# seo-content > Content quality and E-E-A-T analysis with AI citation readiness assessment, covering experience signals, expertise indicators, authoritativeness markers, and trustworthiness factors aligned with Google's 2025 quality rater guidelines. **Use case**: Score content for E-E-A-T and AI citation readiness **Canonical URL**: https://agentcookbooks.com/skills/seo-content/ **Topics**: claude-code, skills, marketing, seo **Trigger phrases**: "content quality", "E-E-A-T", "content analysis", "thin content", "content audit" **Source**: [AgriciDaniel](https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-content) **License**: MIT --- ## What it does `seo-content` is a Claude Code skill from AgriciDaniel's [claude-seo repo](https://github.com/AgriciDaniel/claude-seo). It evaluates content against Google's September 2025 Quality Rater Guidelines, scoring on four E-E-A-T dimensions: Experience (firsthand signals — original research, before/after results, process documentation), Expertise (author credentials, technical depth, accurate sourcing), Authoritativeness (external citations, brand mentions, industry recognition), and Trustworthiness (contact info, privacy policy, date stamps, HTTPS). Beyond E-E-A-T it scores AI Citation Readiness for Generative Engine Optimization — assessing whether content is structured to be cited by Google AI Overviews, ChatGPT, and Perplexity. Key signals include passage-level citability (optimal 134–167 word self-contained answer blocks), question-based headings, tables for comparative data, and entity clarity. The skill explicitly notes the March 2024 merger of the Helpful Content System into Google's core ranking algorithm. ## When to use it Reach for it when: - A page ranks technically well but doesn't convert — E-E-A-T gaps are often the cause - You want to know if your content is structured to appear in AI Overviews or ChatGPT web search citations - You are auditing a site acquisition and need a content quality baseline before doing anything else When *not* to reach for it: - The URL is behind authentication or a paywall; the skill can only analyze visible content and will report the limitation honestly - You need keyword volume or difficulty data — use `seo-dataforseo` or `seo-google` for that ## Install Copy the [`seo-content` SKILL.md](https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-content) into `.claude/skills/seo-content/`. Trigger phrases: "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", "content audit". Invoke with `/seo content ` for a full analysis. DataForSEO MCP integration is optional — if available, it adds real keyword volume and intent data to the assessment. ## What a session looks like A typical session has three phases: 1. **E-E-A-T audit.** The skill scores each dimension against QRG criteria. Experience is the hardest to fake and the highest signal — original case studies, named authors with disclosed credentials, and firsthand data points all score strongly here. 2. **Content metrics.** Word count is checked against page-type minimums (blog posts 1,500+, service pages 800+), but with an explicit note that word count is not a ranking factor — topical coverage completeness is. Readability, keyword density (1–3%), and multimedia presence are also evaluated. 3. **AI Citation Readiness report.** Content is scored on citability signals: self-contained answer blocks, direct definitions, specific statistics with attribution, and structured data presence. A platform-by-platform breakdown is given for Google AI Overviews, ChatGPT, and Perplexity. ## Receipts **Works well:** The AI Citation Readiness section catches structural patterns traditional SEO audits ignore — buried conclusions, vague general statements, and missing author attribution are exactly the signals that prevent content from being cited in AI search, and they get surfaced here. **Backfires:** Flesch Reading Ease scores are reported but explicitly flagged as not a Google ranking factor (the skill quotes Mueller confirming this). Some users expect a readability score to mean more than it does; the skill adds appropriate caveats rather than letting the number drive decisions. **Pattern that works:** Fix E-E-A-T gaps before optimizing for AI citation — the same signals that make content trustworthy to human quality raters also make it citable by AI systems. They are not separate workstreams. ## Source and attribution Originally written by [AgriciDaniel](https://github.com/AgriciDaniel). The canonical SKILL.md and supporting files live in the [`seo-content` folder](https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-content) of the [claude-seo repository](https://github.com/AgriciDaniel/claude-seo). License: MIT. Install, adapt, and redistribute with attribution preserved. This page documents the skill from a practitioner's perspective. For the formal spec and updates, defer to the source repo.