The llms.txt Standard and Aptos

The llms.txt standard provides a way for websites and documentation to be directly consumable by Large Language Models. The Aptos ecosystem embraces this standard to make blockchain development more accessible to AI-assisted workflows.

What is llms.txt?

The llms.txt standard defines a simple, structured text format that:

Is easy for LLMs to parse and understand
Contains all essential information without HTML, JavaScript, or CSS noise
Follows a consistent hierarchy that maps well to LLM context windows
Can be directly included in prompts or system messages

How the Aptos Book Uses llms.txt

This book is built with mdbook-llms-txt-tools, which automatically generates llms.txt output alongside the HTML version. The build process creates two LLM-optimized outputs:

`llms.txt` - Summary Format

A concise overview of the book's structure and key concepts. Useful for giving an LLM a high-level understanding of the Aptos ecosystem.

`llms-full.txt` - Complete Content

The entire book's content in a flat, LLM-friendly format. Useful for giving an LLM deep knowledge about specific topics.

Using llms.txt in Your Workflow

Providing Context to LLMs

When working with an LLM on Aptos development, include relevant sections of the llms.txt output:

System prompt:
You are an expert Aptos/Move developer. Use the following reference material:

[paste relevant sections from llms-full.txt]

User prompt:
Write a Move module for a token vesting contract...

Building Custom AI Tools

You can fetch the llms.txt file programmatically to build AI-powered tools:

// Fetch the Aptos Book content for LLM context
// This book is hosted at aptos-book.com; the llms-full.txt endpoint
// serves the entire book in a single LLM-friendly text file.
const response = await fetch("https://aptos-book.com/llms-full.txt");
const aptosBookContent = await response.text();

// Include in your LLM prompt
const prompt = `
Reference: ${aptosBookContent}

Task: Generate a Move module for...
`;

IDE Integration

Configure your AI-powered IDE to include Aptos documentation:

Add the llms.txt URL to your editor's AI context sources
Reference specific chapters when asking for code assistance
Use the structured format to provide targeted context

Making Your Own Documentation LLM-Friendly

If you're building on Aptos and want your documentation to be LLM-consumable:

1. Use mdBook with llms-txt-tools

# book.toml
[output.llms-txt]
[output.llms-txt-full]

2. Structure Content Hierarchically

# Main Topic

## Subtopic

### Concept

Explanation with code examples.

```move
// Code example


### 3. Write for Both Humans and LLMs

Good documentation for LLMs:

- **Uses clear headings** that describe the content below
- **Includes complete code examples** that can be used as-is
- **Explains concepts before using them** (define before reference)
- **Uses consistent terminology** throughout
- **Provides context** for code examples (what problem they solve)
- **Lists prerequisites** when building on earlier concepts

### 4. Include Structured Data

Tables, lists, and structured examples help LLMs extract information:

```markdown
| Feature | Description | Example |
|---|---|---|
| `key` | Stored in global storage | `struct Token has key { ... }` |
| `store` | Can be nested | `struct Metadata has store { ... }` |

The Broader Aptos AI Ecosystem

The Aptos ecosystem is actively building infrastructure for AI-blockchain integration:

llms.txt support: Documentation optimized for LLM consumption
AI agent frameworks: Tools for building autonomous on-chain agents
Smart contract templates: LLM-friendly templates for common patterns
API documentation: REST and GraphQL APIs documented in LLM-friendly formats

Benefits for Developers

By using llms.txt-optimized documentation:

Faster onboarding: LLMs can provide accurate Aptos-specific guidance
Better code generation: LLMs produce more correct Move code with proper context
Reduced errors: AI assistants catch common mistakes when given comprehensive documentation
Always up-to-date: llms.txt files are generated from the latest documentation
Language-agnostic: LLMs can explain concepts in any natural language, making Aptos accessible globally

The Aptos Book