertise signals

How to estimate without a tool:

• Average sentence length: 15-20 words is ideal
• Average paragraph length: 2-4 sentences
• Presence of jargon: should be defined when first used
• Passive voice: < 15% of sentences

Paragraph Structure for AI Parsing

AI platforms extract content at the paragraph level. Each paragraph should be a self-contained unit of meaning.

Optimal paragraph structure:

• 2-4 sentences per paragraph (1-sentence paragraphs are weak; 5+ sentences are hard to extract)
• One idea per paragraph — do not mix topics within a paragraph
• Lead with the key claim — first sentence should contain the main point