geo-content — Анализ контента для E-E-A-T и ИИ

--- name: geo-content description: Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure version: 1.0.0 author: geo-seo-claude tags: [geo, content-quality, eeat, citability, ai-content, topical-authority] allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write --- # 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:** | 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 --- ## 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 --- ## 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..." | --- ## 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") --- ## 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 | --- ## 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 --- ## Output Format Generate **GEO-CONTENT-ANALYSIS.md** with: ```markdown # 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] ```