Automated summary
Analyzes the quality of web content against Google's E-E-A-T criteria, including its readiness to be cited by AI systems.
Strengths
- Breaks E-E-A-T into four concrete axes (experience, expertise, authoritativeness, trustworthiness) with checkable signals
- Gives coverage floors per page type while correctly noting these are not direct ranking factors
- Adds an AI-content assessment grid with low-quality markers to watch for
- Covers precise structural checks: readability, keyword density, internal and external linking, multimedia
Limitations
- Several guidelines point to a bundled reference file (eeat-framework.md) not included in the provided SKILL.md
- Does not run technical SEO analysis such as crawling, HTTPS or markup validation; it judges content, not the whole site
- Numeric targets (word counts, Flesch 60-70) are indicative and vary widely by industry and audience
Use it to audit an existing article or landing page for E-E-A-T signals, readability and overall content quality before publishing.
Skip it for technical SEO diagnostics like indexing, page speed, tags or backlink profiles, which belong to other specialized skills.
Security analysis
SafeThis is a purely instructional SEO analysis skill. It declares no allowed tools, contains no executable commands, no network calls, no file writes or deletions, and no handling of secrets or credentials. The only file interaction is a suggestion to read a reference document within the skills directory, which is benign and non-destructive.
No concerns found
How this analysis is madeExamples
Analyse la qualité du contenu de https://example.com/blog/guide-achat-velo-electrique selon les critères E-E-A-T et dis-moi ce qui manque.Vérifie si cette page de service est du thin content : elle fait environ 400 mots pour une page de service.Fais un readability check et une évaluation de la structure H1/H2/H3 de mon article avant que je le publie.name: seo-content description: > Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit". user-invokable: true argument-hint: "[url]" license: MIT metadata: author: AgriciDaniel version: "1.8.1" category: seo
Content Quality & E-E-A-T Analysis
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 contents for long-form content
Multimedia
- Relevant images with proper alt text
- Videos where appropriate
- Infographics for complex data
- Charts/graphs for statistics
Internal Linking
- 3-5 relevant internal links per 1000 words
- Descriptive anchor text
- Links to related content
- No orphan pages
External Linking
- Cite authoritative sources
- Open in new tab for user experience
- Reasonable count (not excessive)
AI Content Assessment (Sept 2025 QRG addition)
Google's raters now formally assess whether content appears AI-generated.
Acceptable AI Content
- Demonstrates genuine E-E-A-T
- Provides unique value
- Has human oversight and editing
- Contains original insights
Low-Quality AI Content Markers
- Generic phrasing, lack of specificity
- No original insight
- Repetitive structure across pages
- No author attribution
- Factual inaccuracies
Helpful Content System (March 2024): The Helpful Content System was merged into Google's core ranking algorithm during the March 2024 core update. It no longer operates as a standalone classifier. Helpfulness signals are now weighted within every core update. The same principles apply (people-first content, demonstrating E-E-A-T, satisfying user intent), but enforcement is continuous rather than through separate HCU updates.
AI Citation Readiness (GEO signals)
Optimize for AI search engines (ChatGPT, Perplexity, Google AI Overviews):
- Clear, quotable statements with statistics/facts
- Structured data (especially for data points)
- Strong heading hierarchy (H1->H2->H3 flow)
- Answer-first formatting for key questions
- Tables and lists for comparative data
- Clear attribution and source citations
AI Search Visibility & GEO (2025-2026)
Google AI Mode launched publicly in May 2025 as a separate tab in Google Search, available in 180+ countries. Unlike AI Overviews (which appear above organic results), AI Mode provides a fully conversational search experience with zero organic blue links, making AI citation the only visibility mechanism.
Key optimization strategies for AI citation:
- Structured answers: Clear question-answer formats, definition patterns, and step-by-step instructions that AI systems can extract and cite
- First-party data: Original research, statistics, case studies, and unique datasets are highly cited by AI systems
- Schema markup: Article, FAQ (for non-Google AI platforms), and structured content schemas help AI systems parse and attribute content
- Topical authority: AI systems preferentially cite sources that demonstrate deep expertise. Build content clusters, not isolated pages
- Entity clarity: Ensure brand, authors, and key concepts are clearly defined with structured data (Organization, Person schema)
- Multi-platform tracking: Monitor visibility across Google AI Overviews, AI Mode, ChatGPT, Perplexity, and Bing Copilot, not just traditional rankings. Treat AI citation as a standalone KPI alongside organic rankings and traffic.
Generative Engine Optimization (GEO):
GEO is the emerging discipline of optimizing content specifically for AI-generated answers. Key GEO signals include: quotability (clear, concise extractable facts), attribution (source citations within your content), structure (well-organized heading hierarchy), and freshness (regularly updated data). Cross-reference the seo-geo skill for detailed GEO workflows.
Content Freshness
- Publication date visible
- Last updated date if content has been revised
- Flag content older than 12 months without update for fast-changing topics
Output
Content Quality Score: XX/100
E-E-A-T Breakdown
| Factor | Score | Key Signals | | ----------------- | ----- | ----------- | | Experience | XX/25 | ... | | Expertise | XX/25 | ... | | Authoritativeness | XX/25 | ... | | Trustworthiness | XX/25 | ... |
AI Citation Readiness: XX/100
Issues Found
Recommendations
DataForSEO Integration (Optional)
If DataForSEO MCP tools are available, use kw_data_google_ads_search_volume for real keyword volume data, dataforseo_labs_bulk_keyword_difficulty for difficulty scores, dataforseo_labs_search_intent for intent classification, and content_analysis_summary for content quality analysis.
Error Handling
| Scenario | Action | | ------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | | URL unreachable (DNS failure, connection refused) | Report the error clearly. Do not guess page content. Suggest the user verify the URL and try again. | | Content behind paywall (402/403, login wall) | Report that the content is not publicly accessible. Analyze only the visible portion (meta tags, headers) and note the limitation. | | Thin content (fewer than 100 words retrievable) | Report the findings as-is rather than guessing. Flag the page as potentially JavaScript-rendered or gated, and suggest the user provide the full text directly. |
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/content-quality-e-e-a-t-analysis-mryiqicx/download' --output '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md.part' && mv '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md.part' '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && test -s '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/seo-content' && cp -R '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx' '.claude/skills/seo-content'Cursor
test -f '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && test -s '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && mkdir -p '.cursor/skills' && test ! -e '.cursor/skills/seo-content' && cp -R '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx' '.cursor/skills/seo-content'Codex
test -f '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && test -s '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md' && mkdir -p '.agents/skills' && test ! -e '.agents/skills/seo-content' && cp -R '.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx' '.agents/skills/seo-content'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx'openskills read 'content-quality-e-e-a-t-analysis-mryiqicx'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.
openskills syncManual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/content-quality-e-e-a-t-analysis-mryiqicx/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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