Geo Content

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

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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:

| Signal | Points | How to Score |

|---|---|---|

| First-person accounts ("I tested...", "We implemented...") | 5 | 5 if present and specific, 3 if generic, 0 if absent |

| Original research or data not available elsewhere | 5 | 5 if original data, 3 if references original work, 0 if none |

| Case studies with specific results | 4 | 4 if detailed with numbers, 2 if general, 0 if none |

| Screenshots, photos, or evidence of direct use | 3 | 3 if authentic evidence, 1 if stock/generic, 0 if none |

| Specific examples from personal experience | 4 | 4 if specific and unique, 2 if somewhat specific, 0 if generic |

| Demonstrations of process (not just outcome) | 4 | 4 if step-by-step from experience, 2 if partial, 0 if none |

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:

| Signal | Points | How to Score |

|---|---|---|

| Author credentials visible (bio, degrees, certifications) | 5 | 5 if full credentials, 3 if basic bio, 0 if no author |

| Technical depth appropriate to topic | 5 | 5 if thorough technical treatment, 3 if adequate, 0 if superficial |

| Methodology explanation (how conclusions were reached) | 4 | 4 if clear methodology, 2 if some explanation, 0 if none |

| Data-backed claims (statistics, research citations) | 4 | 4 if well-sourced, 2 if some data, 0 if unsupported claims |

| Industry-specific terminology used correctly | 3 | 3 if accurate specialized language, 1 if basic, 0 if errors |

| Author page with detailed professional background | 4 | 4 if dedicated author page, 2 if brief bio, 0 if none |

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:

| Signal | Points | How to Score |

|---|---|---|

| Inbound citations from authoritative sources | 5 | 5 if cited by major sources, 3 if some citations, 0 if none |

| Author quoted or cited in press/media | 4 | 4 if media mentions, 2 if industry mentions, 0 if none |

| Industry awards or recognition mentioned | 3 | 3 if relevant awards, 1 if tangential, 0 if none |

| Speaker credentials (conferences, events) | 3 | 3 if listed, 0 if none |

| Published in peer-reviewed or respected outlets | 4 | 4 if tier-1 publications, 2 if industry outlets, 0 if none |

| Comprehensive topic coverage (topical authority) | 3 | 3 if site covers topic thoroughly, 1 if some coverage, 0 if isolated |

| Brand mentioned on Wikipedia or authoritative references | 3 | 3 if Wikipedia, 2 if other encyclopedic refs, 0 if none |

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:

| Signal | Points | How to Score |

|---|---|---|

| Contact information visible (address, phone, email) | 4 | 4 if full contact info, 2 if email only, 0 if none |

| Privacy policy present and linked | 2 | 2 if present, 0 if absent |

| Terms of service present | 1 | 1 if present, 0 if absent |

| HTTPS with valid certificate | 2 | 2 if valid HTTPS, 0 if not |

| Editorial standards or corrections policy | 3 | 3 if documented, 1 if implicit, 0 if none |

| Transparent about business model and conflicts | 3 | 3 if clear disclosures, 1 if some, 0 if none |

| Reviews and testimonials from real customers | 3 | 3 if verified reviews, 1 if testimonials, 0 if none |

| Accurate claims (no misinformation detected) | 4 | 4 if all claims accurate, 2 if mostly accurate, 0 if errors found |

| Clear affiliate/sponsorship disclosures | 3 | 3 if properly disclosed, 0 if undisclosed or absent |

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

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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.

| Page Type | Minimum Words | Ideal Range | Notes |

|---|---|---|---|

| Homepage | 500 | 500-1,500 | Clear value proposition, not a wall of text |

| Blog post | 1,500 | 1,500-3,000 | Thorough but focused |

| Pillar content / Ultimate guide | 2,000 | 2,500-5,000 | Comprehensive topic coverage |

| Product page | 300 | 500-1,500 | Descriptions, specs, use cases |

| Service page | 500 | 800-2,000 | What, how, why, for whom |

| About page | 300 | 500-1,000 | Company/person story and credentials |

| FAQ page | 500 | 1,000-2,500 | Thorough answers, not one-liners |

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
• Support with evidence — remaining sentences provide data, examples, or context
• Quotable standalone — each paragraph should make sense if extracted in isolation

Heading Structure

• One H1 per page — the primary topic/title
• H2 for major sections — should represent distinct subtopics
• H3 for subsections — nested under relevant H2
• No skipped levels — do not go from H1 to H3 without an H2
• Descriptive headings — "How to Optimize for AI Search" not "Section 2"
• Question-based headings where appropriate — these map directly to AI queries

Internal Linking

• Every content page should link to 3-5 related pages on the same site
• Links should use descriptive anchor text (not "click here")
• Create a topic cluster structure: pillar page linked to/from all related subtopic pages
• Orphan pages (no internal links pointing to them) are rarely cited by AI

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AI Content Assessment

AI-Generated Content Policy

AI-generated content is acceptable per Google's guidance (March 2024 clarification) as long as it demonstrates genuine E-E-A-T signals and has human oversight. The concern is not HOW content is created but WHETHER it provides value.

Signs of Low-Quality AI Content (flag these)

| Signal | Description |

|---|---|

| Generic phrasing | "In today's fast-paced world...", "It's important to note that...", "At the end of the day..." |

| No original insight | Content that only rephrases widely available information |

| Lack of first-hand experience | No personal anecdotes, case studies, or specific examples |

| Perfect but empty structure | Well-formatted headings with shallow content beneath them |

| No specific examples | Uses abstract explanations without concrete instances |

| Repetitive conclusions | Each section ends with a variation of the same point |

| Hedging overload | "Generally speaking", "In most cases", "It depends on various factors" without specifying which factors |

| Missing human voice | No opinions, preferences, or professional judgment expressed |

| Filler content | Paragraphs that could be deleted without losing information |

| No data or sources | Claims presented as facts without attribution or evidence |

High-Quality Content Signals (regardless of production method)

| Signal | Description |

|---|---|

| Original data | Surveys, experiments, benchmarks, proprietary analysis |

| Specific examples | Named products, companies, dates, numbers |

| Contrarian or nuanced views | Disagreement with conventional wisdom, backed by reasoning |

| First-person experience | "When I tested this..." or "Our team found..." |

| Updated information | References to recent events, current data |

| Expert opinion | Clear professional judgment, not just facts |

| Practical recommendations | Specific, actionable advice, not vague guidance |

| Trade-offs acknowledged | "This approach works well for X but not for Y because..." |

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Content Freshness Assessment

Publication Dates

• Check for visible datePublished and dateModified in both the content and structured data
• Content without dates is treated as less trustworthy by AI platforms
• Dates should be specific (January 15, 2026) not vague ("recently")

Freshness Scoring

| Criterion | Score |

|---|---|

| Updated within 3 months | Excellent — current and relevant |

| Updated within 6 months | Good — still reasonably current |

| Updated within 12 months | Acceptable — may need refresh |

| Updated 12-24 months ago | Warning — review for accuracy |

| No date or 24+ months old | Critical — AI platforms may deprioritize |

Evergreen Indicators

Some content remains relevant regardless of age. Flag content as evergreen if:

• It covers fundamental concepts that do not change (physics, basic math, legal definitions)
• It is clearly labeled as a reference/guide for lasting concepts
• It does not contain time-dependent claims ("the latest", "currently", "in 2024")

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Topical Authority Assessment

What It Is

Topical authority measures whether a site comprehensively covers a topic rather than touching on it superficially. AI platforms prefer citing sites that are recognized authorities on their topics.

How to Assess

1. Content breadth: Does the site have multiple pages covering different aspects of its core topic?

2. Content depth: Do individual pages go deep into subtopics?

3. Topic clustering: Are pages organized into logical groups with internal linking?

4. Content gaps: Are there obvious subtopics that the site should cover but does not?

5. Competitor comparison: Do competitors cover subtopics that this site misses?

Scoring

| Level | Description | Score Impact |

|---|---|---|

| Authority | 20+ pages covering topic comprehensively, strong clustering | +10 bonus |

| Developing | 10-20 pages with some clustering | +5 bonus |

| Emerging | 5-10 pages on topic, limited clustering | +0 |

| Thin | < 5 pages, no clustering | -5 penalty |

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Overall Scoring (0-100)

Score Composition

| 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 |

Score Interpretation

• 85-100: Exceptional — strong AI citation candidate across platforms
• 70-84: Good — solid foundation, specific improvements will increase citability
• 55-69: Average — multiple E-E-A-T gaps reducing AI visibility
• 40-54: Below Average — significant content quality and trust issues
• 0-39: Poor — fundamental content strategy overhaul needed

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Output Format

Generate GEO-CONTENT-ANALYSIS.md with:

# GEO Content Quality & E-E-A-T Analysis — [Domain]
Date: [Date]

E-E-A-T Breakdown

| Dimension | Score | Key Finding |

|---|---|---|

| Experience | XX/25 | [One-line summary] |

| Expertise | XX/25 | [One-line summary] |

| Authoritativeness | XX/25 | [One-line summary] |

| Trustworthiness | XX/25 | [One-line summary] |

Pages Analyzed

| Page | Word Count | Readability | Heading Structure | Citability Rating |

|---|---|---|---|---|

| [URL] | [Count] | [Score] | [Pass/Warn/Fail] | [High/Medium/Low] |

E-E-A-T Detailed Findings

Experience

[Specific passages and pages with strong/weak experience signals]

Expertise

[Author credentials found, technical depth assessment, specific gaps]

Authoritativeness

[External validation found, topical authority assessment, gaps]

Trustworthiness

[Trust signals present/missing, accuracy concerns if any]

Content Quality Issues

[Specific passages flagged with reasons and rewrite suggestions]

AI Content Concerns

[Any low-quality AI content patterns detected, with specific examples]

Freshness Assessment

| Page | Published | Last Updated | Status |

|---|---|---|---|

| [URL] | [Date] | [Date] | [Current/Stale/No Date] |

Citability Assessment

Most Citable Passages

[Top 5 passages that AI platforms are most likely to cite, with reasons]

Least Citable Pages

[Pages with lowest citability, with specific improvement recommendations]

Improvement Recommendations

Quick Wins

[Specific content changes that can be made immediately]

Content Gaps

[Topics the site should cover to strengthen topical authority]

Author/E-E-A-T Improvements

[Specific steps to strengthen E-E-A-T signals]