Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".
Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".
user-invocable
true
argument-hint
[url]
license
MIT
metadata.author
AgriciDaniel
metadata.version
2.2.4
metadata.category
seo
Content Quality & E-E-A-T Analysis
Google's "Who / How / Why" Test (canonical heuristic)
Before scoring E-E-A-T sub-factors, every page audit should pass Google's
own three-question heuristic from the helpful-content guide:
Question
What to look for
Who created it?
Visible byline, author bio page, professional credentials. Required where readers expect it; non-negotiable for YMYL.
How was it created?
Process disclosure where readers would reasonably ask, especially for AI-assisted content. Original research / first-hand evidence / lived experience.
Why does it exist?
"To help people" rather than "to attract search clicks." Watch for niche entry without expertise, content churn for freshness signals, content written to a word-count target.
When all three answers are weak, the page is at risk under the core ranking
system's helpfulness signals (formerly the standalone Helpful Content System,
merged into core during the March 2024 update).
E-E-A-T Framework (updated Sept 2025 QRG)
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Read skills/seo/references/eeat-framework.md for full criteria.
Experience (first-hand signals)
Original research, case studies, before/after results
Personal anecdotes, process documentation
Unique data, proprietary insights
Photos/videos from direct experience
Expertise
Author credentials, certifications, bio
Professional background relevant to topic
Technical depth appropriate for audience
Accurate, well-sourced claims
Authoritativeness
External citations, backlinks from authoritative sources
Brand mentions, industry recognition
Published in recognized outlets
Cited by other experts
Trustworthiness
Contact information, physical address
Privacy policy, terms of service
Customer testimonials, reviews
Date stamps, transparent corrections
Secure site (HTTPS)
Content Metrics
Word Count Analysis
Compare against page type minimums:
Page Type
Minimum
Homepage
500
Service page
800
Blog post
1,500
Product page
300+ (400+ for complex products)
Location page
500-600
Important: These are topical coverage floors, not targets. Google has confirmed word count is NOT a direct ranking factor. The goal is comprehensive topical coverage; a 500-word page that thoroughly answers the query will outrank a 2,000-word page that doesn't. Use these as guidelines for adequate coverage depth, not rigid requirements.
Readability
Flesch Reading Ease: target 60-70 for general audience
Note: Flesch Reading Ease is a useful proxy for content accessibility but is NOT a direct Google ranking factor. John Mueller has confirmed Google does not use basic readability scores for ranking. Yoast deprioritized Flesch scores in v19.3. Use readability analysis as a content quality indicator, not as an SEO metric to optimize directly.
Grade level: match target audience
Sentence length: average 15-20 words
Paragraph length: 2-4 sentences
Keyword Optimization
Primary keyword in title, H1, first 100 words
Natural density (1-3%)
Semantic variations present
No keyword stuffing
Content Structure
Logical heading hierarchy (H1 -> H2 -> H3)
Scannable sections with descriptive headings
Bullet/numbered lists where appropriate
Table of contents for long-form content
Multimedia
Relevant images with proper alt text
Videos where appropriate
Infographics for complex data
Charts/graphs for statistics
Internal Linking
3-5 relevant internal links per 1000 words
Descriptive anchor text
Links to related content
No orphan pages
External Linking
Cite authoritative sources
Open in new tab for user experience
Reasonable count (not excessive)
AI Content Assessment (Sept 2025 QRG addition)
Google's raters assess low-quality, scaled, copied, or AI-generated main content patterns rather than AI authorship as a standalone issue.
Acceptable AI Content
Demonstrates genuine E-E-A-T
Provides unique value
Has human oversight and editing
Contains original insights
Low-Quality AI Content Markers
Generic phrasing, lack of specificity
No original insight
Repetitive structure across pages
No author attribution
Factual inaccuracies
Helpful Content System (March 2024): The Helpful Content System was merged into Google's core ranking algorithm during the March 2024 core update. It no longer operates as a standalone classifier. Helpfulness signals are now weighted within every core update. The same principles apply (people-first content, demonstrating E-E-A-T, satisfying user intent), but enforcement is continuous rather than through separate HCU updates. Google now also documents continuous, smaller unannounced core updates between major ones (changelog 2025-12-09).
Gen-AI optimization is SEO (Google docs, 2026-06-29): the official "optimizing for generative AI features" guide states you do not need new AI files, markup, Markdown, content chunking, or AI-specific rewrites; chasing inauthentic "mentions" is unhelpful. AEO/GEO is rebranded SEO rooted in core ranking/quality.
Honest scoping (Google docs, 2026-06-05): per "Using third-party SEO tools, services, and advice," no tool guarantees rankings and third-party tools have no access to Google's internal ranking data. claude-seo's scores are heuristics, not Google-internal signals, so say so in reports, and validate GEO/AEO findings against Google's official guidance (Search Console is the first-party source).
AI Citation Readiness (GEO signals)
Optimize for AI search engines (ChatGPT, Perplexity, Google AI Overviews):
Clear, quotable statements with statistics/facts
Structured data (especially for data points)
Strong heading hierarchy (H1->H2->H3 flow)
Answer-first formatting for key questions
Tables and lists for comparative data
Clear attribution and source citations
AI Search Visibility & GEO (2025-2026)
Google AI Mode is Google's conversational AI search surface. Google's last official model naming for AI Mode / AI Overviews is a custom version of Gemini 2.5. Treat third-party AI Mode usage, citation, and link-share figures as methodology-dependent unless primary-sourced, and optimize for both AI Mode and AI Overviews (see the seo-geo skill).
Key optimization strategies for AI citation:
Structured answers: Clear question-answer formats, definition patterns, and step-by-step instructions that AI systems can extract and cite
First-party data: Original research, statistics, case studies, and unique datasets are highly cited by AI systems
Schema markup: Article and other relevant structured content. FAQPage no longer produces Google FAQ rich results; use QAPage only for genuine user Q&A where appropriate
Topical authority: AI systems preferentially cite sources that demonstrate deep expertise. Build content clusters, not isolated pages
Entity clarity: Ensure brand, authors, and key concepts are clearly defined with structured data (Organization, Person schema)
Multi-platform tracking: Monitor visibility across Google AI Overviews, AI Mode, ChatGPT, Perplexity, and Bing Copilot, not just traditional rankings. Treat AI citation as a standalone KPI alongside organic rankings and traffic.
Generative Engine Optimization (GEO):
Per Google's AI optimization guide, "AEO" and "GEO" are rebranded labels for SEO: AI Overviews and AI Mode are grounded in the same ranking and quality systems as classic Search. The optimization signals that matter (quotability, attribution, heading hierarchy, freshness) are SEO fundamentals applied to AI-search surfaces, not a separate discipline. Cross-reference the seo-geo skill for detailed workflows; both surfaces share the primary-source synthesis in skills/seo-geo/references/google-ai-optimization-guide.md.
Content Freshness
Publication date visible
Last updated date if content has been revised
Flag content older than 12 months without update for fast-changing topics
Output
Content Quality Score: XX/100
E-E-A-T Breakdown
Factor
Score
Key Signals
Experience
XX/20
...
Expertise
XX/25
...
Authoritativeness
XX/25
...
Trustworthiness
XX/30
...
Weights are this skill's own scoring model, ordered to reflect Google's
stated hierarchy: Trust is most important (30), then Expertise/
Authoritativeness (25 each), then Experience (20); maxima sum to 100. Google
publishes no numeric E-E-A-T weights (only that trust is most important), so
treat the split as our internal model. Do not use an equal 25/25/25/25 split
(it contradicts Google's "trust is most important").
AI Citation Readiness: XX/100
Issues Found
Recommendations
DataForSEO Integration (Optional)
If DataForSEO MCP tools are available, use kw_data_google_ads_search_volume for real keyword volume data, dataforseo_labs_bulk_keyword_difficulty for difficulty scores, dataforseo_labs_search_intent for intent classification, and content_analysis_summary for content quality analysis.
Error Handling
Scenario
Action
URL unreachable (DNS failure, connection refused)
Report the error clearly. Do not guess page content. Suggest the user verify the URL and try again.
Content behind paywall (402/403, login wall)
Report that the content is not publicly accessible. Analyze only the visible portion (meta tags, headers) and note the limitation.
Thin content (fewer than 100 words retrievable)
Report the findings as-is rather than guessing. Flag the page as potentially JavaScript-rendered or gated, and suggest the user provide the full text directly.
FLOW Framework Integration
For prompt-guided content optimization, use /seo flow optimize <url> and /seo flow win <url>: FLOW's optimize and win prompts provide structured E-E-A-T improvement and BOFU conversion workflows.
