How AI-Ready is Your Website?

What is LLM Rank?

LLM Rank is a free tool that evaluates how well your website can be crawled, parsed, and understood by large language models. As AI systems increasingly rely on web content for answers, ensuring your site is optimized for machine consumption is just as important as traditional search engine optimization.

Simply enter a URL and LLM Rank will fetch your page, analyze its HTML, metadata, and supporting files, then produce a comprehensive score from 0 to 100 with a letter grade from A+ to F. Each score includes a detailed breakdown across seven weighted categories so you know exactly where to improve.

Scoring Categories

Every website is evaluated across seven categories, each measuring a different aspect of AI readiness. Categories are weighted to reflect their relative importance for LLM comprehension.

1. Structured Data (20%) — JSON-LD, Open Graph tags, Twitter Cards, microdata, meta descriptions, and breadcrumb markup that help machines understand your content semantically.
2. LLM Directives (20%) — Presence of an llms.txt file, robots.txt configuration, AI bot rules, meta robot directives, and character encoding declarations.
3. Content Clarity (15%) — Readability score, text-to-HTML ratio, paragraph structure, and word count to ensure content is clear and substantial.
4. Machine-Readable (13%) — RSS and Atom feeds, sitemap availability, canonical URLs, language declarations, navigation structure, URL cleanliness, and date signals.
5. Semantic HTML (12%) — Heading hierarchy, landmark elements, sectioning elements, single H1 usage, and semantic list elements.
6. Accessibility (10%) — Image alt text coverage, ARIA labels, link text quality, and form element labeling that also aid machine understanding.
7. Content Extraction (10%) — Main content element presence, signal-to-noise ratio, script overhead, DOM structure cleanliness, structured content markup, and SPA detection.

How Scoring Works

When you submit a URL, LLM Rank fetches the page along with its robots.txt, llms.txt, and sitemap.xml files. It then runs over 30 individual checks grouped into the seven categories listed above. Each check produces a score from 0 to 100 based on specific criteria.

Category scores are calculated by averaging their individual checks. The overall score is a weighted sum of category scores. Finally, the numeric score is converted to a letter grade using a standard academic scale.

Grading Scale

Grade	Score Range	Meaning
A+	97–100	Exceptional AI readiness
A	93–96	Excellent AI readiness
A-	90–92	Very good AI readiness
B+	87–89	Good AI readiness
B	83–86	Above average
B-	80–82	Slightly above average
C+	77–79	Average
C	73–76	Below average
C-	70–72	Needs improvement
D	60–69	Poor AI readiness
F	0–59	Failing AI readiness

Why AI Readiness Matters

Large language models like GPT, Claude, and Gemini increasingly power search experiences, customer support chatbots, and knowledge retrieval systems. When these models reference your content, they rely on clear structure, accurate metadata, and accessible text to provide correct and attributed answers.

Websites that score well on LLM Rank are more likely to be accurately cited and correctly understood by AI systems. Poor scores often mean your content is being misrepresented, ignored, or conflated with other sources.

Optimizing for AI readiness does not conflict with traditional SEO. In fact, most improvements — better structured data, cleaner HTML, clearer writing — benefit both search engines and language models.

• More accurate AI-generated citations of your content
• Better visibility in AI-powered search results
• Improved traditional SEO as a side effect
• Clearer content structure for all users

Key Files for LLM Discovery

llms.txt

Summary of this site for AI models

llms-full.txt

Detailed documentation for AI models

robots.txt

Crawler access rules

sitemap.xml

Site structure for crawlers