Credit the people behind your website
humans.txt is a small, public text file at example.com/humans.txt that says who built a website and what they built it with. The idea comes from the humanstxt.org initiative: robots.txt speaks to machines, humans.txt speaks to people. It is quick to make, costs nothing to host and is a friendly signal of the real team behind a site. This generator builds one from a simple form, live in your browser.
How to use it
- Add each person with their role and name, and optionally a contact, a website or social profile and a location.
- Add thanks for anyone you want to credit, one name or link per line.
- Describe the site: last update, language, doctype, standards, components, software and editor.
- Download humans.txt, upload it to your site's root, and add the link tag to your pages.
The format
The file uses three comment-style headings, each followed by tab-indented Field: value lines. Every block is optional.
/* TEAM */
Developer: Sam Lee
Contact: sam [at] example.com
From: Dubai, UAE
/* THANKS */
Name: The open source community
/* SITE */
Last update: 2026/10/19
Language: English
Standards: HTML5, CSS3
Components: Next.js, ReactThen add this inside the <head> of your pages so people and tools can find the file:
<link type="text/plain" rel="author" href="/humans.txt" />Good practice
- It is public. Only include details you are happy for anyone to read. Writing an email as "name [at] example.com" slows down address-harvesting bots.
- Keep the Last update date current when the team or the stack changes.
- Serve it as plain text from the root of the site, not from a subfolder.
- Do not expect a ranking boost. Search engines do not use humans.txt as a ranking signal. Its value is transparency and credit.
humans.txt, robots.txt and llms.txt
| File | Audience | Purpose |
|---|---|---|
| robots.txt | Crawlers | Which URLs they may fetch |
| llms.txt | AI models and agents | A map of your most useful content |
| humans.txt | People | Who built the site and how |
Related tools
Check how crawlers read your rules with the robots.txt tester, build a map for AI with the llms.txt generator, and give coding agents project instructions with the AGENTS.md generator.