Skill detail
seo-content
Content quality and E-E-A-T analysis skill with AI citation readiness assessment and last-mile draft cleanup for AI phrasing and invisible characters.
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SKILL.md
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--- name: seo-content description: > Content quality and E-E-A-T analysis with AI citation readiness assessment, plus last-mile draft cleanup (AI-typical phrasing and invisible Unicode watermark characters). Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", "content audit", "humanize", "AI phrasing", "remove watermarks", or "invisible characters". user-invocable: true argument-hint: "[url]" license: MIT metadata: author: AgriciDaniel version: "2.3.1" 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 conteRead the full source on GitHub (opens external page)