The file goes stale after launch
A hand-written list can miss new product pages, guides, and changed URLs. Agents then receive an outdated view of the website.
llms.txt Template for Next.js marketing websites.
This llms.txt template for Next.js gives your marketing site a clear, maintained guide for AI agents. Launch it inside the Agentic Website Template with server-rendered pages, metadata, a sitemap, robots rules, structured data, and release checks that help your team keep every discovery path current.
A useful llms.txt depends on the website behind it.
The llms.txt proposal gives agents a concise map of a website. That map becomes useful when its links lead to clear, accessible pages and stay current as the site changes. Your team needs a publishing system that maintains the file alongside the content it describes.
Use the templateLinked pages lack a clear answer
A tidy list still leads to weak results when the destination pages hide important copy in client-side interactions or leave the topic unclear.
Discovery files tell different stories
The llms.txt file, sitemap, robots rules, metadata, structured data, and site navigation all need to reflect the same public website.
Launch llms.txt as part of a complete website foundation.
The Agentic Website Template gives your team the file and the publishing system around it. AI coding agents can update the site guide, public pages, and search setup in the same repository, while your team reviews the result before each launch.
See the three ways to use the templateGive agents a short, useful map of the website.
Guide AI agents
The included llms.txt follows the proposal's Markdown structure with a site summary, clear guidance, and described links to important resources. It stays concise so an agent can quickly choose what to read next.
- Describe the website in plain language
- Group important links by purpose
- Explain what an agent will find on each page
Lead agents to pages they can read and understand.
Make the links useful
Important copy and links render in HTML, giving web crawlers and agents direct access to the page topic, supporting details, and next steps.
- Render key content on the server
- Use clear headings and page structure
- Keep navigation links available in HTML
Maintain llms.txt beside the sitemap and navigation.
Keep routes connected
The sitemap lists public URLs for search engines while llms.txt curates the pages most useful to an AI agent. Shared route data helps your team keep both views aligned as the website grows.
- Generate the sitemap from public routes
- Curate the most useful links for agents
- Update internal links when routes change
Edit the website and its agent guide together.
Update with your agent
Claude Code, Codex, Cursor, or another coding agent can read the repository instructions, make the requested page change, and update llms.txt when that page belongs in the guide.
- Keep website guidance in the repository
- Ask the agent to update related discovery files
- Review one change set before publishing
Catch broken links and missing updates before launch.
Check every release
The launch workflow checks public routes, metadata, discovery files, and production settings. Your team can confirm that llms.txt returns correctly and points to live, useful pages.
- Confirm the root file returns successfully
- Check every curated URL
- Review discovery files after route changes
Add an accurate llms.txt while you build the website.
Start with the pages that explain your company, product, and useful resources. Then give agents a concise route into that content and keep the guide tied to the same launch process.
Start with the Agentic Website Template- 01
Open the template with your coding agent
Ask Claude Code, Codex, or Cursor to clone the repository and read README.md and AGENTS.md before making changes.
- 02
Build the pages agents should find
Add your product, use-case, migration, and supporting content with clear server-rendered answers and useful internal links.
- 03
Write a concise site guide
Describe the website, group the most useful pages, and add short notes that help an agent choose the right link.
- 04
Test the guide before publishing
Open /llms.txt, follow each link, and ask an agent common questions using the file as its starting point.
Give AI agents a maintained path into your website.
A clear starting point for agents
The file explains the website and points to the pages most useful for understanding your product, content, and next steps.
Discovery files that stay aligned
The sitemap, robots rules, structured data, navigation, and llms.txt can change with the same repository and release.
A website ready for continued publishing
Your team can add pages with an AI coding agent and carry the same content, search, and launch rules into each update.
llms.txt template for Next.js questions.
Straight answers for teams adding llms.txt to a Next.js marketing website.
What is an llms.txt file?
llms.txt is a proposal for a Markdown file that gives AI agents a concise overview of a website and links to useful resources. The proposed structure starts with the site name and can include a summary, guidance, and grouped link lists.
Where does llms.txt go in a Next.js project?
A static llms.txt file can live in the Next.js public folder, which serves it from /llms.txt at the site root. Your team can also generate a text response when the content needs to come from route data.
Does llms.txt guarantee visibility in ChatGPT or other AI tools?
AI visibility and citations still depend on whether a system can access the site, chooses to use the file, understands the linked pages, and considers the content useful for a query. llms.txt gives participating agents a clearer route into that content.
How is llms.txt different from robots.txt and sitemap.xml?
robots.txt communicates crawl permissions, sitemap.xml lists public URLs for search engines, and llms.txt offers AI agents a curated explanation with selected links. A complete website can use all three for their separate roles.