geo-content
geo-content is an code AI skill with a core value of Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
Quick Facts
mkdir -p ./skills/geo-content && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/geo-content/SKILL.md -o ./skills/geo-content/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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
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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:**
| Signal | Points | How to Score |
|---|---|---|
| First-person accounts ("I tested...", "We implemented...") | 5 | 5 if present and specific, 3 if generic, 0 if absent |
| Original research or data not available elsewhere | 5 | 5 if original data, 3 if references original work, 0 if none |
| Case studies with specific results | 4 | 4 if detailed with numbers, 2 if general, 0 if none |
| Screenshots, photos, or evidence of direct use | 3 | 3 if authentic evidence, 1 if stock/generic, 0 if none |
| Specific examples from personal experience | 4 | 4 if specific and unique, 2 if somewhat specific, 0 if generic |
| Demonstrations of process (not just outcome) | 4 | 4 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:**
| Signal | Points | How to Score |
|---|---|---|
| Author credentials visible (bio, degrees, certifications) | 5 | 5 if full credentials, 3 if basic bio, 0 if no author |
| Technical depth appropriate to topic | 5 | 5 if thorough technical treatment, 3 if adequate, 0 if superficial |
| Methodology explanation (how conclusions were reached) | 4 | 4 if clear methodology, 2 if some explanation, 0 if none |
| Data-backed claims (statistics, research citations) | 4 | 4 if well-sourced, 2 if some data, 0 if unsupported claims |
| Industry-specific terminology used correctly | 3 | 3 if accurate specialized language, 1 if basic, 0 if errors |
| Author page with detailed professional background | 4 | 4 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:**
| Signal | Points | How to Score |
|---|---|---|
| Inbound citations from authoritative sources | 5 | 5 if cited by major sources, 3 if some citations, 0 if none |
| Author quoted or cited in press/media | 4 | 4 if me
🎯 Best For
- Claude users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply geo-content to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is geo-content compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for geo-content?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install geo-content?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/geo-content/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.