| name | seo-content |
| description | SEO content strategy and quality: E-E-A-T analysis, readability, thin-content detection, AI citation readiness; competitive content briefs with per-section word counts; SERP-overlap topic clustering with hub-and-spoke architecture and internal link matrices; industry content planning (SaaS, e-commerce, local, publisher, agency); programmatic SEO page generation; and search experience (SXO) analysis for well-optimized pages that fail to rank. Use when the user says 'content quality', 'E-E-A-T', 'content brief', 'content plan', 'topic cluster', 'pillar page', 'keyword grouping', 'programmatic SEO', 'thin content', or 'why doesn't this page rank'. Not for technical crawl issues (seo-technical) or full audits (seo-audit). |
| user-invocable | true |
| argument-hint | [url] |
| license | MIT |
| metadata | {"author":"AgriciDaniel","version":"2.2.0","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. |
Primary source:
https://developers.google.com/search/docs/fundamentals/creating-helpful-content
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)
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 now formally assess whether content appears AI-generated.
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.
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 — powered by Gemini 3.5 Flash since I/O 2026 (May 2026) and now past 1 billion monthly users globally. Unlike AI Overviews (which appear above organic results), AI Mode is a fully conversational experience with zero organic blue links, making AI citation the only visibility mechanism. It is a distinct citation engine from AI Overviews — the two share only ~14% of cited URLs — so optimize for both surfaces, not one (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, FAQPage (Google retired FAQ rich results in May 2026, but the markup still aids AI parsing/entity resolution) or QAPage for genuine user Q&A, and structured content schemas help AI systems parse and attribute content
- 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/25 | ... |
| Expertise | XX/25 | ... |
| Authoritativeness | XX/25 | ... |
| Trustworthiness | XX/25 | ... |
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.
Consolidated capabilities (references)
