---
name: "AEO GEO optimizer"
repo: https://github.com/thatrebeccarae/claude-marketing
source: https://github.com/thatrebeccarae/claude-marketing/blob/HEAD/skills/aeo-geo-optimizer/SKILL.md
license: "MIT"
install: "npx skills add thatrebeccarae/claude-marketing --skill aeo-geo-optimizer"
page: https://100xlab.com/resources/agent-skills/thatrebeccarae-claude-marketing--aeo-geo-optimizer--2wxgwe
---

# AEO/GEO Optimizer

Optimize content and websites for AI-powered search experiences — ChatGPT, Perplexity, Claude, Google AI Overviews, and Bing Copilot.

## Install

```bash
git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/aeo-geo-optimizer ~/.claude/skills/
```

## Why This Matters

Traditional SEO optimizes for 10 blue links. AEO/GEO optimizes for AI-generated answers. When someone asks ChatGPT or Perplexity a question, the answer synthesizes from sources — and those sources get cited, linked, and trusted. If your content is not structured for AI consumption, you are invisible in the fastest-growing search channel.

## Core Concepts

### AEO vs GEO vs Traditional SEO

| Dimension | Traditional SEO | AEO (Answer Engine) | GEO (Generative Engine) |
|-----------|----------------|---------------------|------------------------|
| **Target** | Google/Bing SERPs | Featured snippets, AI Overviews, voice assistants | ChatGPT, Perplexity, Claude citations |
| **Goal** | Rank on page 1 | Be THE answer | Be cited in AI-generated responses |
| **Content format** | Long-form, keyword-rich | Concise, structured Q&A | Authoritative, quotable, fact-dense |
| **Signals** | Backlinks, keywords, UX | Schema markup, direct answers, authority | E-E-A-T, data density, citation-worthiness |
| **Measurement** | Rankings, traffic | Answer box appearance, voice search hits | AI citation tracking, brand mentions in AI |

### The Citation Hierarchy

AI models prioritize sources based on:

1. **Authority signals** — Domain authority, author expertise, institutional backing
2. **Content structure** — Clear headings, direct answers, structured data
3. **Freshness** — Recent publication dates, updated statistics
4. **Specificity** — Exact numbers, named sources, verifiable claims
5. **Uniqueness** — Original research, proprietary data, novel frameworks

## AEO/GEO Audit Workflow

### Step 1: Assess Current AI Visibility

1. **Test AI citation presence**: Query ChatGPT, Perplexity, and Google AI Overviews with questions your content should answer. Document which queries cite your content vs competitors.

2. **Check structured data**: Validate schema markup coverage using Google Rich Results Test or Schema.org validator.

3. **Evaluate content structure**: Score each page on AEO readiness using the Content Scorecard below.

### Step 2: Content Scorecard

Rate each piece of content (1-5) on these dimensions:

| Dimension | Score 1 (Poor) | Score 5 (Excellent) |
|-----------|---------------|-------------------|
| **Direct answers** | Buried in paragraphs | Clear Q&A format, first-sentence answers |
| **Data density** | Opinions without evidence | Specific numbers, percentages, dates |
| **Source attribution** | No citations | Named sources, linked studies |
| **Structure** | Wall of text | H2/H3 hierarchy, lists, tables |
| **Schema markup** | None | Article, FAQ, HowTo, or relevant type |
| **Freshness signals** | No dates | Published date, "Updated" date, recent data |
| **Author authority** | No byline | Named author with expertise credentials |
| **Quotability** | Meandering prose | Crisp, self-contained statements AI can extract |

**Scoring**: 32-40 = AI-ready. 24-31 = Needs optimization. Below 24 = Major rework needed.

### Step 3: Optimize for AI Citation

#### Content Structure Patterns

**The Direct Answer Pattern:**
```
## [Question as H2]

[One-sentence direct answer.] [Supporting context in 2-3 sentences.]

**Key details:**
- [Specific data point]
- [Specific data point]
- [Source attribution]
```

**The Definition Pattern:**
```
## What Is [Term]?

[Term] is [clear, concise definition in one sentence]. [Elaboration with context.] [How it differs from related concepts.]
```

**The Comparison Pattern:**
```
## [X] vs [Y]: Key Differences

| Dimension | [X] | [Y] |
|-----------|-----|-----|
| [Aspect 1] | [Specific detail] | [Specific detail] |
| [Aspect 2] | [Specific detail] | [Specific detail] |

**Bottom line:** [One-sentence recommendation with reasoning.]
```

**The Statistics Pattern:**
```
## [Topic] Statistics ([Year])

- **[Stat 1]**: [Number] ([Source, Year])
- **[Stat 2]**: [Number] ([Source, Year])
- **[Stat 3]**: [Number] ([Source, Year])

*Sources: [List with links]*
```

#### Writing for AI Extraction

1. **Lead with the answer.** AI models extract the first sentence after a heading. Make it count.
2. **Use specific numbers.** "Revenue increased 47% year-over-year" beats "revenue increased significantly."
3. **Name your sources.** "According to a 2026 McKinsey report" is citable; unsourced claims are not.
4. **Create self-contained paragraphs.** Each paragraph should make sense extracted in isolation.
5. **Use comparison tables.** AI models love structured comparisons — they are easy to synthesize.
6. **Include "What is" and "How to" headings.** These directly match common AI queries.
7. **Add freshness signals.** Include publication date, last-updated date, and date-stamp your statistics.
8. **Write quotable sentences.** Crisp, declarative statements that AI can extract verbatim.

#### Technical Optimization

1. **Schema markup** — See the schema-markup-generator skill for implementation
2. **Canonical URLs** — Ensure AI models find the authoritative version
3. **XML sitemap** — Keep it current so AI crawlers find new content
4. **Page speed** — AI crawlers respect crawl budgets; fast sites get crawled more
5. **robots.txt** — Ensure AI crawlers (GPTBot, anthropic-ai, PerplexityBot) are not blocked

### Step 4: Monitor AI Visibility

#### AI Crawler User Agents

| Crawler | User Agent | Purpose |
|---------|-----------|---------|
| OpenAI | GPTBot | ChatGPT training and browsing |
| Anthropic | anthropic-ai, ClaudeBot | Claude training and citations |
| Perplexity | PerplexityBot | Perplexity search citations |
| Google | Google-Extended | Gemini/AI Overview training |
| Microsoft | Bingbot (+ AI signals) | Bing Copilot citations |
| Meta | Meta-ExternalAgent | Meta AI features |
| Apple | Applebot-Extended | Apple Intelligence |

#### robots.txt Recommendations

```
# Allow AI crawlers for maximum AI search visibility
User-agent: GPTBot
Allow: /

User-agent: anthropic-ai
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Google-Extended
Allow: /
```

**Decision framework:** If your goal is AI visibility (AEO/GEO), allow all AI crawlers. If you have licensing concerns about training data, selectively block training-only crawlers while allowing search/citation crawlers.

#### Measurement Approaches

| Method | What It Tracks | Tools |
|--------|---------------|-------|
| **Manual citation checks** | Query AI platforms, document citations | ChatGPT, Perplexity, Google |
| **Server log analysis** | AI crawler frequency and pages crawled | Log analyzers, custom scripts |
| **Brand mention monitoring** | Your brand/content mentioned in AI answers | Manual checks, brand monitoring tools |
| **Referral traffic** | Traffic from AI platforms | GA4 (check referral sources for chat.openai.com, perplexity.ai) |
| **Schema validation** | Structured data coverage and errors | Google Search Console, Rich Results Test |

## Content Types and AI Optimization

### Blog Posts / Articles
- Add FAQ schema for common questions
- Structure with clear H2 question headings
- Include "Key Takeaways" or "TL;DR" section
- Date-stamp all statistics

### Product / Service Pages
- Add Product or Service schema
- Include comparison tables vs alternatives
- Answer "What is [product]?" in first paragraph
- List specific features with quantified benefits

### Documentation / How-To Content
- Add HowTo schema with explicit steps
- Number every step
- Include time estimates and difficulty level
- Add "Prerequisites" and "Common Mistakes" sections

### Research / Data Content
- Add Dataset schema where applicable
- Lead with key findings before methodology
- Create a "Key Statistics" summary section
- Cite sample sizes, date ranges, and confidence levels

## Anti-Patterns (Never Do)

1. **Do not block AI crawlers** if your goal is AI visibility
2. **Do not write "click here" or "read more below"** — AI extracts content out of context
3. **Do not bury answers in long introductions** — lead with the answer
4. **Do not use vague qualifiers** — "many," "significant," "some" — use specific numbers
5. **Do not neglect author bylines** — E-E-A-T signals matter to AI models
6. **Do not duplicate content across pages** — AI models deduplicate and may ignore both
7. **Do not over-optimize for one AI platform** — optimize for all of them
8. **Do not forget internal linking** — AI crawlers follow links to build topical authority maps

## Integration with Other Skills

- **technical-seo-audit** — Run technical audit first, then layer AEO/GEO optimization
- **schema-markup-generator** — Generate the structured data this skill recommends
- **seo-content-writer** — Apply AEO writing patterns during content creation
- **content-creator** — Use brand voice analysis to maintain voice while optimizing for AI

---

## Supporting file: EXAMPLES.md

# AEO/GEO Optimizer — Examples

## Example 1: Full AEO/GEO Audit

### Prompt

> Audit our marketing blog for AI search visibility. We publish 3 articles per week about email marketing and want to appear in ChatGPT and Perplexity answers.

### What the skill does

1. **Assess current visibility**: Tests 10 target queries across ChatGPT, Perplexity, and Google AI Overviews. Documents which queries cite the blog vs competitors.

2. **Crawlability check**: Reviews robots.txt for AI crawler access. Finds GPTBot and PerplexityBot are blocked — flags as critical issue.

3. **Content scorecard**: Scores the 5 most recent articles using the AEO scoring rubric:
   - Article 1: 18/40 — no dates, no author byline, no schema
   - Article 2: 24/40 — has dates but answers buried in paragraph 3
   - Article 3: 21/40 — good structure but no statistics cited

4. **Produces prioritized recommendations**:
   - Critical: Unblock AI crawlers in robots.txt
   - High: Add Article + Person schema to all blog posts
   - High: Restructure content to lead with direct answers
   - Medium: Add FAQ sections with related questions
   - Medium: Date-stamp all statistics with sources

---

## Example 2: Optimize Existing Article for AI Citation

### Prompt

> Optimize this article about email deliverability best practices so it gets cited by AI search engines.

### What the skill does

1. **Scores current state**: Runs the Content Scorecard — scores 22/40
2. **Identifies specific issues**:
   - No direct answer in first paragraph (starts with background)
   - Statistics without sources ("studies show" instead of named studies)
   - No FAQ schema markup
   - H2 headings are topic-based, not question-based

3. **Rewrites key sections** following AEO patterns:
   - Adds "What is email deliverability?" H2 with one-sentence definition
   - Restructures "Best Practices" into numbered steps for HowTo schema
   - Adds comparison table: Good vs Poor deliverability signals
   - Creates FAQ section with 5 questions
   - Adds specific statistics with sources and dates

4. **Generates schema markup** (references schema-markup-generator skill)

---

## Example 3: Competitive AI Visibility Analysis

### Prompt

> Our competitor keeps getting cited in ChatGPT for email marketing questions. What are they doing that we are not?

### What the skill does

1. Queries 15 email marketing questions in ChatGPT and Perplexity
2. Documents which sources are cited for each query
3. Analyzes competitor content structure vs yours:
   - Competitor uses question-format H2s — you use topic-format
   - Competitor includes specific benchmarks with sources — you use general statements
   - Competitor has FAQ schema on every page — you have none
   - Competitor content is updated quarterly with fresh dates — yours has no update dates
4. Produces a gap analysis with specific remediation steps for each finding

---

## Supporting file: REFERENCE.md

# AEO/GEO Optimizer — Reference

## AI Platform Citation Behaviors

### ChatGPT (OpenAI)
- **Browsing mode**: Cites sources with links when browsing is enabled
- **Training cutoff**: Knowledge up to training date; browsing supplements
- **Citation style**: Inline links with source titles
- **Preferences**: Authoritative domains, recent content, structured data
- **Crawler**: GPTBot (respect robots.txt)

### Perplexity
- **Always cites**: Every response includes numbered source citations
- **Real-time search**: Fetches current web results for every query
- **Citation style**: Numbered footnotes with full URLs
- **Preferences**: Content that directly answers the query, recent publications
- **Crawler**: PerplexityBot

### Google AI Overviews
- **Integrated into SERPs**: Appears above organic results
- **Citation style**: Source cards with site name and favicon
- **Preferences**: E-E-A-T signals, schema markup, topical authority
- **Trigger**: Informational and "how-to" queries
- **Crawler**: Googlebot + Google-Extended for AI features

### Claude (Anthropic)
- **Tool use**: Can browse web when tools are available
- **Citation style**: Inline references to source content
- **Preferences**: Well-structured, authoritative, factual content
- **Crawler**: anthropic-ai, ClaudeBot

## Schema Markup for AI Visibility

### Priority Schema Types for AEO

| Content Type | Schema | AI Benefit |
|-------------|--------|-----------|
| Articles | Article, NewsArticle | Author credibility, publish date |
| How-tos | HowTo | Step extraction for procedural queries |
| FAQs | FAQPage | Direct Q&A matching |
| Products | Product | Feature/price comparison queries |
| Reviews | Review, AggregateRating | Trust signals |
| Data/Stats | Dataset | Factual citation preference |
| People | Person | Author expertise signals |
| Organizations | Organization | Brand authority |

### Recommended Schema Combinations

**Blog Post**: Article + Person (author) + BreadcrumbList + FAQPage (if FAQ section)

**Product Page**: Product + AggregateRating + FAQPage + BreadcrumbList

**How-To Guide**: HowTo + Article + Person + BreadcrumbList

## Content Optimization Checklists

### Article Optimization for AI Citation

- [ ] H1 contains the primary question/topic
- [ ] First paragraph directly answers the core question
- [ ] All statistics include source and year
- [ ] Author byline with credentials/expertise
- [ ] Published date and last-updated date visible
- [ ] FAQ section with 3-5 related questions
- [ ] Comparison table (if applicable)
- [ ] Key Takeaways / TL;DR section
- [ ] Article schema markup implemented
- [ ] Internal links to related authoritative content

### Page-Level AEO Checklist

- [ ] Title tag includes target question/topic (50-60 chars)
- [ ] Meta description answers the query concisely (150-160 chars)
- [ ] H2 headings use question format where natural
- [ ] Content is scannable (short paragraphs, lists, tables)
- [ ] Images have descriptive alt text
- [ ] Page loads in under 2.5 seconds (LCP)
- [ ] Mobile-responsive layout
- [ ] Canonical URL set correctly
- [ ] AI crawlers allowed in robots.txt

## Query Intent Mapping

| Intent Type | AI Behavior | Content Strategy |
|------------|-------------|-----------------|
| **Definitional** ("What is X?") | Extracts first clear definition | Lead H2 with definition, keep under 2 sentences |
| **Procedural** ("How to X") | Extracts numbered steps | Use HowTo schema, number every step |
| **Comparative** ("X vs Y") | Synthesizes from comparison content | Comparison tables, explicit pros/cons |
| **Statistical** ("How many X?") | Extracts specific numbers | Bold key stats, cite sources inline |
| **Evaluative** ("Best X for Y") | Aggregates recommendations | Clear criteria, ranked recommendations |
| **Explanatory** ("Why does X?") | Extracts causal reasoning | Direct cause-effect in first paragraph |

## Measurement Framework

### Tracking AI Citations

**Manual Process (Monthly):**
1. Compile your top 20 target queries
2. Ask each AI platform (ChatGPT, Perplexity, Google AI Overview)
3. Record: Was your content cited? Which competitor was cited instead?
4. Track month-over-month citation rate

**Automated Signals:**
- GA4 referral traffic from: `chat.openai.com`, `perplexity.ai`, `you.com`
- Server logs: crawl frequency from GPTBot, PerplexityBot, ClaudeBot
- Search Console: AI Overview impressions (where available)
- Brand monitoring: mentions in AI-generated content

### KPIs

| Metric | How to Measure | Target |
|--------|---------------|--------|
| AI citation rate | Manual query testing | >30% of target queries |
| AI referral traffic | GA4 referral report | Month-over-month growth |
| Crawl frequency | Server log analysis | Weekly crawls from AI bots |
| Schema coverage | Rich Results Test | 100% of eligible pages |
| Content score | AEO Scorecard (above) | >32/40 on key pages |