Agent skill

geo-aeo-optimization

Optimize content for AI search engines (ChatGPT, Perplexity, Claude, Gemini) and featured snippets. Covers Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), E-E-A-T signals, and content structuring for maximum AI citation probability. Use when optimizing content for AI visibility or auditing AI search readiness.

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Install this agent skill to your Project

npx add-skill https://github.com/schwepps/skills/tree/main/geo-aeo-optimization

Metadata

Additional technical details for this skill

tags
geo, aeo, ai-search, chatgpt, perplexity, featured-snippets
author
Schwepps
version
1.0.0
category
marketing

SKILL.md

GEO & AEO Optimization Framework

Professional methodology for visibility in AI-powered search engines and generative AI responses.

Understanding GEO vs AEO vs SEO

SEO  → Rank in traditional search results (blue links)
AEO  → Appear in featured snippets, AI Overviews, voice answers
GEO  → Get cited in generative AI responses (ChatGPT, Claude, Perplexity)

2025 Reality:

  • 58% of queries are conversational
  • AI Overviews appear in ~47% of Google searches
  • Traditional CTR dropped 34.5% for top results due to AI answers
  • These strategies are complementary, not competing

When to Use This Skill

  • Optimizing content for AI search engines
  • Improving featured snippet capture rate
  • Auditing AI citation readiness
  • Restructuring content for AI extractability
  • Implementing E-E-A-T signals
  • Preparing for voice search

The Triple-Threat Framework

1. E-E-A-T Foundation (Required for All)

AI systems prioritize trusted, authoritative sources:

Experience   → First-hand knowledge, case studies, original research
Expertise    → Credentials, depth of knowledge, technical accuracy
Authority    → Citations, backlinks, mentions, brand recognition
Trustworthiness → Accuracy, transparency, clear sourcing

Implementation Checklist:

□ Author bio with credentials on every article
□ Link to authoritative sources
□ Include original data/research
□ Show methodology and sources
□ Update content regularly with visible dates
□ Display contact information
□ Include editorial guidelines

2. AEO: Featured Snippets & AI Overviews

Lead with the Answer:

  • First 40-60 words should directly answer the query
  • Use question-format H2 headers
  • Provide concise, extractable definitions

Content Structure for AEO:

markdown
## What is [Topic]?

[Direct answer in 1-2 sentences that can be extracted as a snippet]

[Supporting details and context follow]

Snippet-Optimized Formats:

Query Type Best Format
"What is X?" Definition paragraph (40-60 words)
"How to X" Numbered steps (5-8 steps)
"Best X" Bulleted list with brief descriptions
"X vs Y" Comparison table
"Why X?" Direct answer + explanation

3. GEO: AI Citation Optimization

The CRASP Framework:

C - Clarity    → Unambiguous statements AI can quote
R - Relevance  → Match conversational query intent
A - Authority  → Cited sources, expert credentials
S - Structure  → Scannable, extractable format
P - Precision  → Specific facts, numbers, dates

High-Citation Content Elements:

  1. TL;DR blocks at the top
  2. Statistics with sources ("According to [Source], X increased by Y%")
  3. Expert quotes with attribution
  4. Definition lists for key terms
  5. Comparison tables with clear data
  6. FAQ sections with complete answers

Content Structure Template

markdown
# [H1: Primary Question or Topic]

**TL;DR:** [2-3 sentence summary with key facts]

## What is [Topic]? {#definition}

[Direct definition in 40-60 words - optimized for extraction]

[Expanded explanation with context]

## How [Topic] Works {#how-it-works}

[Step-by-step explanation]

1. **Step One**: [Description]
2. **Step Two**: [Description]
3. **Step Three**: [Description]

## Key Statistics

| Metric | Value | Source |
|--------|-------|--------|
| [Stat 1] | [Value] | [Source, Year] |
| [Stat 2] | [Value] | [Source, Year] |

## [Topic] vs [Alternative]

| Factor | [Topic] | [Alternative] |
|--------|---------|---------------|
| [Factor 1] | [Value] | [Value] |
| [Factor 2] | [Value] | [Value] |

## Frequently Asked Questions

### [Question 1]?

[Complete, standalone answer - 50-100 words]

### [Question 2]?

[Complete, standalone answer - 50-100 words]

## Expert Insights

> "[Quotable statement with specific insight]"
> — [Expert Name], [Title], [Organization]

---
*Last updated: [Date] | Author: [Name], [Credentials]*

Fact-Density Checklist

Extractability:
□ TL;DR or summary present at top
□ Paragraphs <120 words each
□ Clear topic sentences (first sentence = main point)
□ Bullet lists for features/benefits
□ Tables for comparisons
□ FAQ section with schema

Fact-Density:
□ Statistics with sources cited
□ Specific numbers and dates
□ Verifiable data points
□ Expert quotes with attribution
□ Original research/data
□ Named entities (people, companies, places)

Structure for AI:
□ Question-based H2 headers
□ Direct answers in first 40-60 words
□ Logical information hierarchy
□ Schema markup (FAQPage, HowTo, Article)

AI Crawler Configuration

robots.txt for AI Search Visibility:

# ALLOW search/chat features
User-agent: OAI-SearchBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: ClaudeBot
Allow: /

# OPTIONAL: Block training (keeps search)
User-agent: GPTBot
Disallow: /

User-agent: Google-Extended
Disallow: /

Critical: Ensure server-side rendering. AI crawlers often don't execute JavaScript well.

Schema Markup for AI

Priority Schema Types:

  1. FAQPage - Highest AI citation impact
  2. HowTo - Step-by-step visibility
  3. Article + Author - E-E-A-T signals
  4. Organization - Brand authority

FAQPage Example:

json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "What is [topic]?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "[Complete answer that can be extracted]"
    }
  }]
}

Output Format

markdown
# GEO/AEO Audit Report

**Page:** [URL]
**Date:** [Date]
**Overall Score:** X/100

## Executive Summary
[2-3 sentence AI search readiness assessment]

## Scores by Category

| Category | Score | Status |
|----------|-------|--------|
| E-E-A-T Signals | X/25 | [Good/Needs Work/Critical] |
| Content Structure | X/20 | [Good/Needs Work/Critical] |
| Fact-Density | X/20 | [Good/Needs Work/Critical] |
| Extractability | X/20 | [Good/Needs Work/Critical] |
| AI Technical Readiness | X/15 | [Good/Needs Work/Critical] |

## Priority Issues
1. **[Issue]** - [Impact] - [Fix]
2. **[Issue]** - [Impact] - [Fix]
3. **[Issue]** - [Impact] - [Fix]

## AI Visibility Assessment
[Current citation probability and gaps]

## Action Plan

**Immediate:**
- [ ] Add TL;DR to top articles
- [ ] Implement FAQ schema

**Short-term:**
- [ ] Restructure headers as questions
- [ ] Add author credentials

**Ongoing:**
- [ ] Monitor AI platform citations
- [ ] Update content freshness

Quick Audit (5-Point Check)

  1. TL;DR - Summary present at top?
  2. Structure - Question-based headers?
  3. Facts - Statistics with sources?
  4. E-E-A-T - Author credentials visible?
  5. Schema - FAQPage/HowTo markup?

Scoring Guide

  • 90-100: Excellent - High AI citation probability
  • 70-89: Good - Likely cited with minor improvements
  • 50-69: Needs Work - Significant optimization needed
  • Below 50: Critical - Major restructuring required

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