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Overview

llms.txt is a standard for helping Large Language Models (LLMs) understand your documentation. Companies place it at the root of their docs site (e.g., docs.example.com/llms.txt) so AI tools can quickly find and use the right resources.
The llms.txt format is designed to be both human-readable and optimized for LLM consumption.

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Why llms.txt Exists

Modern documentation sites are often large, complex, and difficult for LLMs to navigate efficiently. Common problems include:
  • Too much content: LLMs struggle to process entire documentation sites due to context window limitations
  • Poor structure: Nested navigation and dynamic content make it hard for AI to find relevant information
  • Missing context: LLMs don’t know which pages are most important or how they relate to each other
The llms.txt format solves these problems by providing a curated, structured overview of your documentation specifically designed for AI consumption.

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How It Helps LLMs

When an AI coding assistant or chatbot needs to understand an API, it can:
  1. Fetch the llms.txt file from a known location
  2. Parse the structured content to understand the documentation hierarchy
  3. Access relevant information without crawling the entire documentation site
  4. Provide better answers based on accurate, up-to-date API information
This approach reduces the tokens needed to understand an API from hundreds of thousands to just thousands.

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Format and Structure

An llms.txt file typically consists of two main sections separated by ---:

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1. Documentation Overview

A curated list of documentation pages with descriptions: 
# API Name

> Brief description of the API and its capabilities

Important notes:
- Authentication requirements
- Key concepts
- Rate limits or restrictions

## Getting Started
- [Quickstart](url): Description of what this guide covers
- [Authentication](url): How to authenticate API requests

## Core Features
- [Feature 1](url): Description
- [Feature 2](url): Description

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2. API Reference

A comprehensive list of API endpoints with methods and descriptions: 
# API Reference

> Complete API reference with base URL and authentication details

## Resource Name
- [Endpoint Name](url): `METHOD /path` - Description of what this endpoint does
- [Another Endpoint](url): `POST /path` - Description

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Real-World Example

Here’s how Mono’s llms.txt is structured: 
# Mono Banking API Documentation

> Mono is an African open banking platform...

## Getting Started
- [Definitions](https://docs.mono.co/docs/definitions): Key terms including Account ID, Token...
- [Use Cases](https://docs.mono.co/docs/use-cases): Common implementation scenarios...

## Financial Data (Mono Connect)
- [Overview](https://docs.mono.co/docs/financial-data/overview): Introduction to Mono Connect...

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Benefits for Nigerian Fintech APIs

For Nigerian fintech companies, adopting llms.txt means:

Faster Integration

Developers using AI assistants can integrate your API faster with better context

Better Developer Experience

AI tools can provide more accurate answers about your API documentation

Reduced Support Load

Fewer basic questions as AI assistants can answer common integration queries

Competitive Advantage

Stand out as AI-friendly and developer-focused in the fintech ecosystem

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Learn More

Visit llmstxt.org to learn more about the standard and how to implement it for your own documentation.
Mintlify offers automatic llms.txt generation for documentation sites built with their platform.

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Next Steps

How to Use These Files

Learn how to use these llms.txt files with AI coding assistants like Cursor and Claude Code.

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