superlines

AI Search Intelligence plugin for Cursor. Track brand visibility, citations, and share of voice across ChatGPT, Gemini, Perplexity, Claude, and 10+ AI platforms. Includes GEO skills, optimization rules, and MCP server integration with 26+ analytics tools.

Homepage Source

ai-search geo generative-engine-optimization seo brand-visibility mcp analytics chatgpt perplexity gemini

8 skills

llms-txt-creator

Create and maintain llms.txt files for AI crawlers. Use when setting up AI-friendly documentation indexes, creating machine-readable content maps, or helping websites become more discoverable by LLMs like ChatGPT, Perplexity, and Gemini.

# llms.txt Creator

Create standardized llms.txt files that help AI systems discover, understand, and cite your content accurately.

## What is llms.txt?

The llms.txt file is a standardized markdown document hosted at a website's root path (e.g., `https://example.com/llms.txt`). It serves as a curated index for LLMs, providing:

- Concise summaries of the site's purpose
- Critical contextual details about the brand/product
- Prioritized links to machine-readable resources

Think of it as the third layer next to existing files:
- `robots.txt` - explains what crawlers may access
- `sitemap.xml` - lists URLs for indexing
- `llms.txt` - tells LLMs which content is most important and where to find clean versions

## File Structure

Follow this standardized schema:

```markdown
# [Brand/Company Name]

> [One-sentence description of what the company/product does]

Key terms: [Important concepts, product names, technologies]

## [Section Name]

- [URL to markdown resource] — [Brief description]
- [URL to markdown resource] — [Brief description]

## Optional

- [URL to secondary resource] — [Brief description]
```

## When Creating llms.txt

### 1. Audit High-Value Content

Identify the pages that matter most for AI-driven questions:

- Core documentation and API references
- Pricing, plans, and usage rules
- Policies (returns, SLAs, compliance)
- Critical onboarding or integration guides

**Ask:** "If someone asked an AI about this topic, which pages should it read first?"

### 2. Create Clean Markdown Versions

llms.txt works best when linking to content that is:

- Free of navigation clutter and cookie banners
- Structured with headings, code blocks, and short paragraphs
- Focused on a single topic or task

For each priority page, consider creating a `.md` version at the same path (e.g., `/docs/api.md` alongside `/docs/api`).

### 3. Organize by Section

Standard sections include:

| Section | Purpose |
|---------|---------|
| **Docs** | Technical documentation, API references, tutorials |
| **Product** | Product descriptions, features, pricing |
| **Policies** | Terms, privacy, return policies, compliance |
| **Support** | FAQs, troubleshooting, contact information |
| **Optional** | Secondary content that can be skipped if context is limited |

### 4. Write Clear Descriptions

Each link should have a brief description (10-20 words) explaining:
- What the page contains
- When/why an AI should reference it

## Example: SaaS Company

```markdown
# Superlines

> AI Search Intelligence platform that helps brands track, optimize, and grow their visibility in AI Search across ChatGPT, Perplexity, Gemini, and Google AI Mode.

Key terms: GEO, Generative Engine Optimization, AI Search, Brand Visibility, Citation Rate, AI Share of Voice, MCP Server.

## Documentation

- https://docs.superlines.io/getting-started.md — Quick start guide for setting up tracking
- https://docs.superlines.io/api-reference.md — Complete API documentation with authentication
- https://docs.superlines.io/mcp-server.md — Model Context Protocol server setup

## Product

- https://superlines.io/features.md — Platform capabilities and use cases
- https://superlines.io/pricing.md — Current pricing tiers and features
- https://superlines.io/integrations.md — Available integrations and connectors

## Support

- https://docs.superlines.io/faq.md — Frequently asked questions
- https://docs.superlines.io/troubleshooting.md — Common issues and solutions

## Optional

- https://superlines.io/changelog.md — Product updates and release notes
- https://superlines.io/blog.md — Industry insights and tutorials
```

## Example: E-Commerce Company

```markdown
# Nike

> Global leader in athletic footwear, apparel, and innovation, committed to sustainability and performance-driven design.

Key terms: Air Max, Flyknit, Dri-FIT, Nike Membership, SNKRS app.

## Product Lines

- https://nike.com/products/running.md — Overview of running technologies
- https://nike.com/sustainability.md — 2025 targets, recycled materials

## Customer Support

- https://nike.com/returns.md — 60-day return window, exceptions
- https://nike.com/sizing.md — Region-specific size charts

## Optional

- https://nike.com/collaborations.md — Partnerships with athletes and designers
```

## Best Practices

1. **Keep it curated, not comprehensive** - Only include your most important pages
2. **Update when docs change** - Stale llms.txt reduces trust
3. **Use consistent terminology** - Match terms used in your actual content
4. **Test with LLMs** - Ask ChatGPT about your product and check if responses improve
5. **Link to clean markdown** - Avoid linking to pages heavy with JavaScript/navigation

## Common Mistakes to Avoid

- Listing every page on your site instead of curating
- Linking to noisy HTML full of layout code and ads
- Forgetting to update when documentation changes
- Using vague descriptions that don't help AI understand content purpose

## Validation Checklist

After creating llms.txt, verify:

- [ ] File is accessible at `https://yourdomain.com/llms.txt`
- [ ] H1 header contains brand/company name
- [ ] Blockquote provides clear one-sentence description
- [ ] Key terms include important concepts and product names
- [ ] All linked URLs are valid and return 200
- [ ] Linked content is clean, structured markdown
- [ ] Optional section exists for secondary content
- [ ] Descriptions are concise but informative

structured-data-generator

Generate JSON-LD schema markup for GEO optimization. Use when creating structured data for articles, products, FAQs, how-to guides, organizations, and other content types to improve AI search visibility and rich results.

# Structured Data Generator

Generate JSON-LD schema markup to help AI search engines understand and cite your content correctly.

## Why Schema Matters for GEO

Structured data helps AI systems:
- **Parse content accurately** - Understand what the page is about
- **Extract key facts** - Pull specific data points for answers
- **Attribute correctly** - Cite your brand as the source
- **Display rich results** - Enhanced visibility in search

## Schema Types for GEO

### Article Schema

Use for: Blog posts, news articles, guides, tutorials

```json
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Complete Guide to Generative Engine Optimization",
  "description": "Learn how to optimize content for AI search engines like ChatGPT, Perplexity, and Google AI Mode.",
  "image": "https://example.com/images/geo-guide.jpg",
  "author": {
    "@type": "Person",
    "name": "Author Name",
    "url": "https://example.com/authors/author-name",
    "jobTitle": "Content Strategist"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Company Name",
    "logo": {
      "@type": "ImageObject",
      "url": "https://example.com/logo.png",
      "width": 600,
      "height": 60
    }
  },
  "datePublished": "2024-01-15T08:00:00+00:00",
  "dateModified": "2024-03-20T10:30:00+00:00",
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://example.com/geo-guide"
  },
  "keywords": ["GEO", "AI Search", "Content Optimization"],
  "articleSection": "Marketing",
  "wordCount": 2500
}
```

**Required properties:**
- `headline` - Article title
- `author` - Author information
- `datePublished` - Original publish date
- `publisher` - Publishing organization

**Recommended properties:**
- `dateModified` - Last update date (critical for AI freshness signals)
- `description` - Article summary
- `image` - Featured image
- `keywords` - Relevant terms

### FAQPage Schema

Use for: FAQ sections, Q&A pages, help documentation

```json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Generative Engine Optimization (GEO)?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "GEO (Generative Engine Optimization) is the practice of optimizing content to be discovered, understood, and cited by AI search engines like ChatGPT, Perplexity, and Google AI Mode. It builds on traditional SEO by focusing on brand visibility, citation rate, and AI share of voice."
      }
    },
    {
      "@type": "Question",
      "name": "How does GEO differ from traditional SEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "While SEO focuses on ranking in search results and driving clicks, GEO focuses on being mentioned and cited inside AI-generated answers. GEO success is measured by brand visibility percentage, citation frequency, and share of voice in AI responses."
      }
    },
    {
      "@type": "Question",
      "name": "How often should content be updated for GEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "High-value pages should be refreshed every 60-90 days to maintain freshness signals. Update statistics, examples, and dates. AI engines prioritize recently updated content when generating answers."
      }
    }
  ]
}
```

**Required properties:**
- `mainEntity` - Array of Question objects
- Each Question needs `name` and `acceptedAnswer`

**Best practices:**
- Keep answers concise (40-200 words)
- Include the question keywords in the answer
- Make each answer standalone and quotable

### HowTo Schema

Use for: Tutorials, step-by-step guides, processes

```json
{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to Create an llms.txt File for AI Search",
  "description": "Step-by-step guide to creating an llms.txt file that helps AI crawlers discover and understand your content.",
  "image": "https://example.com/images/llms-txt-guide.jpg",
  "totalTime": "PT15M",
  "estimatedCost": {
    "@type": "MonetaryAmount",
    "currency": "USD",
    "value": "0"
  },
  "supply": [
    {
      "@type": "HowToSupply",
      "name": "Text editor"
    },
    {
      "@type": "HowToSupply",
      "name": "Web hosting access"
    }
  ],
  "tool": [
    {
      "@type": "HowToTool",
      "name": "Code editor (VS Code, Cursor)"
    }
  ],
  "step": [
    {
      "@type": "HowToStep",
      "name": "Audit your content",
      "text": "Identify your most important pages: documentation, pricing, policies, and key product pages.",
      "url": "https://example.com/llms-txt-guide#step1",
      "image": "https://example.com/images/step1.jpg"
    },
    {
      "@type": "HowToStep",
      "name": "Create the file structure",
      "text": "Create a new file named llms.txt at your domain root. Start with your brand name as H1 and a blockquote description.",
      "url": "https://example.com/llms-txt-guide#step2"
    },
    {
      "@type": "HowToStep",
      "name": "Add content sections",
      "text": "Organize links into sections like Docs, Product, Support, and Optional. Include brief descriptions for each link.",
      "url": "https://example.com/llms-txt-guide#step3"
    },
    {
      "@type": "HowToStep",
      "name": "Deploy and test",
      "text": "Upload the file and verify it's accessible at https://yourdomain.com/llms.txt. Test by asking AI assistants about your product.",
      "url": "https://example.com/llms-txt-guide#step4"
    }
  ]
}
```

**Required properties:**
- `name` - Title of the how-to
- `step` - Array of HowToStep objects

### Product Schema

Use for: Product pages, SaaS offerings, e-commerce

```json
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Superlines Analytics Platform",
  "description": "AI Search Intelligence platform that helps brands track, optimize, and grow their visibility in AI Search across ChatGPT, Perplexity, Gemini, and Google AI Mode.",
  "image": "https://superlines.io/images/product.jpg",
  "brand": {
    "@type": "Brand",
    "name": "Superlines"
  },
  "offers": {
    "@type": "AggregateOffer",
    "lowPrice": "99",
    "highPrice": "499",
    "priceCurrency": "EUR",
    "offerCount": "3",
    "offers": [
      {
        "@type": "Offer",
        "name": "Starter",
        "price": "99",
        "priceCurrency": "EUR",
        "priceValidUntil": "2025-12-31",
        "availability": "https://schema.org/InStock"
      },
      {
        "@type": "Offer",
        "name": "Professional",
        "price": "299",
        "priceCurrency": "EUR",
        "priceValidUntil": "2025-12-31",
        "availability": "https://schema.org/InStock"
      },
      {
        "@type": "Offer",
        "name": "Enterprise",
        "price": "499",
        "priceCurrency": "EUR",
        "priceValidUntil": "2025-12-31",
        "availability": "https://schema.org/InStock"
      }
    ]
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "reviewCount": "127"
  }
}
```

### Organization Schema

Use for: Company pages, about pages, homepage

```json
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Superlines",
  "alternateName": "Superlines.io",
  "url": "https://superlines.io",
  "logo": "https://superlines.io/logo.png",
  "description": "AI Search Intelligence platform for enterprises and agencies.",
  "foundingDate": "2023",
  "founders": [
    {
      "@type": "Person",
      "name": "Founder Name"
    }
  ],
  "address": {
    "@type": "PostalAddress",
    "addressLocality": "Helsinki",
    "addressCountry": "FI"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer service",
    "url": "https://superlines.io/contact"
  },
  "sameAs": [
    "https://www.linkedin.com/company/superlines",
    "https://twitter.com/superlines"
  ]
}
```

### BreadcrumbList Schema

Use for: Navigation paths on any page

```json
{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://example.com"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Articles",
      "item": "https://example.com/articles"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "GEO Guide",
      "item": "https://example.com/articles/geo-guide"
    }
  ]
}
```

## Implementation Guide

### HTML Placement

Place JSON-LD in the `<head>` section:

```html
<head>
  <title>Page Title</title>
  <meta name="description" content="...">
  
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "Article",
    ...
  }
  </script>
</head>
```

### Multiple Schema Types

You can include multiple schema types on one page:

```html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "name": "Company Name",
      ...
    },
    {
      "@type": "WebPage",
      "name": "Page Title",
      ...
    },
    {
      "@type": "Article",
      "headline": "Article Title",
      ...
    }
  ]
}
</script>
```

## Validation Checklist

Before deploying schema markup:

- [ ] JSON syntax is valid (no trailing commas, proper quotes)
- [ ] All required properties are present
- [ ] URLs are absolute (include https://)
- [ ] Dates use ISO 8601 format (2024-01-15T08:00:00+00:00)
- [ ] Text values are properly escaped
- [ ] Images are valid URLs and accessible
- [ ] Schema type matches content type
- [ ] No duplicate conflicting schema on same page

## Testing Tools

1. **Google Rich Results Test** - https://search.google.com/test/rich-results
2. **Schema.org Validator** - https://validator.schema.org/
3. **JSON-LD Playground** - https://json-ld.org/playground/

## Quick Reference Table

| Content Type | Schema | Key Properties |
|--------------|--------|----------------|
| Blog/Article | Article | headline, author, datePublished, dateModified |
| FAQ | FAQPage | mainEntity (Questions with Answers) |
| Tutorial | HowTo | name, step (HowToSteps) |
| Product | Product | name, offers, brand |
| Company | Organization | name, url, logo, description |
| Navigation | BreadcrumbList | itemListElement (ListItems) |
| Person | Person | name, jobTitle, url |
| Service | Service | name, provider, description |

faq-schema-creator

Create FAQ content and JSON-LD schema markup optimized for AI search. Use when building FAQ sections, help documentation, or Q&A content that should be easily extracted and cited by AI assistants.

# FAQ Schema Creator

Create FAQ content and structured data that AI search engines can easily extract, understand, and cite in their answers.

## Why FAQs Matter for GEO

FAQs are one of the most effective content formats for AI search visibility:

1. **Question-answer format** - Matches how users query AI assistants
2. **Highly extractable** - Each Q&A can be quoted standalone
3. **Schema support** - FAQPage schema helps AI parse content
4. **Multiple keywords** - Each question targets different search intents

## FAQ Content Structure

### Writing Effective Questions

**Good questions:**
- Start with "What", "How", "Why", "When", "Can", "Does"
- Match actual user search queries
- Are specific enough to have clear answers
- Include relevant keywords naturally

**Examples:**
```markdown
# Good
What is Generative Engine Optimization (GEO)?
How does GEO differ from traditional SEO?
How often should I update content for AI search?

# Bad (too vague or not searchable)
Tell me about optimization
What's the deal with AI?
Can you explain more?
```

### Writing Effective Answers

Follow these guidelines for AI-friendly answers:

1. **Answer immediately** - First sentence should directly answer the question
2. **Keep it concise** - 40-200 words per answer
3. **Make it standalone** - Each answer should make sense without context
4. **Include key terms** - Echo question keywords in the answer
5. **Be specific** - Use concrete details, numbers, examples

**Answer template:**
```markdown
### [Question]?

[Direct answer in 1-2 sentences]. [Supporting detail or context]. 
[Example or specific recommendation if relevant].
```

**Example:**
```markdown
### What is Generative Engine Optimization (GEO)?

GEO (Generative Engine Optimization) is the practice of optimizing 
content to be discovered and cited by AI search engines like ChatGPT, 
Perplexity, and Google AI Mode. Unlike traditional SEO which focuses 
on search rankings, GEO focuses on brand visibility, citation rate, 
and share of voice inside AI-generated answers.
```

## FAQ Categories

Organize FAQs by topic for better structure:

### Product/Service FAQs
```markdown
## Product Questions

### What does [Product] do?
[Clear description of core functionality]

### How much does [Product] cost?
[Pricing information with tiers if applicable]

### What platforms/integrations are supported?
[List of compatible platforms]
```

### How-To FAQs
```markdown
## Getting Started

### How do I sign up for [Product]?
[Step-by-step signup process]

### How do I configure [Feature]?
[Configuration instructions]

### How long does setup take?
[Time estimate with context]
```

### Comparison FAQs
```markdown
## Comparisons

### How does [Product] compare to [Competitor]?
[Objective comparison highlighting differences]

### What makes [Product] different?
[Unique value propositions]

### Is [Product] better for [use case] or [use case]?
[Use case recommendations]
```

### Troubleshooting FAQs
```markdown
## Troubleshooting

### Why isn't [Feature] working?
[Common causes and solutions]

### How do I fix [Error]?
[Step-by-step resolution]

### Who do I contact for support?
[Support channels and response times]
```

## FAQPage Schema

### Basic FAQPage Schema

```json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Generative Engine Optimization (GEO)?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "GEO (Generative Engine Optimization) is the practice of optimizing content to be discovered and cited by AI search engines like ChatGPT, Perplexity, and Google AI Mode. Unlike traditional SEO which focuses on search rankings, GEO focuses on brand visibility, citation rate, and share of voice inside AI-generated answers."
      }
    },
    {
      "@type": "Question",
      "name": "How does GEO differ from traditional SEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "While SEO focuses on ranking pages in search results and driving clicks, GEO focuses on being mentioned and cited inside AI-generated answers. Key GEO metrics include brand visibility percentage, citation frequency, AI share of voice, and context accuracy."
      }
    },
    {
      "@type": "Question",
      "name": "How often should content be updated for GEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "High-value pages should be refreshed every 60-90 days to maintain freshness signals. Update statistics, examples, and publication dates. AI engines prioritize recently updated content when generating answers."
      }
    }
  ]
}
```

### Enhanced FAQ Schema with Rich Content

```json
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "name": "Generative Engine Optimization FAQ",
  "description": "Frequently asked questions about GEO and AI search optimization",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What are the key metrics for measuring GEO success?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "The key GEO metrics are: 1) Brand Visibility - percentage of AI answers mentioning your brand, 2) Citation Rate - how often AI cites your content as a source, 3) AI Share of Voice - your mentions compared to competitors, 4) Context Accuracy - whether AI describes your brand correctly. Most companies target 20-30% brand visibility on non-branded category queries as a first-year goal."
      }
    }
  ]
}
```

## Complete FAQ Page Template

### HTML Structure

```html
<!DOCTYPE html>
<html lang="en">
<head>
  <title>FAQ - [Topic] | [Brand]</title>
  <meta name="description" content="Frequently asked questions about [topic]. Get answers to common questions about [specific areas].">
  
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "FAQPage",
    "mainEntity": [
      // FAQ items here
    ]
  }
  </script>
</head>
<body>
  <main>
    <h1>Frequently Asked Questions</h1>
    
    <section>
      <h2>Getting Started</h2>
      
      <article>
        <h3>What is [Product]?</h3>
        <p>[Answer]</p>
      </article>
      
      <article>
        <h3>How do I get started?</h3>
        <p>[Answer]</p>
      </article>
    </section>
    
    <section>
      <h2>Pricing & Plans</h2>
      
      <article>
        <h3>How much does [Product] cost?</h3>
        <p>[Answer]</p>
      </article>
    </section>
  </main>
</body>
</html>
```

### Markdown Structure

```markdown
# Frequently Asked Questions

## Getting Started

### What is [Product]?

[Product] is [clear one-sentence description]. It helps [target user] 
to [primary benefit]. Key features include [feature 1], [feature 2], 
and [feature 3].

### How do I get started with [Product]?

Getting started takes about [time estimate]. First, [step 1]. Then, 
[step 2]. Finally, [step 3]. You can find detailed setup instructions 
in our [documentation link].

## Pricing & Plans

### How much does [Product] cost?

[Product] offers [number] pricing tiers:
- **Starter:** $X/month - [key features]
- **Professional:** $X/month - [key features]  
- **Enterprise:** Custom pricing - [key features]

All plans include [common features]. See our [pricing page] for details.

### Is there a free trial?

Yes, [Product] offers a [duration] free trial with access to [features]. 
No credit card required to start. [CTA or link].

## Technical Questions

### What integrations are supported?

[Product] integrates with [platform 1], [platform 2], and [platform 3]. 
We also offer a REST API for custom integrations. See our [integrations page] 
for the complete list.
```

## FAQ Best Practices Checklist

### Content Quality
- [ ] Each question matches real user search queries
- [ ] Answers start with a direct response
- [ ] Answers are 40-200 words (concise but complete)
- [ ] Each answer is standalone (makes sense without context)
- [ ] Key terms from questions appear in answers
- [ ] Specific details included (numbers, examples, timelines)

### Structure
- [ ] FAQs grouped by logical categories
- [ ] Most important/common questions first
- [ ] Proper heading hierarchy (H2 for categories, H3 for questions)
- [ ] Clear, consistent formatting throughout

### Schema
- [ ] FAQPage schema is present and valid
- [ ] Question text matches visible heading exactly
- [ ] Answer text matches visible content
- [ ] JSON-LD syntax is valid (no errors)
- [ ] Schema is placed in `<head>` section

### Optimization
- [ ] Meta description summarizes FAQ topic
- [ ] Page title includes "FAQ" or "Questions"
- [ ] Internal links to relevant pages where appropriate
- [ ] Updated date visible on page

## Common FAQ Topics by Industry

### SaaS/Software
- What does [product] do?
- How much does it cost?
- What integrations are available?
- How do I get started?
- What's the difference between plans?
- Is there a free trial?
- How do I cancel my subscription?

### E-Commerce
- How long does shipping take?
- What is your return policy?
- Do you ship internationally?
- How do I track my order?
- What payment methods do you accept?
- Are prices in my local currency?

### Service Business
- What services do you offer?
- What areas do you serve?
- How do I schedule an appointment?
- What are your hours?
- How much do you charge?
- Do you offer consultations?

### Documentation/Technical
- How do I install [product]?
- What are the system requirements?
- How do I authenticate?
- What's the API rate limit?
- Where can I find examples?
- How do I report bugs?

geo-checklist-auditor

Audit pages against the GEO best practices checklist. Use when reviewing content for AI search readiness, ensuring pages follow Generative Engine Optimization principles, or preparing content for better visibility in ChatGPT, Perplexity, and Google AI Mode.

# GEO Checklist Auditor

Audit web pages against the comprehensive GEO (Generative Engine Optimization) best practices checklist to ensure optimal visibility in AI search engines.

## The 10-Point GEO Audit Checklist

Use this checklist as a comprehensive pass before publishing or updating any high-value page.

### 1. AI Search Visibility Baseline

**What to check:**
- Has the page topic been tested in AI assistants?
- Which brands currently appear for related queries?
- What sources are being cited?

**Audit actions:**
- [ ] Test 3-5 relevant prompts in ChatGPT
- [ ] Test same prompts in Perplexity
- [ ] Test in Google AI Mode if available
- [ ] Document which competitors are mentioned
- [ ] Note which sources are cited

**Questions to ask AI:**
```
"What are the best [your category]?"
"How does [your product type] work?"
"[Your product] vs [competitor] comparison"
"What companies offer [your service]?"
```

### 2. Prompt-to-Intent Mapping

**What to check:**
- Does content address real user prompts?
- Are all funnel stages covered?
- Do headings match query patterns?

**Audit criteria:**
- [ ] Awareness prompts addressed (what is X, how does X work)
- [ ] Consideration prompts addressed (best X for Y, X vs Z)
- [ ] Decision prompts addressed (X pricing, X review, buy X)
- [ ] H2 headings match real question patterns
- [ ] Content covers query fan-out variations

**Funnel mapping table:**

| Stage | Prompt Pattern | Page Addresses? |
|-------|---------------|-----------------|
| Awareness | "What is [topic]?" | ☐ Yes ☐ No |
| Awareness | "How does [topic] work?" | ☐ Yes ☐ No |
| Consideration | "Best [category] for [use case]" | ☐ Yes ☐ No |
| Consideration | "[Product A] vs [Product B]" | ☐ Yes ☐ No |
| Decision | "[Product] pricing" | ☐ Yes ☐ No |
| Decision | "[Product] reviews" | ☐ Yes ☐ No |

### 3. Cornerstone Content Quality

**What to check:**
- Is content authoritative and comprehensive?
- Are claims supported by evidence?
- Is expertise demonstrated?

**Audit criteria:**
- [ ] Content length appropriate (1,500+ words for guides)
- [ ] Clear definitions provided for key terms
- [ ] Real examples and case studies included
- [ ] Data/statistics from credible sources
- [ ] Expert quotes or citations where relevant
- [ ] Author credentials visible
- [ ] Original insights not found elsewhere

**Quality indicators:**
| Element | Present? | Quality (1-5) |
|---------|----------|---------------|
| Definitions | ☐ | ___ |
| Examples | ☐ | ___ |
| Data/Statistics | ☐ | ___ |
| Expert quotes | ☐ | ___ |
| Original research | ☐ | ___ |

### 4. Extractability and Structure

**What to check:**
- Can AI easily extract key information?
- Is content structured for machine reading?
- Does formatting support quotability?

**Audit criteria:**

**Page structure:**
- [ ] Clear H1 matching primary intent
- [ ] Logical H2/H3 hierarchy
- [ ] TL;DR or summary section at top
- [ ] Key takeaways section
- [ ] FAQ section with common questions

**Content formatting:**
- [ ] Short paragraphs (3-4 sentences max)
- [ ] Bullet lists for features/benefits
- [ ] Numbered lists for steps/processes
- [ ] Tables for comparisons/specifications
- [ ] Each paragraph is quotable standalone

**Technical extractability:**
- [ ] Page loads in < 0.4 seconds (FCP target)
- [ ] Content in initial HTML (not JS-rendered)
- [ ] Clean semantic HTML structure

### 5. Schema and Metadata

**What to check:**
- Is appropriate schema markup present?
- Are meta tags optimized?
- Is structured data valid?

**Schema audit:**
- [ ] Schema type matches content (Article, FAQPage, HowTo, Product)
- [ ] Required properties populated
- [ ] dateModified reflects actual last update
- [ ] JSON-LD syntax is valid
- [ ] No conflicting schema on page

**Metadata audit:**
- [ ] Title is descriptive (< 60 characters)
- [ ] Meta description summarizes content (150-160 chars)
- [ ] Canonical URL is correct
- [ ] Open Graph tags present
- [ ] Language declared

**Schema checklist by content type:**

| Content Type | Required Schema | Present? | Valid? |
|--------------|-----------------|----------|--------|
| Article/Blog | Article | ☐ | ☐ |
| FAQ page | FAQPage | ☐ | ☐ |
| Tutorial | HowTo | ☐ | ☐ |
| Product page | Product | ☐ | ☐ |
| Company page | Organization | ☐ | ☐ |

### 6. Web-Wide Footprint

**What to check:**
- Does brand appear on third-party sources?
- Are key directories and platforms covered?
- Is information consistent across sources?

**Third-party presence audit:**
- [ ] Wikipedia/Wikidata (if notable)
- [ ] Industry directories
- [ ] Review sites (G2, Capterra, Trustpilot)
- [ ] LinkedIn company page
- [ ] Relevant Reddit communities
- [ ] YouTube presence
- [ ] Industry forums/communities

**Consistency check:**
- [ ] Company description consistent across platforms
- [ ] Product information matches website
- [ ] Pricing is current everywhere
- [ ] Contact information is accurate

### 7. Brand Authority and Engagement

**What to check:**
- Is content publishing consistent?
- Are there quality backlinks?
- Is brand being discussed?

**Authority indicators:**
- [ ] Regular content publishing cadence
- [ ] Quality external links to content
- [ ] Media mentions/press coverage
- [ ] Customer reviews and testimonials
- [ ] Social engagement on content
- [ ] Industry awards or recognition

### 8. GEO Metrics Tracking

**What to check:**
- Are AI visibility metrics being tracked?
- Can improvements be measured?

**Metrics to establish:**
- [ ] Brand Visibility baseline (% of answers mentioning brand)
- [ ] Citation Rate baseline (% of answers citing domain)
- [ ] AI Share of Voice vs competitors
- [ ] Human vs bot traffic tracked
- [ ] AI referral traffic identified

### 9. Content Freshness

**What to check:**
- Is content regularly updated?
- Are dates accurate and visible?

**Freshness audit:**
- [ ] Last update date is visible
- [ ] Statistics are current (< 12 months old)
- [ ] Examples are relevant and recent
- [ ] Links are working (no 404s)
- [ ] Product information is accurate
- [ ] Pricing is current

**Recommended refresh cadence:**

| Content Type | Refresh Every |
|--------------|---------------|
| Product pages | Monthly |
| Pricing pages | Monthly |
| Industry guides | 60-90 days |
| Blog posts with data | Quarterly |
| Documentation | When features change |
| Evergreen content | 6 months |

### 10. Common GEO Mistakes Check

**Verify the page avoids these issues:**
- [ ] NOT relying on thin content (< 500 words for important pages)
- [ ] NOT keyword stuffing unnaturally
- [ ] NOT using only one distribution channel
- [ ] NOT measuring only Google metrics
- [ ] NOT ignoring AI bot access in robots.txt
- [ ] NOT using JavaScript-only content rendering
- [ ] NOT having slow page load times
- [ ] NOT missing schema markup
- [ ] NOT having inconsistent brand information
- [ ] NOT neglecting third-party presence

## Audit Scoring

### Calculate Overall GEO Score

| Section | Max Points | Score |
|---------|------------|-------|
| 1. Visibility Baseline | 10 | ___ |
| 2. Prompt Mapping | 10 | ___ |
| 3. Content Quality | 10 | ___ |
| 4. Extractability | 10 | ___ |
| 5. Schema/Metadata | 10 | ___ |
| 6. Web-Wide Footprint | 10 | ___ |
| 7. Brand Authority | 10 | ___ |
| 8. Metrics Tracking | 10 | ___ |
| 9. Content Freshness | 10 | ___ |
| 10. Mistakes Avoided | 10 | ___ |
| **Total** | **100** | **___** |

### Score Interpretation

| Score | Rating | Action |
|-------|--------|--------|
| 90-100 | Excellent | Maintain and monitor |
| 75-89 | Good | Minor optimizations needed |
| 60-74 | Fair | Significant improvements needed |
| 40-59 | Poor | Major restructuring required |
| < 40 | Critical | Full content overhaul needed |

## Audit Report Template

```markdown
# GEO Audit Report

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

## Executive Summary
[2-3 sentence summary of findings]

## Critical Issues (Fix Immediately)
1. [Issue with impact]
2. [Issue with impact]

## High Priority (Fix This Week)
1. [Issue with recommendation]
2. [Issue with recommendation]

## Medium Priority (Fix This Month)
1. [Issue with recommendation]
2. [Issue with recommendation]

## Strengths
- [What's working well]
- [What's working well]

## Recommendations
1. [Specific actionable recommendation]
2. [Specific actionable recommendation]
3. [Specific actionable recommendation]

## Next Review Date
[Date for follow-up audit]
```

## Quick Audit Checklist

For fast assessments, use this condensed checklist:

- [ ] **Structure:** H1 matches intent, logical H2/H3 hierarchy
- [ ] **Answer First:** Main point in first 1-2 sentences
- [ ] **TL;DR:** Summary section at page top
- [ ] **FAQ:** Common questions addressed
- [ ] **Schema:** Appropriate type, valid syntax
- [ ] **Speed:** Page loads under 0.4s FCP
- [ ] **Freshness:** Updated within 90 days
- [ ] **Entities:** Consistent terminology throughout
- [ ] **Evidence:** Claims backed by data/sources
- [ ] **Quotability:** Each paragraph stands alone

geo-content-optimizer

Optimize existing content for better AI search visibility using GEO (Generative Engine Optimization) best practices. Use when improving articles, documentation, or web pages to increase citations and brand mentions in AI-generated answers.

# GEO Content Optimizer

Analyze and optimize existing content to improve visibility and citation rates in AI search engines like ChatGPT, Perplexity, Gemini, and Google AI Mode.

## What is GEO?

**Generative Engine Optimization (GEO)** is the AI-era evolution of SEO. While traditional SEO focuses on ranking in search results, GEO focuses on:

- Being **cited** in AI-generated answers
- **Brand visibility** inside AI assistant responses  
- **AI Share of Voice** compared to competitors
- **Context accuracy** - ensuring AI describes your brand correctly

## Optimization Process

### Step 1: Analyze Current Structure

Evaluate the content against these structural requirements:

**Check for:**
- [ ] Clear H1 that matches search intent
- [ ] Logical H2/H3 hierarchy
- [ ] TL;DR or summary section at the top
- [ ] Question-based headings where appropriate
- [ ] FAQ section for common questions
- [ ] Scannable formatting (lists, tables, short paragraphs)

**Identify issues:**
- Long introductions before the main point
- Missing or unclear heading structure
- Walls of text without formatting
- Buried key information

### Step 2: Apply the "Answer First" Pattern

Transform content to lead with answers:

**Before (SEO-style):**
```markdown
## Understanding API Authentication

In the modern digital landscape, API security has become 
increasingly important. There are several methods...

[500 words later]

API keys are strings used to authenticate requests.
```

**After (GEO-optimized):**
```markdown
## What is API Authentication?

API authentication is the process of verifying the identity 
of clients making API requests. The most common method is 
API keys—unique strings passed in request headers.

### How API Keys Work

[Details and examples]
```

### Step 3: Enhance Extractability

Make content easy for AI to extract and quote:

#### Add TL;DR Sections

Place at the beginning of articles:

```markdown
> **TL;DR:** [Main point in 1-2 sentences]. [Key supporting 
> detail]. [What the reader will learn/gain].
```

#### Convert to Structured Formats

| Original | Optimized |
|----------|-----------|
| Long paragraphs listing features | Bullet list of features |
| Narrative comparisons | Comparison tables |
| Step descriptions in prose | Numbered step lists |
| Inline definitions | Definition lists or callout boxes |

#### Add FAQ Blocks

Convert common questions buried in content into explicit FAQ format:

```markdown
## Frequently Asked Questions

### How long does setup take?
Setup typically takes 5-10 minutes for basic configuration.

### What integrations are supported?
We support integrations with Slack, GitHub, and Zapier.
```

### Step 4: Strengthen Entity Clarity

Ensure clear, consistent entity references:

**Check for:**
- Company/product name used consistently
- Key concepts defined on first use
- Related entities mentioned naturally
- Clear subject-verb relationships

**Fix:**
- Replace vague pronouns with specific nouns
- Define acronyms on first use: "GEO (Generative Engine Optimization)"
- Keep terminology consistent throughout

### Step 5: Add Schema Markup Recommendations

Identify appropriate schema types for the content:

| Content Type | Recommended Schema |
|--------------|-------------------|
| How-to guides | HowTo |
| FAQ pages | FAQPage |
| Product pages | Product |
| Articles/blogs | Article |
| Company info | Organization |
| Service descriptions | Service |

### Step 6: Optimize for Query Fan-Out

AI systems expand user questions into multiple sub-queries. Ensure content addresses these patterns:

**Primary query:** "best project management tools"

**Fan-out queries the content should address:**
- "project management software features"
- "project management tool pricing comparison"
- "project management for remote teams"
- "Asana vs Monday vs Trello"

**Optimization actions:**
- Add H2s targeting fan-out variations
- Include comparison tables for "vs" queries
- Address specific use cases (remote teams, agencies, etc.)

## Content Audit Checklist

Run through this checklist when optimizing:

### Structure (Score: /10)
- [ ] Clear, descriptive H1 (1 point)
- [ ] Logical H2/H3 hierarchy (2 points)
- [ ] TL;DR or summary at top (2 points)
- [ ] Question-based headings (2 points)
- [ ] FAQ section (2 points)
- [ ] Short paragraphs (1 point)

### Extractability (Score: /10)
- [ ] First paragraph answers main question (2 points)
- [ ] Key information in lists/tables (2 points)
- [ ] Each paragraph is quotable standalone (2 points)
- [ ] Clear definitions for key terms (2 points)
- [ ] Evidence/data to support claims (2 points)

### Entity Clarity (Score: /10)
- [ ] Consistent terminology throughout (2 points)
- [ ] Acronyms defined on first use (2 points)
- [ ] Clear pronoun references (2 points)
- [ ] Brand/product name used correctly (2 points)
- [ ] Related concepts mentioned naturally (2 points)

### Technical Readiness (Score: /10)
- [ ] Schema markup appropriate for content type (3 points)
- [ ] Meta description is clear and accurate (2 points)
- [ ] Page loads quickly (2 points)
- [ ] Mobile-friendly formatting (2 points)
- [ ] Clean URL structure (1 point)

**Target Score:** 32/40 or higher for GEO-optimized content

## Common Optimization Patterns

### Pattern 1: Definition Enhancement

**Before:**
> "GEO is important for modern marketing."

**After:**
> "Generative Engine Optimization (GEO) is the practice of optimizing content to be cited in AI-generated answers. It extends traditional SEO by focusing on how AI assistants like ChatGPT and Perplexity discover, understand, and reference your content."

### Pattern 2: Comparison Table Addition

**Before:**
> "Product A is faster but Product B has more features. Product C is the most affordable option."

**After:**

| Product | Speed | Features | Price |
|---------|-------|----------|-------|
| Product A | Fast | Basic | $99/mo |
| Product B | Medium | Advanced | $149/mo |
| Product C | Medium | Basic | $49/mo |

### Pattern 3: Process Clarification

**Before:**
> "First you need to sign up, then configure your settings, and finally you can start using the platform."

**After:**
> **Getting Started (3 Steps)**
> 1. **Sign up** - Create your account at example.com/signup
> 2. **Configure settings** - Set your preferences in the dashboard
> 3. **Start using** - Begin tracking your first project

## Refresh Cadence

For optimal AI search visibility, refresh high-value content:

| Content Type | Refresh Frequency |
|--------------|-------------------|
| Product/pricing pages | Monthly |
| Industry guides | Every 60-90 days |
| Documentation | When features change |
| Blog posts with data | Quarterly |
| Evergreen content | Every 6 months |

**Refresh actions:**
- Update statistics and dates
- Add new examples or case studies
- Expand FAQ sections based on new questions
- Strengthen internal linking
- Update schema markup

ai-friendly-content-writer

Write content optimized for AI search engines using the 12 Principles of AI-Friendly Writing. Use when creating articles, documentation, or marketing content that needs to be easily understood and cited by LLMs like ChatGPT, Perplexity, and Gemini.

# AI-Friendly Content Writer

Create content that is easily understood, extracted, and cited by AI search engines while remaining engaging for human readers.

## The 12 Principles of AI-Friendly Writing

AI-friendly content means writing so clearly that both humans and machines can follow your thinking. Apply these principles to every piece of content.

### 1. Don't Bury the Point (BLUF - Bottom Line Up Front)

Start with the main takeaway, then explain it. When you open a section, give the answer in the first one or two sentences, then add context and proof.

**Bad:**
> "In today's fast-paced digital landscape, businesses are constantly looking for ways to improve visibility and stay competitive. One of the most effective ways to do that is through optimizing content for AI-driven search engines."

**Good:**
> "To rank in AI Search, start your article with the answer, not the setup. AI engines (and readers) both reward clarity over buildup."

### 2. Ask a Question, Answer It Immediately

If your heading is a question, the first sentence under it should contain a direct answer in plain language.

**Bad:**
> **What is AI-friendly writing?**
> Before we define it, let's talk about how writing itself has evolved with the rise of large language models...

**Good:**
> **What is AI-friendly writing?**
> AI-friendly writing is writing that's easy for both humans and machines to interpret—clear, structured, and impossible to misquote.

### 3. Keep Grammatical Dependencies Low

Use short sentences with a clear subject and verb. Avoid long chains of clauses that delay the main point.

**Bad:**
> "By implementing these strategies, you can boost engagement across your content."

**Good:**
> "Use these strategies to boost engagement."

### 4. Say What You Mean Before You Get Clever

State the point literally first. You can add personality, metaphors, or jokes after the core idea is clear.

**Bad:**
> "When it comes to AI Search, most brands are still flying blind."

**Good:**
> "A lot of brands don't yet understand how AI Search discovers and cites their content."

### 5. Use Clear Pronouns and References

Every "it", "this", or "that" should have an obvious referent in the same sentence or the one before it.

**Bad:**
> "This is why it's important to simplify your structure."

**Good:**
> "Clear antecedents make your writing easier for both readers and AI to follow; that's why simplifying your structure matters."

### 6. One Topic at a Time

Each paragraph should support one main idea. If you introduce a new claim, start a new paragraph. This makes it easier for models to assign a single topic to that block of text.

**Bad:**
> "AI-friendly writing requires clear structure. It also changes how we think about storytelling and creativity. Some writers worry this means the death of nuance, but that's not necessarily true if you understand how LLMs process language."

**Good:**
> "AI-friendly writing requires clear structure. Use short sentences, explicit antecedents, and one idea per paragraph. These patterns help both humans and machines follow your argument without getting lost."

### 7. Use a Clear Heading Hierarchy

Treat headings as a map of your reasoning. Use H2 for core sections, H3 for subpoints, and keep the order logical: claim, explanation, proof.

**Structure Example:**
```markdown
## Main Topic (H2)
Introductory statement about the topic.

### Subtopic A (H3)
Details about subtopic A.

### Subtopic B (H3)
Details about subtopic B.
```

### 8. Keep Terminology and Names Consistent

Pick one term for each important concept and use it throughout. If you want to be known for "Generative Engine Optimization (GEO)", avoid switching between GEO, AI SEO, and "AI content tuning" in the same article.

**Bad:**
> "Superlines helps marketers create better content for search. SL also supports AI visibility tracking. Our platform offers several AI-powered tools."

**Good:**
> "Superlines helps brands track, optimize, and grow their visibility in AI Search—from monitoring AI visibility to identifying citation opportunities."

### 9. Write Confident, Evidence-Backed Statements

When you know something, say it directly and support it. Avoid constant hedging like "it seems" or "it might" unless you genuinely don't know.

**Bad:**
> "It seems like AI Search might change how brands approach SEO."

**Good:**
> "AI Search is rewriting how brands approach SEO."

### 10. Use Semantically Related Terms

Don't only use your main keyword. Surround it with the natural vocabulary of the topic: related tools, concepts, metrics, and use cases.

**Bad:**
> "AI Search is changing how people find information online."

**Good:**
> "AI Search, through features like Google's AI Overviews and the broader GEO layer, is changing how people discover and trust information online."

### 11. Define Acronyms and Technical Terms Once

Spell out any acronym the first time you use it.

**Bad:**
> "GEO is changing how brands approach search visibility."

**Good:**
> "Generative Engine Optimization (GEO)—the practice of optimizing content for AI-powered search engines—is changing how brands approach visibility."

### 12. Make Every Paragraph Quotable on Its Own

Write each paragraph so it can stand alone as a small answer. One clear idea, stated directly, with enough context that it still makes sense if an AI lifts only those two or three sentences.

**Bad:**
> "AI-friendly writing requires structure, clarity, and empathy. You need to think about formatting, semantics, and tone, because LLMs read differently than people do, and readers still want personality."

**Good:**
> "AI-friendly writing starts with structure. One idea per paragraph makes your content easier to parse—for humans and for machines."

## Content Structure Template

When creating new content, use this structure:

```markdown
# [Clear, Question-Based Title]

> **TL;DR:** [2-3 sentence summary with the main takeaway]

## [Question-Based H2]

[Direct answer in first 1-2 sentences]

[Supporting details, evidence, examples]

### [Subtopic H3]

[Focused explanation of one aspect]

## Key Takeaways

- [Takeaway 1 - quotable standalone statement]
- [Takeaway 2 - quotable standalone statement]
- [Takeaway 3 - quotable standalone statement]

## FAQ

### [Common question 1]
[Direct answer]

### [Common question 2]
[Direct answer]
```

## Checklist Before Publishing

- [ ] Title answers or implies a question users would ask
- [ ] TL;DR section summarizes key points in 2-3 sentences
- [ ] First paragraph contains the main answer/thesis
- [ ] Each H2 is question-based or clearly topic-focused
- [ ] Every paragraph supports exactly one main idea
- [ ] All acronyms are defined on first use
- [ ] Pronouns have clear antecedents
- [ ] Terminology is consistent throughout
- [ ] Statements are confident and evidence-backed
- [ ] Content includes semantically related terms
- [ ] Every paragraph could be quoted standalone
- [ ] FAQ section addresses common questions directly

## Word Count Guidelines

- **Articles:** 1,500-3,000 words for comprehensive coverage
- **Documentation pages:** 500-1,500 words, focused on one task
- **FAQ entries:** 50-150 words per answer
- **TL;DR sections:** 50-100 words maximum

## Formatting for Extractability

Use these elements to make content easy for AI to extract:

| Element | Use For |
|---------|---------|
| **Tables** | Comparisons, features, specifications |
| **Bullet lists** | Steps, features, benefits |
| **Numbered lists** | Sequences, rankings, processes |
| **Blockquotes** | Key definitions, important callouts |
| **Code blocks** | Examples, templates, configurations |

ai-search-technical-auditor

Audit front-end code for AI search readiness. Use when reviewing HTML structure, meta tags, schema markup, and technical elements that affect how AI crawlers understand and index web pages.

# AI Search Technical Auditor

Audit HTML, meta tags, schema markup, and technical implementation to ensure pages are optimized for AI search engine crawlers.

## Understanding AI Crawlers

AI search engines use different crawlers than traditional search engines. Key AI crawlers include:

| Crawler | Platform | User Agent Contains |
|---------|----------|---------------------|
| GPTBot | OpenAI/ChatGPT | `GPTBot` |
| Google-Extended | Google AI/Gemini | `Google-Extended` |
| ClaudeBot | Anthropic/Claude | `ClaudeBot` |
| PerplexityBot | Perplexity | `PerplexityBot` |
| Bytespider | ByteDance | `Bytespider` |

## Technical Audit Checklist

### 1. robots.txt Configuration

Check that AI crawlers are allowed:

```txt
# Good - Allow AI crawlers
User-agent: GPTBot
Allow: /

User-agent: Google-Extended
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: PerplexityBot
Allow: /
```

```txt
# Bad - Blocking AI crawlers (unless intentional)
User-agent: GPTBot
Disallow: /
```

**Audit questions:**
- [ ] Are AI crawlers explicitly allowed or blocked?
- [ ] Is the intent to block deliberate and documented?
- [ ] Are important content paths accessible?

### 2. HTML Structure

#### Semantic HTML

Check for proper semantic structure:

```html
<!-- Good -->
<article>
  <header>
    <h1>Page Title</h1>
    <p class="summary">TL;DR content here</p>
  </header>
  <section>
    <h2>Section Heading</h2>
    <p>Content...</p>
  </section>
</article>

<!-- Bad -->
<div class="article">
  <div class="title">Page Title</div>
  <div class="content">
    <div class="heading">Section Heading</div>
    <div>Content...</div>
  </div>
</div>
```

**Audit questions:**
- [ ] Uses semantic elements (`<article>`, `<section>`, `<nav>`, `<aside>`)?
- [ ] Heading hierarchy is logical (H1 → H2 → H3)?
- [ ] Only one `<h1>` per page?
- [ ] Main content is in `<main>` element?

#### Content Accessibility

```html
<!-- Good - Content in HTML -->
<h2>Product Features</h2>
<ul>
  <li>Feature one description</li>
  <li>Feature two description</li>
</ul>

<!-- Bad - Content in JavaScript only -->
<div id="features"></div>
<script>
  renderFeatures(); // Content not in initial HTML
</script>
```

**Audit questions:**
- [ ] Key content is in initial HTML (not JavaScript-rendered)?
- [ ] Images have descriptive alt text?
- [ ] Tables have proper headers (`<th>`)?
- [ ] Lists use `<ul>`/`<ol>` elements?

### 3. Meta Tags

#### Essential Meta Tags

```html
<head>
  <!-- Page title - Clear and descriptive -->
  <title>What is GEO? Generative Engine Optimization Guide | Brand</title>
  
  <!-- Meta description - Summarizes page content -->
  <meta name="description" content="GEO (Generative Engine Optimization) 
    is the practice of optimizing content for AI search engines. Learn 
    how to improve visibility in ChatGPT, Perplexity, and Google AI Mode.">
  
  <!-- Canonical URL -->
  <link rel="canonical" href="https://example.com/geo-guide">
  
  <!-- Language -->
  <html lang="en">
  
  <!-- Viewport for mobile -->
  <meta name="viewport" content="width=device-width, initial-scale=1">
</head>
```

**Audit questions:**
- [ ] Title is descriptive and under 60 characters?
- [ ] Meta description summarizes content (150-160 chars)?
- [ ] Canonical URL is set correctly?
- [ ] Language is declared?
- [ ] Viewport meta tag is present?

#### Open Graph Tags

```html
<meta property="og:title" content="What is GEO?">
<meta property="og:description" content="Guide to Generative Engine Optimization">
<meta property="og:type" content="article">
<meta property="og:url" content="https://example.com/geo-guide">
<meta property="og:image" content="https://example.com/images/geo-guide.jpg">
```

**Audit questions:**
- [ ] OG title and description are set?
- [ ] OG image is specified and valid?
- [ ] OG URL matches canonical?

### 4. Schema Markup (JSON-LD)

#### Article Schema

```html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "What is Generative Engine Optimization (GEO)?",
  "description": "A comprehensive guide to GEO for AI search visibility",
  "author": {
    "@type": "Person",
    "name": "Author Name",
    "url": "https://example.com/authors/author-name"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Company Name",
    "logo": {
      "@type": "ImageObject",
      "url": "https://example.com/logo.png"
    }
  },
  "datePublished": "2024-01-15",
  "dateModified": "2024-03-20",
  "mainEntityOfPage": "https://example.com/geo-guide"
}
</script>
```

#### FAQ Schema

```html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is GEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "GEO (Generative Engine Optimization) is the practice of optimizing content to be cited in AI-generated answers."
      }
    },
    {
      "@type": "Question",
      "name": "How does GEO differ from SEO?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "SEO focuses on search rankings while GEO focuses on being cited in AI answers."
      }
    }
  ]
}
</script>
```

#### HowTo Schema

```html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to Create an llms.txt File",
  "description": "Step-by-step guide to creating llms.txt for AI crawlers",
  "step": [
    {
      "@type": "HowToStep",
      "name": "Audit your content",
      "text": "Identify your most important pages for AI discovery"
    },
    {
      "@type": "HowToStep", 
      "name": "Create the file",
      "text": "Create llms.txt at your domain root"
    }
  ]
}
</script>
```

**Audit questions:**
- [ ] Schema type matches content type?
- [ ] JSON-LD is valid (no syntax errors)?
- [ ] Required properties are populated?
- [ ] Dates are in ISO 8601 format?
- [ ] URLs are absolute, not relative?

### 5. Page Speed

AI crawlers, especially agentic ones, have tight time budgets. Target:

| Metric | Target | Critical for |
|--------|--------|--------------|
| Time to First Byte (TTFB) | < 200ms | All crawlers |
| First Contentful Paint (FCP) | < 1.8s | Content extraction |
| Largest Contentful Paint (LCP) | < 2.5s | Full page analysis |
| **AI Crawler Target** | < 0.4s FCP | Real-time agents |

**Audit questions:**
- [ ] TTFB under 200ms?
- [ ] FCP under 1.8s (ideally under 0.4s)?
- [ ] No render-blocking JavaScript?
- [ ] Images are optimized and lazy-loaded?
- [ ] CSS is minified?

### 6. Mobile Friendliness

```html
<!-- Viewport meta tag -->
<meta name="viewport" content="width=device-width, initial-scale=1">
```

**Audit questions:**
- [ ] Viewport meta tag is present?
- [ ] Content is readable without zooming?
- [ ] Touch targets are appropriately sized?
- [ ] No horizontal scrolling required?

### 7. URL Structure

```
Good URLs:
/guides/geo-optimization
/products/analytics-platform
/docs/api-reference

Bad URLs:
/page.php?id=123&cat=5
/guides/geo-optimization-best-practices-guide-2024-updated-version-3
/p/12345
```

**Audit questions:**
- [ ] URLs are descriptive and readable?
- [ ] URLs are not excessively long?
- [ ] URLs use hyphens, not underscores?
- [ ] No query parameters for primary content?

## Audit Report Template

```markdown
# AI Search Technical Audit Report

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

## Summary
[Brief summary of findings]

## Critical Issues
- [ ] Issue 1
- [ ] Issue 2

## Warnings
- [ ] Warning 1
- [ ] Warning 2

## Passed Checks
- [x] Check 1
- [x] Check 2

## Recommendations
1. [Priority 1 recommendation]
2. [Priority 2 recommendation]
3. [Priority 3 recommendation]
```

## Quick Reference: Schema Types

| Content Type | Schema | Required Properties |
|--------------|--------|---------------------|
| Article | Article | headline, author, datePublished |
| FAQ | FAQPage | mainEntity (array of Questions) |
| How-to | HowTo | name, step (array of HowToSteps) |
| Product | Product | name, description, offers |
| Organization | Organization | name, url, logo |
| Person | Person | name |
| BreadcrumbList | BreadcrumbList | itemListElement |

## Validation Tools

After implementing fixes, validate using:

1. **Schema:** Google Rich Results Test, Schema.org Validator
2. **HTML:** W3C Validator
3. **Speed:** Google PageSpeed Insights, WebPageTest
4. **Mobile:** Google Mobile-Friendly Test
5. **robots.txt:** Google Search Console robots.txt Tester

ai-search-visibility-audit

Comprehensive AI search visibility analysis using Superlines data. Use when auditing brand visibility across AI engines, analyzing competitor presence, or building GEO strategies based on real AI search data. Requires Superlines MCP server connection.

# AI Search Visibility Audit

Perform comprehensive AI search visibility analysis using real-time data from AI search engines. This skill leverages the Superlines MCP server for authentic visibility metrics.

## Prerequisites

This skill requires the **Superlines MCP server** to access AI search visibility data.

### Installing Superlines MCP Server

Add the Superlines MCP server to your configuration:

**For Claude Code** (`~/.claude.json` or project `.claude.json`):
```json
{
  "mcpServers": {
    "superlines": {
      "command": "npx",
      "args": ["@superlines/mcp-server"],
      "env": {
        "SUPERLINES_API_KEY": "your-api-key"
      }
    }
  }
}
```

**For Cursor** (`.cursor/mcp.json`):
```json
{
  "mcpServers": {
    "superlines": {
      "command": "npx",
      "args": ["@superlines/mcp-server"],
      "env": {
        "SUPERLINES_API_KEY": "your-api-key"
      }
    }
  }
}
```

Get your API key at [superlines.io](https://superlines.io).

## Visibility Audit Framework

### Step 1: Define Audit Scope

Before running the audit, define:

**Brand Information:**
- Primary brand name
- Alternative names/spellings
- Key products/services
- Target markets

**Competitor Set:**
- 3-5 direct competitors
- 2-3 indirect competitors (optional)

**Topic Clusters:**
- Primary category queries
- Product-specific queries
- Comparison queries
- How-to/educational queries

### Step 2: Collect Visibility Data

Use Superlines MCP tools to gather data:

```
# Get brand visibility across AI engines
superlines.get_brand_visibility({
  brand: "Your Brand",
  engines: ["chatgpt", "perplexity", "gemini", "google-ai-mode"],
  date_range: "last_30_days"
})

# Get competitor analysis
superlines.get_competitor_analysis({
  brand: "Your Brand",
  competitors: ["Competitor A", "Competitor B", "Competitor C"],
  topics: ["your category", "key feature"]
})

# Get citation analysis
superlines.get_citations({
  domain: "yourdomain.com",
  date_range: "last_30_days"
})
```

### Step 3: Analyze Key Metrics

#### Brand Visibility Score

**Definition:** Percentage of AI answers that mention your brand for tracked queries.

**Benchmarks:**
| Visibility | Rating | Interpretation |
|------------|--------|----------------|
| > 30% | Excellent | Strong AI presence |
| 20-30% | Good | Solid foundation |
| 10-20% | Fair | Room for improvement |
| < 10% | Poor | Significant gap |

#### Citation Rate

**Definition:** Percentage of answers that cite your domain as a source.

**Benchmarks:**
| Citation Rate | Rating | Interpretation |
|---------------|--------|----------------|
| > 20% | Excellent | Trusted source |
| 10-20% | Good | Building authority |
| 5-10% | Fair | Limited trust |
| < 5% | Poor | Not seen as authoritative |

#### AI Share of Voice

**Definition:** Your brand mentions divided by total competitor mentions.

**Calculation:**
```
AI SOV = (Your Mentions / Total Category Mentions) × 100
```

**Benchmarks:**
| Share of Voice | Rating | Position |
|----------------|--------|----------|
| > 25% | Leader | Category leader |
| 15-25% | Strong | Major player |
| 5-15% | Moderate | Competitive |
| < 5% | Weak | Visibility gap |

#### Context Accuracy

**Definition:** Whether AI describes your brand correctly.

**Check for:**
- Correct product descriptions
- Accurate pricing information
- Current feature lists
- Proper brand positioning
- No outdated information

### Step 4: Gap Analysis

#### Visibility Gaps

Identify where competitors appear but you don't:

```
# Query gap analysis
superlines.get_query_gaps({
  brand: "Your Brand",
  competitors: ["Competitor A", "Competitor B"],
  threshold: 0.2  # Show queries where competitors have 20%+ visibility
})
```

**Gap categories:**
1. **Complete absence** - You never appear
2. **Weak presence** - You appear < 10% vs competitor > 30%
3. **Competitive** - Similar visibility
4. **Leadership** - You dominate

#### Citation Source Gaps

Identify where competitors are cited but you're not:

```
# Citation source analysis
superlines.get_citation_sources({
  competitors: ["Competitor A", "Competitor B"],
  show_gaps: true
})
```

**Common citation sources:**
- Industry publications
- Review sites (G2, Capterra)
- Wikipedia
- Reddit discussions
- YouTube videos
- LinkedIn articles

### Step 5: Query Fan-Out Analysis

Understand how AI systems expand user queries:

```
# Get query fan-out data
superlines.get_query_fanout({
  primary_query: "best GEO tools",
  engine: "chatgpt"
})
```

**What to analyze:**
- Which sub-queries does AI generate?
- Does your content address these sub-queries?
- Are competitors better positioned for fan-out queries?

**Example fan-out:**
```
Primary: "best GEO tools"
├── "GEO analytics platforms"
├── "AI search visibility software"
├── "ChatGPT ranking tools"
├── "Superlines vs competitors"
└── "GEO tool pricing comparison"
```

### Step 6: Engine-by-Engine Analysis

Compare performance across different AI engines:

| Engine | Your Visibility | Top Competitor | Gap |
|--------|-----------------|----------------|-----|
| ChatGPT | _% | _% | _% |
| Perplexity | _% | _% | _% |
| Gemini | _% | _% | _% |
| Google AI Mode | _% | _% | _% |
| Claude | _% | _% | _% |

**Engine-specific notes:**
- **ChatGPT:** Highest search volume, uses Bing/web search
- **Perplexity:** Heavy citation focus, shows sources prominently
- **Gemini:** Integrated with Google Search, affects AI Overviews
- **Google AI Mode:** Uses Google index, affects traditional search too

## Audit Report Template

### AI Search Visibility Audit Report

```markdown
# AI Search Visibility Audit
**Brand:** [Brand Name]
**Date:** [Date]
**Period:** [Date Range]

## Executive Summary
[2-3 paragraph summary of key findings]

## Key Metrics

| Metric | Current | Previous | Change | Target |
|--------|---------|----------|--------|--------|
| Brand Visibility | X% | X% | +/-X% | X% |
| Citation Rate | X% | X% | +/-X% | X% |
| AI Share of Voice | X% | X% | +/-X% | X% |
| Context Accuracy | X% | X% | +/-X% | 95%+ |

## Visibility by Engine

| Engine | Visibility | Citations | SOV Rank |
|--------|------------|-----------|----------|
| ChatGPT | X% | X | #X |
| Perplexity | X% | X | #X |
| Gemini | X% | X | #X |
| Google AI Mode | X% | X | #X |

## Competitor Analysis

| Competitor | Visibility | Citation Rate | SOV |
|------------|------------|---------------|-----|
| Competitor A | X% | X% | X% |
| Competitor B | X% | X% | X% |
| Competitor C | X% | X% | X% |
| **Your Brand** | **X%** | **X%** | **X%** |

## Top Visibility Gaps

1. **[Query/Topic]**
   - Your visibility: X%
   - Top competitor: X% (Competitor A)
   - Opportunity: [Description]

2. **[Query/Topic]**
   - Your visibility: X%
   - Top competitor: X% (Competitor B)
   - Opportunity: [Description]

## Citation Source Analysis

**Currently citing your brand:**
- [Source 1] - [X citations]
- [Source 2] - [X citations]

**Citing competitors but not you:**
- [Source 1] - Cites: [Competitor A, B]
- [Source 2] - Cites: [Competitor A]

## Context Accuracy Issues

- [ ] [Issue 1: e.g., "Outdated pricing mentioned"]
- [ ] [Issue 2: e.g., "Missing key product feature"]

## Recommendations

### Immediate Actions (This Week)
1. [Specific action with expected impact]
2. [Specific action with expected impact]

### Short-Term (This Month)
1. [Specific action with expected impact]
2. [Specific action with expected impact]

### Medium-Term (This Quarter)
1. [Specific action with expected impact]
2. [Specific action with expected impact]

## Appendix

### Tracked Queries
[List of queries being monitored]

### Data Sources
[Superlines platform, date range, methodology]
```

## Action Planning

Based on audit findings, prioritize actions:

### Quick Wins (1-2 weeks)
- Update outdated content on high-visibility pages
- Fix context accuracy issues
- Add missing schema markup
- Refresh dates on cornerstone content

### Medium Priority (1-3 months)
- Create content for visibility gap topics
- Build presence on citation source sites
- Develop comparison content
- Expand FAQ coverage

### Strategic Initiatives (3-6 months)
- Build third-party authority (PR, partnerships)
- Develop original research/data
- Create comprehensive resource hubs
- Establish thought leadership content

## Ongoing Monitoring

Set up recurring visibility tracking:

```
# Schedule weekly visibility check
superlines.create_alert({
  type: "visibility_change",
  threshold: -10,  # Alert if visibility drops 10%+
  queries: ["primary query 1", "primary query 2"],
  notification: "email"
})
```

**Recommended cadence:**
| Check | Frequency |
|-------|-----------|
| Visibility metrics | Weekly |
| Citation analysis | Bi-weekly |
| Competitor review | Monthly |
| Full audit | Quarterly |