> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dakota.xyz/llms.txt
> Use this file to discover all available pages before exploring further.

# Using LLMs

Dakota has made its documentation AI-friendly through multiple mechanisms designed to help Large Language Models understand and integrate with the platform.

## LLM Feed Files

To help LLMs stay current on how Dakota works, we expose two continuously updated files for ingestion:

* [`llms.txt`](/llms.txt) - A concise, high-signal list of top-level docs pages, great for smaller models or quick context building.
* [`llms-full.txt`](/llms-full.txt) - A more exhaustive listing that includes nearly all pages, ideal for full-context indexing.

You can regularly ingest these URLs into your custom GPTs or other LLM apps to ensure Dakota-specific questions are grounded in accurate technical detail.

## Contextual Deep Links

The documentation supports "contextual" features allowing you to:

### Export as Markdown

Export any Dakota documentation page as Markdown for:

* Custom GPT training data
* Internal knowledge bases
* Team documentation
* Offline reference

### AI Chat Integration

Launch pre-loaded chat sessions with Claude or ChatGPT for specific documentation pages. This enables:

* Instant troubleshooting
* Code generation with proper context
* Deeper topic exploration
* Interactive learning

### Use Cases

**Troubleshooting**: Open a docs page about webhooks, click "Ask Claude", and get immediate help with your specific webhook implementation issue.

**Code Generation**: Load the API reference page, start a chat, and generate production-ready code that follows Dakota's best practices.

**Learning**: Explore complex topics like transaction flows by chatting with an AI that has full context of Dakota's documentation.

## Best Practices

### Regular Ingestion

For custom GPTs or internal tools:

* Fetch llms.txt or llms-full.txt regularly (daily or weekly)
* Update your knowledge base with the latest documentation
* Ensure accurate, current technical information

### Context Management

* Use llms.txt for general queries and overviews
* Use llms-full.txt when detailed implementation guidance is needed
* Combine with live API testing for verification

### Security Considerations

* Never share API keys with AI assistants
* Use sandbox credentials when generating code examples
* Review AI-generated code before production deployment
* Verify security recommendations against official docs

## Getting Started

1. **Choose Your Integration Method**
   * Quick start: Use llms.txt with your AI assistant
   * Full context: Ingest llms-full.txt into custom GPTs

2. **Test Your Setup**
   * Ask basic questions about Dakota concepts
   * Request code examples for common operations
   * Verify responses against official documentation

3. **Build with Confidence**
   * Generate boilerplate integration code
   * Get instant answers to API questions
   * Troubleshoot issues with AI assistance

## Resources

* [Concise documentation feed](/llms.txt)
* [Complete documentation feed](/llms-full.txt)
* [Complete API documentation](/api-reference/introduction)

## Support

Need help integrating Dakota documentation with your AI tools? Contact our support team at [dakota.xyz/talk-to-sales](https://dakota.xyz/talk-to-sales) for assistance.