humans.txt

The humans.txt standard: what it is, how to create it, and whether AI agents and crawlers use it.

2026-02-01

What is humans.txt?

humans.txt is a plain-text file placed at the root of a site (/humans.txt) that describes the people behind the project: authors, designers, developers, contributors. It was created in 2012 by Abel Cabans and Juanjo Bernabeu, inspired by robots.txt.

Example:

/* TEAM */
Developer: Jane Smith
Site: https://example.com
Twitter: @janesmith
Location: Paris, France

/* THANKS */
Name: John Doe

/* SITE */
Last update: 2026-01-15
Standards: HTML5, CSS3
Components: Next.js, Tailwind CSS
Software: VS Code

Is it useful for AI agents?

Directly, humans.txt carries little weight for AI agents. Crawlers do not parse it automatically, and there is no consensus standard for machines.

However, it presents two indirect benefits:

  1. Authorship signal: If the file is structured and consistent, it can be parsed by agents specifically looking to identify a site's maintainers. This reinforces the concept of EEAT (Experience, Expertise, Authoritativeness, Trustworthiness), valued by Google and increasingly by AI systems.

  2. Complement to llms.txt: Alongside llms.txt (which targets AI agents), humans.txt completes the picture of human identity behind the content.

Comparison: humans.txt, robots.txt, llms.txt

File Audience Purpose
robots.txt Crawlers (bots) Access permissions
llms.txt AI agents and LLMs Site structure, key links, content policy
humans.txt Human visitors and SEO tools Team identity and site credits
security.txt Security researchers Responsible disclosure contacts

How to add it

Create a static file /public/humans.txt in your project:

/* TEAM */
Lead Developer: [name]
Contact: contact [at] yourdomain.com
Site: https://yourdomain.com

/* SITE */
Last update: 2026-02-01
Language: English
Standards: HTML5, CSS3, JSON-LD

Referencing it in HTML

To signal the file to browsers and tools, add in your <head>:

<link rel="author" href="/humans.txt" />

Recommendation

humans.txt is a low-effort practice. Its real value lies in combining it with proper EEAT signals:

  • Schema.org Person or Organization structured data
  • Author pages with biography
  • Visible social links and credentials

For AI agent optimization, prioritize llms.txt and JSON-LD. Add humans.txt as an additional identity signal.