LLMs.txt Validator
Check if your website has an LLMs.txt file or validate the contents of your LLMs.txt file to ensure it follows best practices for AI model transparency.
Check Domain for LLMs.txt
Enter a domain name to check if it has an LLMs.txt file at the root level.
Ensure transparency and compliance in AI development with our comprehensive LLMs.txt validator. Check domain presence, validate content structure, and follow best practices for AI model documentation that builds trust with users, researchers, and regulatory bodies in the rapidly evolving AI landscape.
What is LLMs.txt?
LLMs.txt is a standardized file format that provides transparent documentation about AI language models hosted on websites. Similar to robots.txt for web crawlers, LLMs.txt serves as a machine-readable way to communicate essential information about AI systems, including training data, capabilities, limitations, and ethical guidelines.
AI Transparency Standard
Building trust through open documentation of AI capabilities and limitations
transparency in AI development
Why LLMs.txt is Essential for Modern AI Development
Regulatory Compliance
Meet emerging AI regulations and guidelines from governments worldwide. LLMs.txt provides the transparency required by AI governance frameworks like the EU AI Act and helps prepare for future compliance requirements.
User Trust
Build confidence with users by openly documenting your AI systems. Transparency about capabilities, limitations, and ethical considerations helps users make informed decisions about AI tool usage.
Industry Best Practice
Join leading AI companies in adopting transparency standards. LLMs.txt demonstrates commitment to responsible AI development and positions your organization as a leader in ethical AI practices.
LLMs.txt Validator Features
Our comprehensive validator helps you create, check, and maintain LLMs.txt files that meet industry standards and regulatory requirements for AI transparency and documentation.
Domain Presence Check
Instantly verify if any domain has an LLMs.txt file. Check competitors, partners, or your own domains to understand the current state of AI transparency adoption across the web.
Content Validation
Validate your LLMs.txt content for proper structure, required fields, and best practices. Get detailed feedback on formatting, completeness, and compliance with emerging standards.
Standard Compliance
Ensure your documentation meets industry standards for AI transparency. Our validator checks against established formats and emerging best practices in responsible AI development.
Error Detection
Identify formatting errors, missing required fields, and potential compliance issues before deploying your LLMs.txt file. Get actionable feedback to improve your AI documentation.
Real-time Analysis
Get instant feedback as you create or modify your LLMs.txt content. Our real-time validation helps you build compliant documentation efficiently and effectively.
Best Practice Guidance
Receive recommendations for improving your AI documentation based on industry best practices, regulatory guidelines, and successful implementations from leading AI companies.
Understanding LLMs.txt Structure
General Info
Basic information about your organization, contact details, website, and overall AI development approach. This section provides context for all documented models.
Model Details
Specific information about each AI model including architecture, parameters, training data sources, performance metrics, and version information for transparency.
Usage Guidelines
Documentation of intended use cases, capabilities, limitations, and restrictions. Clear guidance on appropriate applications and potential risks or biases.
Ethical Framework
Ethical considerations, bias mitigation strategies, safety measures, and responsible AI practices implemented in model development and deployment.
Essential LLMs.txt Sections
General Information
Organization name, contact information, website, and general AI development philosophy or approach.
Model Information
Detailed specifications including model architecture, parameters, training data, and performance characteristics.
Intended Use
Specific use cases, capabilities, and limitations of the AI models, including appropriate applications and restrictions.
Ethical Considerations
Bias mitigation, safety measures, responsible AI practices, and ethical frameworks governing model development.
Example LLMs.txt Structure
Website: https://example.com
Contact: ai-team@example.com
Version: 1.0
Parameters: 175B
Restrictions: No harmful content
LLMs.txt Best Practices
Content Quality
Comprehensive Documentation
Include all relevant model information, capabilities, and limitations
Clear, Accessible Language
Write for both technical and non-technical audiences
Regular Updates
Keep information current as models evolve and improve
Technical Standards
Proper File Location
Place at domain root (/llms.txt) for easy discovery
Structured Format
Use consistent section headers and key-value pairs
Machine Readable
Format for both human and automated parsing
Compliance Focus
Regulatory Alignment
Meet current and anticipated AI governance requirements
Ethical Transparency
Document bias mitigation and safety considerations
Stakeholder Communication
Provide information relevant to users, researchers, and regulators
Frequently Asked Questions About LLMs.txt
What information should be included in LLMs.txt?
Include basic organization info, detailed model specifications, training data sources, intended use cases, capabilities and limitations, ethical considerations, bias mitigation efforts, and contact information for AI-related inquiries.
Where should I place the LLMs.txt file?
Place it at the root of your domain (e.g., https://example.com/llms.txt) to ensure easy discovery by researchers, regulators, and automated tools that need to access AI transparency information.
Is LLMs.txt required by law?
While not universally mandated, emerging AI regulations like the EU AI Act require transparency documentation. LLMs.txt helps meet these requirements and prepares for future compliance obligations.
How often should I update my LLMs.txt file?
Update whenever you release new models, modify existing ones, change intended use cases, or implement new safety measures. Regular reviews ensure accuracy and compliance with evolving standards.
What happens if I don't have an LLMs.txt file?
You may face compliance issues with AI regulations, reduced trust from users and researchers, and missed opportunities to demonstrate responsible AI development practices to stakeholders and customers.
Can I include multiple models in one LLMs.txt file?
Yes, document all AI models your organization develops or hosts. Use clear section headers to separate different models and include comprehensive information for each system.
What format should I use for LLMs.txt?
Use plain text with clear section headers (ending with colons) and key-value pairs. Include comments with # for additional context. Keep it human-readable while maintaining machine-parseable structure.
Who should have access to our LLMs.txt file?
Make it publicly accessible to researchers, regulators, users, and automated tools. Transparency is the goal - avoid restricting access unless required by specific security or competitive considerations.