CONTENT SKILL
seo-content
Content quality and E-E-A-T scoring against Google’s own who-how-why test, with an AI citation readiness score and a deterministic draft cleanup that strips invisible Unicode watermarks and AI-typical phrasing.
by Daniel AgriciAgriciDaniel/claude-seoMIT licencev2.3.1upstream 2026-09-10read by us 11 September 2026
It begins with Google’s three questions from the helpful-content guide, who created it, how, and why, and treats them as the gate before any sub-score. Then experience, expertise, authoritativeness and trust get 20, 25, 25 and 30 points, ordered by Google’s stated "trust is most important", and the skill says out loud that the split is its own model.
It is careful where most content skills are not: word counts are floors not targets, Flesch is not a ranking factor, FAQPage no longer produces Google rich results, the Helpful Content System merged into core in March 2024, and "AEO and GEO are rebranded SEO" per Google’s June 2026 guide.
The cleanup script is the concrete tool: two passes, one removing zero-width and directional characters and Unicode tag smuggling, one making conservative one-to-one swaps of AI-typical phrases. It states that statistical watermarks cannot be removed and declines to launder content you do not own.
When to use it
The phrases that trigger it
From the skill’s own description: say any of these and an agent that has it installed will load it.
- content quality
- E-E-A-T
- readability check
- thin content
- content audit
- humanize
- AI phrasing
- remove watermarks
- invisible characters
What’s inside
The playbook, section by section
Who, how, why
Visible byline and credentials; process disclosure where readers would ask, especially for AI-assisted work; written to help, not to attract clicks.
Content metrics with caveats
Page-type coverage floors (homepage 500, service 800, blog 1,500, product 300+), readability as a quality indicator not an SEO metric, 3 to 5 internal links per thousand words.
AI content assessment
Raters assess low-quality, scaled or copied patterns, not AI authorship; the markers are generic phrasing, no original insight, repetitive structure, no attribution, inaccuracies.
Honest scoping
Per Google’s June 2026 note on third-party tools, the skill’s scores are heuristics with no access to ranking data, and reports must say so.
Draft cleanup
invisible_removed and changes logged in JSON; emoji sequences preserved; nothing paraphrased or added.
Output tables
Content quality out of 100, the four-factor E-E-A-T breakdown with key signals, AI citation readiness out of 100, issues, recommendations.
Reference files: none, the whole skill is SKILL.md.
See it in action
One real run, cropped
We installed the skill folder, gave it the request below, and kept what it returned. Nothing was edited; the excerpt is the first 1,716 of 11,487 characters. The full output is in our repository as research/skills/runs/seo-content.md.
Run the content quality and E-E-A-T analysis on https://addition-labs.com/resources/guides/seo-audit. Run the plugin scripts through the launcher where the skill calls for them: the plugin root is /private/tmp/claude-501/-Users-mertmuftuoglu-dev-addition-growth-system-Addition-Website/fbf5911f-bbfc-4575-a8f6-8dfe4797faf7/scratchpad/skillrepos/claude-seo (${CLAUDE_PLUGIN_ROOT}) and the runtime data dir is /private/tmp/claude-501/-Users-mertmuftuoglu-dev-addition-growth-system-Addition-Website/fbf5911f-bbfc-4575-a8f6-8dfe4797faf7/scratchpad/claude-seo-data Give the score table and the issues.
Content Quality & E-E-A-T Analysis
URL: https://addition-labs.com/resources/guides/seo-audit Fetched: 2026-09-11 (HTTP 200, server-rendered article body; header/footer are injected client-side) Page type: Long-form guide (blog/guide floor: 1,500 words)
> All scores below are claude-seo heuristics, not Google-internal signals. Google publishes no numeric E-E-A-T weights; the 20/25/25/30 split is this skill's own model (trust weighted highest). Validate against Search Console before acting on ranking assumptions.
Google's Who / How / Why test
| Question | Finding |
|---|---|
| Who created it? | Byline reads "By the Addition team". No named author, no author bio page, no credentials on the page. Article schema author is an Organization, not a Person. The /about page names the founder (ex-Google Ads account manager, three years at Semrush) but nothing on this guide links to it. Weak on-page, moderate site-wide. |
| How was it created? | Strong. 19 sources listed with dates and access dates, staleness notes on old studies ("Measured 4 years ago, on a surface that has moved since"), original annotated screenshots (PageSpeed Insights failed assessment, Search Console impressions-vs-clicks), first-person process ("We check this pair first on any audit"). No AI-assistance disclosure either way. |
| Why does it exist? | Reads as written to help: separates published thresholds from convention, refuses to invent a price range ("no published survey prices ecommerce SEO audits ... So there is no range here"). Commercial links to /services/seo and /shopify/seo are present but proportionate (2 of 15 internal links). Pass. |
Content Quality Score: 76/100
Cropped here. The rest continues in the same register.
What it could not do in this run
DataForSEO keyword volume/difficulty/intent and content_analysis_summary (MCP not connected); backlink/brand-mention data for Authoritativeness (no tool); Flesch Reading Ease is my own heuristic syllable-count script because the plugin ships no readability script; no Search Console data.
Method behind it
Where we would differ, and why
Our AI SEO guide covers the citation-readiness half with the studies behind it. The skill’s E-E-A-T half is the closest thing on this shelf to our own source rules: named authors, dated sources, and a limit stated rather than argued.
- Note 1
- The keyword section keeps "natural density (1 to 3%)". Its sibling seo-content-brief skill in the same plugin says not to optimise to a density at all; the plugin disagrees with itself here, and the brief skill is right.
- Note 2
- Coverage floors by page type are useful as a smell test and dangerous as a target; the skill says so, and we would still remove the table from a report to a client.
SKILL.md
The upstream file, as we read it
Copyright Daniel Agrici, MIT licence, commit 55c7914 of AgriciDaniel/claude-seo. Reproduced here under that licence so you can read what the agent will read; the folder’s reference files are in the repository.
Open SKILL.md (1,678 words)
---
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 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 assess low-quality, scaled, copied, or AI-generated main content patterns rather than AI authorship as a standalone issue.
### 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. Google now also documents **continuous, smaller unannounced core updates** between major ones (changelog 2025-12-09).
> **Gen-AI optimization is SEO (Google docs, 2026-06-29):** the official "optimizing for generative AI features" guide states you do **not** need new AI files, markup, Markdown, content chunking, or AI-specific rewrites; chasing inauthentic "mentions" is unhelpful. AEO/GEO is rebranded SEO rooted in core ranking/quality.
> **Honest scoping (Google docs, 2026-06-05):** per "Using third-party SEO tools, services, and advice," no tool guarantees rankings and third-party tools have no access to Google's internal ranking data. claude-seo's scores are **heuristics**, not Google-internal signals, so say so in reports, and validate GEO/AEO findings against Google's official guidance (Search Console is the first-party source).
## Draft Cleanup: AI Phrasing & Invisible Watermarks
For "humanize this", "remove watermarks", or "clean up this draft", run the
bundled cleanup script on the user's own content:
```bash
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run content_humanize.py draft.md -o cleaned.md
cat draft.md | "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run content_humanize.py --json
```
Two deterministic passes, both logged in the JSON output:
1. **Invisible characters** (`invisible_removed`): strips zero-width
codepoints, directional marks/overrides, Unicode tag characters (hidden
text smuggling), and normalizes exotic spaces. Emoji sequences (ZWJ,
variation selectors next to emoji) are preserved.
2. **AI-typical phrasing** (`changes`): conservative 1:1 swaps from the
replacement table ("delve into" → "explore", etc.). Nothing is
paraphrased or added.
Scope honesty: statistical watermarks (SynthID-style token-probability
schemes) live in word choice, not codepoints. No tool reliably detects or
removes them; do not claim otherwise in reports. This cleanup is for
editing the user's own drafts, not for laundering third-party content —
decline requests to strip provenance from content the user doesn't own.
## 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** is Google's conversational AI search surface. Google's last official model naming for AI Mode / AI Overviews is a custom version of **Gemini 2.5**. Treat third-party AI Mode usage, citation, and link-share figures as methodology-dependent unless primary-sourced, and optimize for both AI Mode and AI Overviews (see the `seo-geo` skill).
**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 and other relevant structured content. FAQPage no longer produces Google FAQ rich results; use QAPage only for genuine user Q&A where appropriate
- **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):**
Per Google's AI optimization guide, "AEO" and "GEO" are rebranded labels for SEO: AI Overviews and AI Mode are grounded in the same ranking and quality systems as classic Search. The optimization signals that matter (quotability, attribution, heading hierarchy, freshness) are SEO fundamentals applied to AI-search surfaces, not a separate discipline. Cross-reference the `seo-geo` skill for detailed workflows; both surfaces share the primary-source synthesis in `skills/seo-geo/references/google-ai-optimization-guide.md`.
## 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/20 | ... |
| Expertise | XX/25 | ... |
| Authoritativeness | XX/25 | ... |
| Trustworthiness | XX/30 | ... |
> Weights are **this skill's own scoring model**, ordered to reflect Google's
> stated hierarchy: **Trust is most important** (30), then Expertise/
> Authoritativeness (25 each), then Experience (20); maxima sum to 100. Google
> publishes no numeric E-E-A-T weights (only that trust is most important), so
> treat the split as our internal model. Do not use an equal 25/25/25/25 split
> (it contradicts Google's "trust is most important").
### 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. |
## FLOW Framework Integration
For prompt-guided content optimization, use `/seo flow optimize <url>` and `/seo flow win <url>`: FLOW's optimize and win prompts provide structured E-E-A-T improvement and BOFU conversion workflows.
Questions
Questions people ask before installing
Is the "humanize" pass a detector-beater?
No, and the skill says so: it removes invisible characters and swaps a list of tells. Statistical watermarks live in word choice and no tool removes them. It refuses to process content you do not own.
Where do the E-E-A-T weights come from?
The plugin author’s model, ordered by Google’s statement that trust matters most. Google publishes no numbers.
Does it check AI citation readiness the same way seo-geo does?
It scores a lighter version (quotable statements, structure, attribution) and hands the crawler and platform analysis to seo-geo.