ANNOTATED SAMPLE

Sample Audit Report

https://example-client.com

Generated 10 Feb 2026 · Report ID: ao_sample_demo

Visibility Score

out of 100

Passed

Weak

Missing / Blocked

Signals Scanned

Full Analysis

11-Signal Scorecard

Each signal measures a distinct dimension of how AI systems discover, parse, and cite your content.

1. Title Tag

● OK

Title tag is 58 characters and describes the page purpose clearly.

2. Meta Description

● WEAK

Only 32 characters. Short meta descriptions reduce clarity when AI models cite your page.

3. Canonical Tag

● OK

Self-referencing canonical tag found and matches the live URL.

4. OpenGraph Tags

● OK

og:title, og:description, and og:image all present and valid.

5. JSON-LD Structured Data

● MISSING

No JSON-LD schema detected. AI models cannot parse structured entity data from your page.

6. FAQ Schema

● MISSING

No FAQPage schema found. FAQ-rich pages are heavily referenced by AI answer engines.

7. Content Depth

● WEAK

Only 240 words on the page. AI models prefer pages with substantive, structured content (500+ words).

8. OAI-SearchBot Access

● OK

OAI-SearchBot is allowed in robots.txt for search visibility.

9. GPTBot Policy

● BLOCKED

GPTBot is disallowed in robots.txt. ChatGPT cannot train on or retrieve your content.

10. AI Crawlers (Claude & Perplexity)

● OK

ClaudeBot and PerplexityBot are permitted. Your content is accessible to these AI systems.

11. llms.txt

● MISSING

No /llms.txt file found. LLMs have no concise guide to your key pages and capabilities.

Implementation

Priority Fix Cards

Each fix card includes the logic, a source reference, and copy-paste code.

Fix #1 — Add JSON-LD Structured Data

● MISSING

Why It Matters

JSON-LD gives AI systems a clean, machine-readable description of your organization, products, and content structure. Without it, AI models must infer entity relationships from raw text.

Source schema.org/Organization

Add to <head>

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Example Client",
  "url": "https://example-client.com",
  "description": "Your core value proposition",
  "sameAs": [
    "https://twitter.com/exampleclient",
    "https://linkedin.com/company/exampleclient"
  ]
}
</script>

Fix #2 — Add FAQ Schema Markup

● MISSING

Why It Matters

FAQ schema is one of the most referenced structured data types by AI answer engines. Pages with FAQPage markup are significantly more likely to be cited as sources in AI-generated answers.

Source schema.org/FAQPage

Add to page with FAQ content

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "What does your service include?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "Our service includes..."
    }
  }]
}
</script>

Fix #3 — Create /llms.txt

● MISSING

Why It Matters

llms.txt is an emerging standard that gives large language models a concise, curated guide to your site's most important pages. Think of it as a sitemap specifically designed for AI consumption.

Source llmstxt.org

Create /llms.txt in your root

# Example Client
> Your one-line company description.

## About
- [About Us](https://example-client.com/about)

## Products
- [Product A](https://example-client.com/products/a)

## Support
- [FAQ](https://example-client.com/faq)
- [Contact](https://example-client.com/contact)

Your report includes all 11 signals with full fix cards

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