llms.txt Validator – Check & Optimize Your AI Files
Validates your llms.txt for format errors, token limits and missing sections. Optimize your AI files with actionable tips – all for free.
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Validation Result
What does the llms.txt Validator check?
The validator analyzes your AI files (llms.txt, llms-full.txt, llms-data.json, llms-meta.yaml) and checks the llms.txt against the official llmstxt.org standard.
Format checks: Correct Markdown structure with H1 heading, blockquote summary, H2 sections and Markdown links. HTML fragments and empty files are detected.
Token analysis: LLMs have limited context windows. The llms.txt should ideally stay under 4,000 tokens, the llms-full.txt under 100,000. Files that are too large get truncated and lose important information.
Combine the Validator with other GEO Tools
Combine the validator with the robots.txt AI Check, the AI Visibility Check and the Schema.org Checker for a complete picture of your AI visibility.
Frequently asked questions about the Validator
The validator analyzes your llms.txt and llms-full.txt on three levels: format compliance with the llms.txt standard, token usage relative to AI context windows, and content completeness (project name, description, sections, links). Errors and optimization opportunities are reported with specific guidance.
AI assistants like ChatGPT and Claude read llms.txt within their context window. If the file exceeds the limit (~8,000–16,000 tokens depending on the system), it gets truncated – important product or service information is lost. The validator shows your exact token usage and warns when limits are exceeded.
A complete llms.txt should include at least the sections ## Products (or ## Services), ## About, and ## Contact. Missing sections mean AI systems cannot retrieve key context about your business.
Yes – you can validate both the compact llms.txt and the extended llms-full.txt. For the full version, token limits are evaluated separately since it is designed for deep research queries and requires larger context windows.
Alongside the validator, we recommend the llms.txt Generator for creating optimized AI files and the Schema.org Score for analyzing structured data. Together they form the foundation for complete AI visibility optimization – from technical implementation to the content shaping of your AI presence.
llms.txt Validator – additional features
The validator detects common errors like missing User-agent: * at the start of the file, inconsistent Markdown formatting, descriptions that are too short, and duplicate section headers. It also checks whether all listed links (Docs:, API:) are reachable. Regular validation after changes to your llms.txt ensures AI systems can process your content correctly.
How to use the validator: Enter your domain or paste the content of your llms.txt directly. The validator checks format, completeness, and token usage and displays all findings with priority. Critical errors are marked in red, optimization hints in yellow. After making corrections, you can re-validate to confirm all issues have been resolved.