Analyze Content Quality and E-E-A-T Signals

Content Quality & E-E-A-T Analysis audits content quality, readability, thin-content risk, and E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals, per Google's September 2025 Quality Rater Guidelines, producing a Content Quality Score and a separate AI Citation Readiness score.

Use this when auditing content quality, readability, thin content risk, or E-E-A-T signals, when the user wants a content-focused SEO review rather than a full technical audit, or when checking whether content is structured and trustworthy enough for both search ranking and AI citation.

Scores four E-E-A-T pillars, 25 points each toward a 100-point score: Experience (original research, case studies, before/after results, personal anecdotes, unique data, first-hand photos/video); Expertise (author credentials, professional background, technical depth, well-sourced claims); Authoritativeness (external citations, backlinks from authoritative sources, brand mentions, being cited by other experts); and Trustworthiness (contact info, privacy policy, testimonials, date stamps, transparent corrections, HTTPS). It also checks word count against page-type floors - homepage 500, service page 800, blog post 1,500, product page 300+ or 400+ for complex products, location page 500-600 - explicitly framed as topical-coverage floors, not ranking targets, since Google has confirmed word count isn't a direct ranking factor; readability (Flesch Reading Ease 60-70 as a quality proxy, not a ranking metric; 15-20 word average sentences; 2-4 sentence paragraphs); keyword placement and natural density of 1-3% with no stuffing; heading hierarchy and scannability; multimedia use; internal linking density of 3-5 relevant links per 1000 words; and external citation quality. A separate AI-generated-content check looks for genuine E-E-A-T and human editing as acceptable signals versus generic phrasing, repetitive structure, and no author attribution as low-quality markers, and flags content freshness by publication/update date, calling out anything over 12 months stale on fast-changing topics.

Covers AI citation readiness (GEO) for ChatGPT, Perplexity, and Google AI Overviews/AI Mode - quotable statements, structured data, answer-first formatting, tables for comparative data, clear source attribution - and cross-references the separate seo-geo skill for deeper GEO workflows. It optionally uses DataForSEO MCP tools when available: kw_data_google_ads_search_volume for keyword volume, dataforseo_labs_bulk_keyword_difficulty for difficulty, dataforseo_labs_search_intent for intent classification, and content_analysis_summary for content-quality analysis. It defines explicit error handling for an unreachable URL (report the error, don't guess), paywalled content (analyze only the visible meta tags/headers and note the limitation), and thin retrievable content under 100 words (report as-is and flag possible JS-rendering or gating rather than guessing).

SEO or content teams who need a content-specific quality and trustworthiness audit, distinct from a full technical SEO audit, covering both traditional ranking signals and AI-search citation readiness across Google AI Mode, ChatGPT, Perplexity, and Bing Copilot.