Google Analytics, Vercel Web Analytics, Leadsy and the TikTok Pixel stay off until you accept. The help chat starts once you have chosen. The scheduling button starts once you have chosen. Read our Privacy Policy.
AGENTS.md and llms.txt: make your code and site agent ready
How to write AGENTS.md for your codebase and llms.txt for your website so AI agents and answer engines can read them. StellarFirm is the worked example.
Making a codebase and a website agent ready means giving AI systems a clear, short, accurate place to start: AGENTS.md for the repository and llms.txt for the website. This guide shows what each file contains, how to serve Markdown copies of your pages, and how the StellarFirm site does it, so you can copy the pattern.
AGENTS.md is a plain Markdown file at the root of a repository that tells coding agents how to work there. It is documented at agents.md and read by tools such as OpenAI Codex, and Cursor documents support for it too. Think of it as a README written for an agent.
Keep it short and verifiable. A reliable layout:
Section
Content
Overview
One paragraph: what the project is and its main folders
Setup
Exact install and run commands
Checks
The commands that must pass before a change is done
Conventions
Style, naming, structure, patterns to repeat
Boundaries
What not to touch, and when to ask first
Pull requests
Size, title format, what to put in the description
Nested folders can have their own file for local rules, and the closest file to the code usually applies. Link to deeper docs instead of copying them.
PromptGenerate a first AGENTS.md
Read this repository and write an AGENTS.md with sections for overview, setup, checks, conventions, boundaries, and pull requests. Use only commands you can verify in the repository, keep it under 80 lines, and list anything you could not verify at the end.
PromptAudit an AGENTS.md
Audit our AGENTS.md. Find commands that no longer work, rules that contradict each other, and sections that are too long. Propose a shorter version and show me the changes before saving.
llms.txt is a proposed convention, described at llmstxt.org, for a Markdown file at the root of your website that gives language models a concise map of the site. It is not a guarantee of visibility, and support varies by system, but it is cheap and it forces you to decide what matters.
The proposal suggests this shape:
A title line with the site or product name.
A short summary in a quote block.
Sections of links, each with a one line description, pointing to the pages an agent should read.
Make every description a fact, not a slogan. An agent deciding whether to open a page reads that line.
PromptDraft an llms.txt
Draft an llms.txt for [website]. Start with the product name and a two sentence summary, then add sections for the main pages, documentation, pricing or plans, and contact. Give each link a plain one line description. Use only pages that exist, listed here: [list of URLs].
Agents read Markdown cleanly and HTML poorly. A Markdown copy strips navigation, scripts, and layout, so the answer to a question is a few hundred clean tokens instead of a noisy page.
Two common ways to serve it:
A parallel address, such as the same path with a .md ending.
Content negotiation: when a request sends an Accept header asking for text/markdown, answer with the Markdown version of the same page.
Do the two if you can. Keep the Markdown identical in substance to the page, because answer engines compare what they read with what is shown.
StellarFirm's public site is made for agents, and every piece below is a stable, public address.
Piece
What it gives an agent
/llms.txt
A map of the site for AI systems
/agents.md
Instructions on when to use StellarFirm and how to reach it
/openapi.json
The public API as an OpenAPI file
/docs
Documentation pages, also available as Markdown
/mcp
A public, read only MCP server
The public API is JSON with one error shape, so a program can tell what went wrong without reading a web page. See the API docs, and the MCP server page for how an agent can search the docs directly. Everything public is for reading and checking: anything that sends, deploys, or charges waits for a person's Approve inside the app.
Write AGENTS.md and test it by giving an agent a small task.
Write llms.txt from the pages you already want read.
Add Markdown copies of your key pages.
Add content negotiation for Accept: text/markdown.
If you have an API, publish an OpenAPI file and one error shape.
PromptPlan agent readiness
Look at [website or repository] and give me a prioritized plan to make it agent ready. Cover AGENTS.md, llms.txt, Markdown copies of key pages, and API documentation. For each step say what to write, how to test it, and how long it should take.
AGENTS.md is a plain Markdown file in a repository that tells coding agents how to work there: setup, checks, conventions, and boundaries. It is documented at agents.md and read by several tools.
What is llms.txt?
llms.txt is a proposed convention, described at llmstxt.org, for a Markdown file at the root of a website that gives language models a concise map of the site with links to the key pages.
Do I need two files?
They solve different problems. AGENTS.md guides agents that work inside your code, and llms.txt guides AI systems that read your public site. A product with a website and a repository benefits from each.
Does llms.txt guarantee AI search visibility?
No. It is a convention, not a guarantee, and support varies by system. Clear content, good structure, and accurate facts matter most. Treat llms.txt as a helpful extra.
Tips for Cursor and OpenAI Codex from their docs: project rules, AGENTS.md, background and cloud agents, MCP, and review habits, with copy-ready prompts.
How to design approval workflows for AI agents: why writes wait for a human, what to gate, and how to set rules, with StellarFirm Approve as the example.
What the Model Context Protocol is, how hosts, clients, and servers fit together, how to stay safe, and how StellarFirm uses MCP. With prompts to paste.