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Agent skill

GEO Content E-E-A-T Scorer

by zubair-trabzada in zubair-trabzada/geo-seo-claude

Scores a page's content against Google's E-E-A-T framework and AI-citability structure, then writes a scored gap-analysis report.

MITAuto-check: notesMarketing & SEO

Install GEO Content E-E-A-T Scorer

skills CLI
$ npx skills add zubair-trabzada/geo-seo-claude --skill geo-content -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zubair-trabzada/geo-seo-claude geo-content --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/geo-content .claude/skills/geo-content && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
geo-content
GitHub stars
11k
Used in
2 other repos
Token cost
~4k tokens
SKILL.md length
1,876 words
Files
1
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

Scores a page's content against Google's E-E-A-T framework and AI-citability structure, then writes a scored gap-analysis report.

  • Works in 2 steps: E-E-A-T signals — does the content… → AI citability — is the content…
  • Checking whether a page's content is likely to be cited by AI search
  • SKILL.md covers Purpose, How to Use This Skill, E-E-A-T Framework (100 points… and Content Quality Metrics, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

This skill fetches target pages, such as the homepage and key blog or product pages, and scores Experience, Expertise, Authoritativeness, and Trustworthiness at 25 points each against concrete signals like first-person accounts, original research, case studies with real numbers, and evidence such as screenshots, flagging weak experience such as hedging language or content that only summarizes other sources.

Beyond the four E-E-A-T dimensions it checks content-quality metrics such as structure, readability, and depth, AI-content quality signals, and topical authority across the whole site, then writes the scores and reasoning into a GEO-CONTENT-ANALYSIS.md report.

When your agent uses it

  • Checking whether a page's content is likely to be cited by AI search
  • Scoring a site's E-E-A-T signals before a content push
  • Finding where content reads as generic rather than first-hand

Example prompts

  • “Score our blog's homepage against the E-E-A-T framework.”
  • “Check why this product page might not get cited by AI search.”
  • “Audit topical authority across our help center.”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash, WebFetch, Write

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. E-E-A-T signals — does the content demonstrate real expertise and trust?
  2. AI citability — is the content structured so AI platforms can extract and cite specific claims?

What it can do on your machine

Read from SKILL.md and the folder at commit 989cae0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash
    • WebFetch
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

GEO Content E-E-A-T Scorer loads about 4k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 1,876 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zubair-trabzada/geo-seo-claude at commit 989cae0, republished under its MIT licence (© zubair-trabzada). 1,876 words, ~3,963 tokens.

Download SKILL.mdSave it as .claude/skills/geo-content/SKILL.md (or your agent's skills folder).
name
geo-content
description
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
allowed-tools
Read, Grep, Glob, Bash, WebFetch, Write
version
1.0.0
author
geo-seo-claude
tags
geo, content-quality, eeat, citability, ai-content, topical-authority

GEO Content Quality & E-E-A-T Assessment

Purpose

AI search platforms do not just find content — they evaluate whether content deserves to be cited. The primary framework for this evaluation is E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), which per Google's December 2025 Quality Rater Guidelines update now applies to ALL competitive queries, not just YMYL (Your Money Your Life) topics. Content that scores high on E-E-A-T is dramatically more likely to be cited by AI platforms.

This skill evaluates content through two lenses:

  1. E-E-A-T signals — does the content demonstrate real expertise and trust?
  2. AI citability — is the content structured so AI platforms can extract and cite specific claims?

How to Use This Skill

  1. Fetch the target page(s) — homepage, key blog posts, service/product pages
  2. Evaluate E-E-A-T across the 4 dimensions (25% each)
  3. Assess content quality metrics (structure, readability, depth)
  4. Check for AI content quality signals
  5. Evaluate topical authority across the site
  6. Score and generate GEO-CONTENT-ANALYSIS.md

E-E-A-T Framework (100 points total)

Experience — 25 points

First-hand knowledge and direct involvement with the topic. AI platforms increasingly distinguish between content that reports on a topic and content from someone who has DONE it.

Signals to evaluate:

SignalPointsHow to Score
First-person accounts ("I tested...", "We implemented...")55 if present and specific, 3 if generic, 0 if absent
Original research or data not available elsewhere55 if original data, 3 if references original work, 0 if none
Case studies with specific results44 if detailed with numbers, 2 if general, 0 if none
Screenshots, photos, or evidence of direct use33 if authentic evidence, 1 if stock/generic, 0 if none
Specific examples from personal experience44 if specific and unique, 2 if somewhat specific, 0 if generic
Demonstrations of process (not just outcome)44 if step-by-step from experience, 2 if partial, 0 if none

What to flag as weak Experience:

  • Content that only summarizes what other sources say without adding new perspective
  • Generic advice that could apply to any situation ("It depends on your needs")
  • No mention of actual usage, testing, or direct involvement
  • Hedging language that suggests lack of direct knowledge ("reportedly", "supposedly", "some say")
Expertise — 25 points

Demonstrated knowledge depth and professional competence in the subject matter.

Signals to evaluate:

SignalPointsHow to Score
Author credentials visible (bio, degrees, certifications)55 if full credentials, 3 if basic bio, 0 if no author
Technical depth appropriate to topic55 if thorough technical treatment, 3 if adequate, 0 if superficial
Methodology explanation (how conclusions were reached)44 if clear methodology, 2 if some explanation, 0 if none
Data-backed claims (statistics, research citations)44 if well-sourced, 2 if some data, 0 if unsupported claims
Industry-specific terminology used correctly33 if accurate specialized language, 1 if basic, 0 if errors
Author page with detailed professional background44 if dedicated author page, 2 if brief bio, 0 if none

What to flag as weak Expertise:

  • Claims without supporting evidence or sources
  • Surface-level coverage of complex topics
  • Misuse of technical terminology
  • No visible author or author without relevant credentials
  • Content that is broad and generic rather than deep and specific
Authoritativeness — 25 points

Recognition by others as a credible source on the topic.

Signals to evaluate:

SignalPointsHow to Score
Inbound citations from authoritative sources55 if cited by major sources, 3 if some citations, 0 if none
Author quoted or cited in press/media44 if media mentions, 2 if industry mentions, 0 if none
Industry awards or recognition mentioned33 if relevant awards, 1 if tangential, 0 if none
Speaker credentials (conferences, events)33 if listed, 0 if none
Published in peer-reviewed or respected outlets44 if tier-1 publications, 2 if industry outlets, 0 if none
Comprehensive topic coverage (topical authority)33 if site covers topic thoroughly, 1 if some coverage, 0 if isolated
Brand mentioned on Wikipedia or authoritative references33 if Wikipedia, 2 if other encyclopedic refs, 0 if none

What to flag as weak Authoritativeness:

  • Single-topic site with no depth of coverage
  • No external validation of expertise claims
  • No backlinks from authoritative sources
  • Claims of authority without evidence (self-proclaimed "expert")
Trustworthiness — 25 points

Signals that the content and its publisher are reliable and transparent.

Signals to evaluate:

SignalPointsHow to Score
Contact information visible (address, phone, email)44 if full contact info, 2 if email only, 0 if none
Privacy policy present and linked22 if present, 0 if absent
Terms of service present11 if present, 0 if absent
HTTPS with valid certificate22 if valid HTTPS, 0 if not
Editorial standards or corrections policy33 if documented, 1 if implicit, 0 if none
Transparent about business model and conflicts33 if clear disclosures, 1 if some, 0 if none
Reviews and testimonials from real customers33 if verified reviews, 1 if testimonials, 0 if none
Accurate claims (no misinformation detected)44 if all claims accurate, 2 if mostly accurate, 0 if errors found
Clear affiliate/sponsorship disclosures33 if properly disclosed, 0 if undisclosed or absent

What to flag as weak Trustworthiness:

  • No contact information or physical address
  • Missing privacy policy or terms
  • Undisclosed affiliate links or sponsored content
  • Claims that are verifiably false or misleading
  • No way to contact the publisher for corrections

Content Quality Metrics

Word Count Benchmarks

These are floors, not targets. More words does not mean better content. The benchmark is the minimum length to adequately cover a topic for AI citability.

Page TypeMinimum WordsIdeal RangeNotes
Homepage500500-1,500Clear value proposition, not a wall of text
Blog post1,5001,500-3,000Thorough but focused
Pillar content / Ultimate guide2,0002,500-5,000Comprehensive topic coverage
Product page300500-1,500Descriptions, specs, use cases
Service page500800-2,000What, how, why, for whom
About page300500-1,000Company/person story and credentials
FAQ page5001,000-2,500Thorough answers, not one-liners
Readability Assessment
  • Target Flesch Reading Ease: 60-70 (8th-9th grade level)
  • This is NOT a direct ranking factor but affects citability — AI platforms prefer content that is clear and unambiguous
  • Overly academic writing (score < 30) reduces citability for general queries
  • Overly simple writing (score > 80) may lack the depth needed for expertise signals

How to estimate without a tool:

  • Average sentence length: 15-20 words is ideal
  • Average paragraph length: 2-4 sentences
  • Presence of jargon: should be defined when first used
  • Passive voice: < 15% of sentences
Paragraph Structure for AI Parsing

AI platforms extract content at the paragraph level. Each paragraph should be a self-contained unit of meaning.

Optimal paragraph structure:

  • 2-4 sentences per paragraph (1-sentence paragraphs are weak; 5+ sentences are hard to extract)
  • One idea per paragraph — do not mix topics within a paragraph
  • Lead with the key claim — first sentence should contain the main point
  • Support with evidence — remaining sentences provide data, examples, or context
  • Quotable standalone — each paragraph should make sense if extracted in isolation
Show full SKILL.md (713 more words)Show less
Heading Structure
  • One H1 per page — the primary topic/title
  • H2 for major sections — should represent distinct subtopics
  • H3 for subsections — nested under relevant H2
  • No skipped levels — do not go from H1 to H3 without an H2
  • Descriptive headings — "How to Optimize for AI Search" not "Section 2"
  • Question-based headings where appropriate — these map directly to AI queries
Internal Linking
  • Every content page should link to 3-5 related pages on the same site
  • Links should use descriptive anchor text (not "click here")
  • Create a topic cluster structure: pillar page linked to/from all related subtopic pages
  • Orphan pages (no internal links pointing to them) are rarely cited by AI

AI Content Assessment

AI-Generated Content Policy

AI-generated content is acceptable per Google's guidance (March 2024 clarification) as long as it demonstrates genuine E-E-A-T signals and has human oversight. The concern is not HOW content is created but WHETHER it provides value.

Signs of Low-Quality AI Content (flag these)
SignalDescription
Generic phrasing"In today's fast-paced world...", "It's important to note that...", "At the end of the day..."
No original insightContent that only rephrases widely available information
Lack of first-hand experienceNo personal anecdotes, case studies, or specific examples
Perfect but empty structureWell-formatted headings with shallow content beneath them
No specific examplesUses abstract explanations without concrete instances
Repetitive conclusionsEach section ends with a variation of the same point
Hedging overload"Generally speaking", "In most cases", "It depends on various factors" without specifying which factors
Missing human voiceNo opinions, preferences, or professional judgment expressed
Filler contentParagraphs that could be deleted without losing information
No data or sourcesClaims presented as facts without attribution or evidence
High-Quality Content Signals (regardless of production method)
SignalDescription
Original dataSurveys, experiments, benchmarks, proprietary analysis
Specific examplesNamed products, companies, dates, numbers
Contrarian or nuanced viewsDisagreement with conventional wisdom, backed by reasoning
First-person experience"When I tested this..." or "Our team found..."
Updated informationReferences to recent events, current data
Expert opinionClear professional judgment, not just facts
Practical recommendationsSpecific, actionable advice, not vague guidance
Trade-offs acknowledged"This approach works well for X but not for Y because..."

Content Freshness Assessment

Publication Dates
  • Check for visible datePublished and dateModified in both the content and structured data
  • Content without dates is treated as less trustworthy by AI platforms
  • Dates should be specific (January 15, 2026) not vague ("recently")
Freshness Scoring
CriterionScore
Updated within 3 monthsExcellent — current and relevant
Updated within 6 monthsGood — still reasonably current
Updated within 12 monthsAcceptable — may need refresh
Updated 12-24 months agoWarning — review for accuracy
No date or 24+ months oldCritical — AI platforms may deprioritize
Evergreen Indicators

Some content remains relevant regardless of age. Flag content as evergreen if:

  • It covers fundamental concepts that do not change (physics, basic math, legal definitions)
  • It is clearly labeled as a reference/guide for lasting concepts
  • It does not contain time-dependent claims ("the latest", "currently", "in 2024")

Topical Authority Assessment

What It Is

Topical authority measures whether a site comprehensively covers a topic rather than touching on it superficially. AI platforms prefer citing sites that are recognized authorities on their topics.

How to Assess
  1. Content breadth: Does the site have multiple pages covering different aspects of its core topic?
  2. Content depth: Do individual pages go deep into subtopics?
  3. Topic clustering: Are pages organized into logical groups with internal linking?
  4. Content gaps: Are there obvious subtopics that the site should cover but does not?
  5. Competitor comparison: Do competitors cover subtopics that this site misses?
Scoring
LevelDescriptionScore Impact
Authority20+ pages covering topic comprehensively, strong clustering+10 bonus
Developing10-20 pages with some clustering+5 bonus
Emerging5-10 pages on topic, limited clustering+0
Thin< 5 pages, no clustering-5 penalty

Overall Scoring (0-100)

Score Composition
ComponentWeightMax Points
Experience25%25
Expertise25%25
Authoritativeness25%25
Trustworthiness25%25
Subtotal100
Topical Authority Modifier+10 to -5
Final ScoreCapped at 100
Score Interpretation
  • 85-100: Exceptional — strong AI citation candidate across platforms
  • 70-84: Good — solid foundation, specific improvements will increase citability
  • 55-69: Average — multiple E-E-A-T gaps reducing AI visibility
  • 40-54: Below Average — significant content quality and trust issues
  • 0-39: Poor — fundamental content strategy overhaul needed

Output Format

Generate GEO-CONTENT-ANALYSIS.md with:

markdown
# GEO Content Quality & E-E-A-T Analysis — [Domain]
Date: [Date]

## Content Score: XX/100

## E-E-A-T Breakdown
| Dimension | Score | Key Finding |
|---|---|---|
| Experience | XX/25 | [One-line summary] |
| Expertise | XX/25 | [One-line summary] |
| Authoritativeness | XX/25 | [One-line summary] |
| Trustworthiness | XX/25 | [One-line summary] |

## Topical Authority Modifier: [+10 to -5]

## Pages Analyzed
| Page | Word Count | Readability | Heading Structure | Citability Rating |
|---|---|---|---|---|
| [URL] | [Count] | [Score] | [Pass/Warn/Fail] | [High/Medium/Low] |

## E-E-A-T Detailed Findings

### Experience
[Specific passages and pages with strong/weak experience signals]

### Expertise
[Author credentials found, technical depth assessment, specific gaps]

### Authoritativeness
[External validation found, topical authority assessment, gaps]

### Trustworthiness
[Trust signals present/missing, accuracy concerns if any]

## Content Quality Issues
[Specific passages flagged with reasons and rewrite suggestions]

## AI Content Concerns
[Any low-quality AI content patterns detected, with specific examples]

## Freshness Assessment
| Page | Published | Last Updated | Status |
|---|---|---|---|
| [URL] | [Date] | [Date] | [Current/Stale/No Date] |

## Citability Assessment
### Most Citable Passages
[Top 5 passages that AI platforms are most likely to cite, with reasons]

### Least Citable Pages
[Pages with lowest citability, with specific improvement recommendations]

## Improvement Recommendations
### Quick Wins
[Specific content changes that can be made immediately]

### Content Gaps
[Topics the site should cover to strengthen topical authority]

### Author/E-E-A-T Improvements
[Specific steps to strengthen E-E-A-T signals]

© zubair-trabzada, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/geo-content of zubair-trabzada/geo-seo-claude.

Open the folder on GitHubat commit 989cae0

Used in 2 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in zubair-trabzada/geo-seo-claude, which our catalogue first saw on October 7, 2026.

Compare with similar skills

GEO Content E-E-A-T Scorer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

GEO Content E-E-A-T Scorer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
GEO Content E-E-A-T Scorer this skillzubair-trabzada/geo-seo-claude11k2 repos~4kAutomated safety check: NotesMIT
Content BriefRyze-AI-Adgent/open-seo-mcp-skills4.7k—~610Automated safety check: PassMIT
Geoyaojingang/GEOHub165—~364Automated safety check: PassAGPL-3.0
Geo Content Planningonvoyage-ai/gtm-engineer-skills1.3k—~1.9kAutomated safety check: PassMIT
Content Writeraaron-he-zhu/aaron-marketing-skills2.9k—~3.6kAutomated safety check: PassApache-2.0
Blog StrategyAgriciDaniel/claude-blog2.3k—~4.4kAutomated safety check: PassMIT

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Categories

Questions about GEO Content E-E-A-T Scorer

What does GEO Content E-E-A-T Scorer do?

Scores a page's content against Google's E-E-A-T framework and AI-citability structure, then writes a scored gap-analysis report. This skill fetches target pages, such as the homepage and key blog or product pages, and scores Experience, Expertise, Authoritativeness, and Trustworthiness at 25 points each against concrete signals like first-person accounts, original research, case studies with real numbers, and evidence such as screenshots, flagging weak experience such as hedging language or content that only summarizes other sources.

When should I use GEO Content E-E-A-T Scorer?

GEO Content E-E-A-T Scorer fits situations like: checking whether a page's content is likely to be cited by AI search; scoring a site's E-E-A-T signals before a content push; finding where content reads as generic rather than first-hand.

How do I install GEO Content E-E-A-T Scorer in Claude Code?

Run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-content -a claude-code`. Or copy the skill folder (skills/geo-content in zubair-trabzada/geo-seo-claude) into .claude/skills/geo-content in your project. Claude Code loads it when a task matches its description.

How do I install GEO Content E-E-A-T Scorer in Codex?

Run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-content -a codex`. Or copy the skill folder (skills/geo-content in zubair-trabzada/geo-seo-claude) into .agents/skills/geo-content in your project. Codex loads it when a task matches its description.

Can I use GEO Content E-E-A-T Scorer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zubair-trabzada/geo-seo-claude --skill geo-content -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/geo-content, .gemini/skills/geo-content, .github/skills/geo-content and .opencode/skills/geo-content in your project.

What does GEO Content E-E-A-T Scorer need to run?

SKILL.md names no scripts, command-line tools or credentials: GEO Content E-E-A-T Scorer is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash, WebFetch, Write.

Does GEO Content E-E-A-T Scorer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is GEO Content E-E-A-T Scorer safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does GEO Content E-E-A-T Scorer use?

GEO Content E-E-A-T Scorer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GEO Content E-E-A-T Scorer use?

About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to GEO Content E-E-A-T Scorer?

Skills that share tags, products or a category with GEO Content E-E-A-T Scorer: Content Brief (Ryze-AI-Adgent/open-seo-mcp-skills, 4.7k stars), Geo (yaojingang/GEOHub, 165 stars), Geo Content Planning (onvoyage-ai/gtm-engineer-skills, 1.3k stars) and Content Writer (aaron-he-zhu/aaron-marketing-skills, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GEO Content E-E-A-T Scorer?

zubair-trabzada (a GitHub user) maintains it in zubair-trabzada/geo-seo-claude, which has 10,982 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on October 10, 2026.

Source: zubair-trabzada/geo-seo-claude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.