How LLMao Works
Our research-backed platform analyzes your website using the same criteria that LLMs like ChatGPT, Claude, and Perplexity use to evaluate and recommend content.
View Full MethodologyEnter Your URL
Simply paste your URL into our analyzer. We support any publicly accessible site—websites, SaaS products, company pages, and more.
- No login required for free analysis
- Supports all site types
- Instant URL validation
AI-Powered Deep Crawl
Our advanced crawler scans your website, extracting content, structure, HTML semantics, and metadata that AI assistants use to understand your site.
- Full content extraction
- HTML structure analysis
- Structured data detection
Research-Backed Analysis
Using Methodology v2.0, we evaluate your website across 8 categories with 35+ specific tests based on official LLM documentation and academic research.
- 35+ individual tests
- Objective, measurable criteria
- Evidence-based scoring
Actionable Recommendations
Receive specific, prioritized recommendations linked to individual tests. Each recommendation includes the expected impact and relevant documentation.
- Linked to specific tests
- Prioritized by impact
- References to official docs
Track Your Progress
Re-verify specific categories after making changes. Watch your test scores improve as you implement recommendations.
- Category-specific re-verification
- Historical score tracking
- Progress visualization
The 8 Evaluation Categories
Based on research from OpenAI, Google E-E-A-T, Anthropic, Perplexity, and Zhang et al. 2025
Content Structure
Hierarchical, machine-readable content organization that LLMs can easily parse and understand.
Readability
Content that is easy to parse, summarize, and quote by AI systems.
Schema.org Markup
Explicit semantic signals about content type, entities, and relationships using structured data.
Entity Definition
Clear, consistent identification of people, organizations, products, and concepts.
Authority & Trust Signals
E-E-A-T indicators that establish credibility and trustworthiness.
Citation & Source Quality
Verifiable claims backed by high-quality sources that LLMs can corroborate.
Content Freshness
Up-to-date information with clear temporal signals that help LLMs assess relevance.
Technical Accessibility
Content that AI crawlers can easily access, parse, and index.
Research Foundation
Our methodology is based on:
- OpenAI GPTBot Documentation
- Google E-E-A-T Guidelines
- Anthropic Claude Documentation
- Perplexity Indexing Guidelines
- Schema.org Specifications
- Zhang et al. 2025 (ArXiv)
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