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), from Google's Search Quality Rater Guidelines. E-E-A-T began as a YMYL (Your Money Your Life) lens but is now widely applied by raters well beyond YMYL topics; treat strong E-E-A-T as table stakes for any competitive query. Content that scores high on E-E-A-T is materially more likely to be cited by AI platforms. (See [docs/SOURCES.md](../../docs/SOURCES.md) for the guidelines reference and dates.)

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 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: Provenance (THL): tag the score [scan] (data fetched this run), [partial-scan], [heuristic] (judgement, no data), or [unmeasured] — and emit — instead of a number when [unmeasured] or pure [heuristic]. A number with weak provenance still reads as hard data. See [the GEO Method](../../docs/THL-GEO-METHOD.md).

Generate GEO-CONTENT-ANALYSIS.md with:

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

## Content Score: XX/100

## 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] |

## Topical Authority Modifier: [+10 to -5]

## 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]

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: techhorizonlabs
• Source: techhorizonlabs/thl-open
• License: MIT
• Homepage: https://techhorizonlabs.com

Install and usage instructions live in the source repository linked above.