AgentRef publishes machine-readable documentation endpoints that follow the llms.txt standard. These endpoints let you feed the full AgentRef documentation into any AI assistant as context — enabling more accurate answers, code generation, and integration help.
Endpoints
| URL | Description | Best For |
|---|
https://www.agentref.co/docs/llms.txt | Concise overview of all documentation pages with links | Quick orientation, smaller context windows |
https://www.agentref.co/docs/llms-full.txt | Complete documentation content in plain Markdown | Full context, comprehensive answers |
What is llms.txt?
The llms.txt standard provides a way for websites to publish their content in a format optimized for large language models. Instead of making an LLM crawl HTML pages, you give it a single plain-text file containing everything it needs.
llms.txt — A structured index of all documentation pages with titles, descriptions, and URLs. Think of it as a table of contents for AI.llms-full.txt — The complete documentation rendered as plain Markdown in a single file. Every page, every code example, every table — all in one response.
Using with AI Assistants
Claude
Paste the URL directly in a conversation:
Read https://www.agentref.co/docs/llms-full.txt and then help me set up
an affiliate program with 20% recurring commission.
- Create a new Claude Project
- Add
https://www.agentref.co/docs/llms-full.txt as a knowledge file
- All conversations in the project will have full AgentRef context
ChatGPT
Use the URL in a prompt or with Browse mode:
Fetch https://www.agentref.co/docs/llms-full.txt and use it as context.
I need to integrate AgentRef webhooks into my Express.js app.
Cursor
Add the docs to your project context in .cursorrules or paste the URL:
@https://www.agentref.co/docs/llms-full.txt
Help me create a conversion tracking integration using the AgentRef Node SDK.
Tips for Optimal Context Usage
Choose the right endpoint
- Use
llms.txt when you only need the AI to know what documentation exists and where to find it. This is lighter on tokens and works well for navigation questions.
- Use
llms-full.txt when you need the AI to have deep knowledge of AgentRef’s APIs, SDKs, and features. This gives the best answers but uses more context window.
Scope your questions
Even with full documentation context, you’ll get better results by being specific:
# Good
"Using the AgentRef Node SDK, show me how to list pending payouts
and create a payout for each affiliate that meets the threshold."
# Less good
"Help me with AgentRef."
Combine with code context
For integration tasks, give the AI both the AgentRef docs and your own code:
I'm building a Next.js app. Here's my current webhook handler:
[your code]
Read https://www.agentref.co/docs/llms-full.txt and help me verify
the webhook signature correctly.
Use llms.txt for discovery
When you are not sure which part of the docs you need, start with llms.txt:
Read https://www.agentref.co/docs/llms.txt and tell me which pages
are relevant for setting up fraud detection.
llms-full.txt for the complete context.
Programmatic Access
You can fetch these endpoints from your code for automated workflows:
// Fetch the full docs as context for an LLM call
const response = await fetch('https://www.agentref.co/docs/llms-full.txt');
const docsContext = await response.text();
// Use as system prompt context
const messages = [
{
role: 'system',
content: `You are an AgentRef integration assistant. Here is the full documentation:\n\n${docsContext}`
},
{
role: 'user',
content: 'How do I set up webhook signature verification?'
}
];
Content Updates
The llms.txt endpoints reflect the latest published documentation. When docs are updated, the endpoints serve the new content immediately — no caching delay.
Bookmark https://www.agentref.co/docs/llms-full.txt in your AI tools. Whenever you’re building an AgentRef integration, load it as context for the most accurate, up-to-date assistance.
