What It Does
Beyond E-E-A-T, the skill audits readability, keyword optimization, content structure, internal/external linking, multimedia usage, and content freshness, then outputs prioritized recommendations.
It also assesses **AI Citation Readiness** — how likely your content is to be cited by ChatGPT, Perplexity, Google AI Overviews, and Bing Copilot — making it relevant for both traditional SEO and the emerging discipline of Generative Engine Optimization (GEO).
The SEO Content skill evaluates any URL against Google's E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) and scores content quality on a 100-point scale.
Key Features
- E-E-A-T Scoring (Sept 2025 QRG) — Scores Experience, Expertise, Authoritativeness, and Trustworthiness each out of 25 points, based on Google's updated Quality Rater Guidelines. Each dimension maps to concrete, detectable signals such as author credentials, original research, external citations, and trust indicators like HTTPS and contact information.
- AI Citation Readiness Assessment — Scores content on a 100-point scale for likelihood of being cited by AI search engines including Google AI Overviews, AI Mode, ChatGPT, Perplexity, and Bing Copilot. Evaluates quotability, answer-first formatting, schema markup, heading hierarchy, and use of first-party data — key GEO signals for 2025–2026.
- Content Metrics Analysis — Audits word count against page-type minimums (homepage, blog, service page, product page, etc.), readability (Flesch Reading Ease target 60–70), sentence and paragraph length, keyword density (1–3%), and semantic variation — all contextualized with accurate guidance on what Google actually uses as ranking signals.
- Content Structure & Linking Audit — Evaluates heading hierarchy (H1→H2→H3 flow), internal link density (3–5 per 1,000 words), anchor text quality, external citation patterns, multimedia usage, and alt text — flagging structural issues that reduce scannability or create orphaned pages.
- AI Content Quality Detection — Identifies low-quality AI content markers such as generic phrasing, lack of specificity, repetitive structure, missing author attribution, and factual inaccuracies — aligned with how Google's raters formally assess AI-generated content under the March 2024 Helpful Content System integration.
- DataForSEO Integration (Optional) — When DataForSEO MCP tools are available, the skill can pull real keyword search volume, bulk keyword difficulty scores, search intent classification, and content analysis data to enrich its recommendations with live market data.
Use Cases
- Pre-publish content review — Before a blog post or service page goes live, run the skill against the URL to get an E-E-A-T score and a list of gaps — missing author bio, no original data, thin word count for the page type — so editors can address issues before indexing.
- AI search visibility optimization — For pages targeting AI Overviews or ChatGPT citations, use the AI Citation Readiness score to identify whether content uses answer-first formatting, structured data, and quotable statistics — then apply the GEO recommendations to improve discoverability in conversational search results.
- Thin content identification in a content audit — Run the skill across underperforming URLs to surface pages with insufficient topical coverage, missing trust signals, or low E-E-A-T scores that may be dragging down overall site quality in Google's core updates.
- AI-generated content quality check — After producing AI-assisted drafts, use the skill to verify whether the published content demonstrates genuine E-E-A-T, contains original insights, and avoids the generic phrasing patterns that Google's quality raters are trained to flag as low-quality AI content.