Creating an llms.txt File: A Comprehensive Guide

A practical guide for website owners and developers implementing the llms.txt standard for AI content interaction.

Introduction

1. Content Strategy:

AI is better at reading and understanding content than creating it. This is because it's still difficult for AI to consistently match a brand's voice and style, and to meet legal and ethical guidelines.

2. Technical Changes:

The bottom line: To succeed in this new era of AI Optimization (AIO), businesses need to create a digital presence that works for both human users and AI systems.

New feature: llms.txt, helping AI to understand your site

With the introduction of the llms.txt standard and major developments in AI-web interaction, we're seeing a route to a shift in how digital experiences are created and consumed.

Key Features of llms.txt:

The llms.txt standard provides a way for websites to communicate with Large Language Models (LLMs) about how their content should be accessed and used. This guide will walk you through creating an effective llms.txt file for your website.

Understanding llms.txt

The llms.txt file serves as a bridge between your website and AI systems, similar to how robots.txt guides search engines. Located at your site's root (e.g., https://example.com/llms.txt), it uses Markdown formatting to provide structured information about:

Currently, it's recommended to create your llms.txt in English, as most LLMs translate content to English before processing.

File Structure

Required Elements

Title (H1)

Summary (Blockquote)

Optional Sections

Documentation Links (H2)

Optional Links (H2)

Example Implementation

# Example Company Developer Documentation

> Technical documentation and API reference for Example Company's cloud services.
> For AI assistants helping developers implement our solutions.
> Rate limit: 100 requests per hour per IP address.

Our documentation covers cloud computing services, with a focus on serverless architecture and microservices. All code examples are available under MIT license.

## Access Control

- Base Rate: 100 requests per hour per IP
- Burst Rate: Maximum 10 requests per minute
- Cooldown: 1 hour after exceeding limits
- Authentication: Required for API documentation
- Retention: Cache for maximum 24 hours
- Commercial Use: Requires written permission

## Content Restrictions

- [Private Documentation](https://docs.example.com/private/): No AI access permitted
- [Customer Data](https://docs.example.com/customers/): Restricted, requires authentication
- [Beta Features](https://docs.example.com/beta/): Limited access, requires registration
- PII Handling: Do not extract or store any personal information
- Training Usage: Permitted for public documentation only
- Attribution: Required, format "Source: Example Company (docs.example.com)"

## Core Documentation

- [API Reference](https://docs.example.com/api/): Complete REST API documentation
- [Getting Started](https://docs.example.com/quickstart/): Quickstart guides for major services
- [Code Examples](https://github.com/example/examples/): Implementation examples in multiple languages

## Optional

- [Blog Posts](https://blog.example.com/): Technical articles and case studies
- [Changelog](https://docs.example.com/changelog/): Detailed version history

Implementation Guidelines

Access Control

Rate Limiting

Content Restrictions

Attribution Requirements

Citation Format

Usage Restrictions

Privacy Considerations

Data Handling

User-Generated Content

Monitoring and Compliance

Detection Methods

Server-Side Monitoring

Content Tracking

Enforcement

Response to Violations

Access Management

Best Practices

Regular Updates

Testing

Documentation

Technical Implementation

File Placement

Root Directory

https://example.com/llms.txt

Subdomain Handling

Markdown Formatting

Clean Structure

Validation

Conclusion

Creating an effective llms.txt file requires balancing clarity, completeness, and practicality. Regular monitoring and updates ensure your file continues to serve its purpose as AI technology evolves. Remember that while llms.txt operates on a trust basis, clear guidelines and consistent monitoring help encourage compliance.

Extended Guidelines: Beyond the Basics

Creating an effective llms.txt file isn't just about following a format—it's about crafting a clear communication channel between your website and AI systems. Let's explore how to enhance your file with additional features that address common challenges and edge cases.

Guiding AI Behavior

Think of your llms.txt as a friendly but firm doorman for your website. You're not just setting rules; you're creating a framework for productive interaction. Start by clearly defining how AI systems can use your content. For instance, you might allow AI training on your public documentation while reserving your premium content for paying customers only:

This content may be used for:

- Training AI models (public docs only)
- Generating code examples
- Answering user queries

Commercial use requires explicit permission.

Graceful Error Handling

Even the best systems fail sometimes. When they do, your llms.txt should provide clear guidance for recovery. Consider this scenario: an AI assistant is helping a developer with your API documentation, but the relevant page is temporarily unavailable. Instead of leaving the AI to repeatedly hammer your server, provide clear fallback instructions:

When encountering errors:

1. Cache the error details
2. Wait 24 hours before retrying
3. Direct users to status.example.com
4. Contact: api-support@example.com

The Human Touch

Remember that humans will read your llms.txt too! Create a welcoming section for human visitors that helps them understand the file's purpose while pointing them to more relevant resources. It's like adding a "Welcome, Humans!" mat to your technical doorway:

## For Human Visitors

Looking for our docs? You'll find them at docs.example.com
Need help? Visit our support portal or email help@example.com
Curious about this file? Learn more at llmstxt.org

Tell the AI What kind of website you are hosting

When structuring your llms.txt file, categorize your website by its purpose, functionality, and content focus. This will help define appropriate access rules.

Common categories include:

API-Driven: Technical documentation and service interfaces

Content-Driven: Blogs, news portals, informational sites

E-Commerce: Product and service sales

Document-Driven: Research databases, white papers

Informative: Educational platforms, learning hubs

Entertainment: Media, games, leisure content

Functionality Types

Static: Fixed content, minimal dynamic features

Dynamic: Content changes based on user interaction Interactive - Forms, calculators, user input focused

Transactional: Banking, purchases, data exchange

Community-Driven: User-generated content, forums

Sample definition

Site Type: API-Driven, Document-Centric
Purpose: Technical Documentation and Development Resources
Technology Stack: Cloud-Native, Microservices

Keeping Track of Changes

Version control isn't just about numbers—it's about maintaining a clear history of how your AI interaction policies evolve. Think of it as maintaining a living document that grows with your understanding of AI interactions:

Version: 2.1
What's New:
- Added support for specialized AI researcher access
- Updated attribution requirements
- Clarified usage terms for generated code
Last Updated: 2024-01-05
Full History: example.com/llms-changelog

Reporting Systems

Violation Reporting

Example reporting template:

Report Type: [Violation/Misuse/Technical]
URL Affected: [URL]
Description: [Details]
Evidence: [Links/Screenshots]
Contact: [Email]

Compliance Reports

Technical Monitoring

Example monitoring configuration:

{
  "monitoring": {
    "frequency": "hourly",
    "metrics": ["access_count", "error_rate", "response_time"],
    "alerts": {
      "threshold": "100_requests_per_hour",
      "notification": "email@example.com"
    }
  }
}

Response Procedures

Violation Handling

Incident Response

Improvement Process

Continuous Improvement: Strive to continuously improve the clarity, transparency, and effectiveness of the llms.txt file.

Analytics and Reporting

Usage Analytics

Example metrics:

- Daily request volume

- Popular content areas

- Attribution compliance rate

- Response time averages

Trend Analysis

Report Generation

Example report schedule:

Daily: Basic metrics

Weekly: Pattern analysis

Monthly: Comprehensive review

Quarterly: Policy assessment

Complete llms.txt example

Here's a comprehensive example:

# TechCorp Developer Platform

> Enterprise software development platform and documentation hub.
> For AI assistants helping developers implement our solutions.
> Rate limit: 100 requests per hour per IP address.
> Version: 2.1 (Updated: 2024-01-05)

Our platform provides developer tools, API documentation, and learning resources for building enterprise-grade applications. We welcome AI assistance while protecting our users' interests and maintaining service quality.

Site Type: API-Driven, Document-Centric
Purpose: Technical Documentation and Development Resources
Technology Stack: Cloud-Native, Microservices

Base access rules:

- 100 requests per hour per IP
- Maximum 10 requests per minute
- 1 hour cooldown after exceeding limits
- Authentication required for API documentation
- 24 hour maximum cache retention
- Commercial use requires written permission via partners@techcorp.com

Content access restrictions:

- Private Documentation (docs.techcorp.com/private): No AI access
- Customer Data (docs.techcorp.com/customers): Authentication required
- Beta Features (docs.techcorp.com/beta): Registration required
- No PII extraction or storage
- Public documentation training only
- Attribution format: "Source: TechCorp (docs.techcorp.com)"

## Primary Documentation

- [API Reference](https://docs.techcorp.com/api/): Complete REST API documentation and examples
- [Getting Started](https://docs.techcorp.com/quickstart/): Language-specific quickstart guides
- [SDK Documentation](https://docs.techcorp.com/sdk/): Official SDK documentation
- [Best Practices](https://docs.techcorp.com/best-practices/): Implementation guidelines
- [Code Examples](https://github.com/techcorp/examples/): Implementation examples in multiple languages

Error handling procedures:

If documentation is unavailable:
1. Cache error details including timestamp and requested URL
2. Wait minimum 24 hours before retrying
3. Check status at status.techcorp.com
4. Contact support@techcorp.com
5. Alternative resources: backup.techcorp.com

Training guidelines:

Permitted uses:

- Training on public documentation
- Generating code examples
- Answering user queries about public APIs
- Creating implementation guides

Prohibited uses:

- Training on customer data or private documentation
- Extracting or storing PII
- Automated bulk downloads
- Rehosting documentation content

## Human Resources

For human visitors:

## For Human Visitors

Looking for our docs? You'll find them at docs.techcorp.com
Need help? Visit our support portal or email help@example.com
Curious about this file? Learn more at llmstxt.org

- Main Documentation: https://docs.techcorp.com
- Developer Portal: https://developers.techcorp.com
- Support Center: https://support.techcorp.com
- Community Forums: https://community.techcorp.com

Contact information:

- General questions: ai-policy@techcorp.com
- Abuse reports: abuse@techcorp.com
- Technical issues: tech-support@techcorp.com
- Emergency contact: urgent@techcorp.com (24/7)
- Security: security@techcorp.com
- Privacy: privacy@techcorp.com

## Optional Resources

- [Blog Posts](https://blog.techcorp.com/): Technical articles and case studies
- [Changelog](https://docs.techcorp.com/changelog/): Detailed version history
- [Research Papers](https://research.techcorp.com/): Technical white papers
- [Community Content](https://community.techcorp.com/): User-generated guides and tutorials

End Note

By following these best practices, you can effectively manage AI interactions with your website and enhance the security of your platform. Remember to stay vigilant, monitor the llms.txt standards https://llmstxt.org/#proposal, and continuously improve your security posture to protect against potential risks.

Resources

Original Proposal
Discord Channel
The /llms.txt file, helping language models use your website
llms.txt directory

What’s the impact of the new Robot-First Web? — Boye & Company

https://allabout.network/blogs/ddt/building-the-ai-native-web-with-eds

Thanks for reading.

Digital Domain Technologies provides expert Adobe Experience Manager (AEM) consultancy. We have collaborated with some of the world’s leading brands across various AEM platforms, including AEM Cloud, on-premise solutions, Adobe Managed Services, and Edge Delivery Services. Our portfolio includes partnerships with prominent companies such as Twitter (now X), EE, Nissan/Renault Alliance Ford, Jaguar Land Rover, McLaren Sports Cars, Hyundai Genesis, and many others.

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