llms.txt Examples for SaaS, E-commerce, Blogs, and Documentation Sites

An llms.txt file is a simple markdown-style file placed at the root of a website. It helps AI assistants and agents understand which pages are important and what each section of the site is for.

It should be short, accurate, and useful. Think of it as a map for machines, not a replacement for your sitemap or robots.txt.

Basic llms.txt Structure

A practical llms.txt file usually contains:

• A title.
• A one-paragraph summary.
• A section for important pages.
• A section for tools, docs, or product categories.
• Short descriptions after links.

Avoid turning it into a dump of every URL. Your XML sitemap already handles exhaustive discovery.

SaaS Example

For a SaaS website, prioritize:

• Product overview.
• Pricing.
• Documentation.
• API reference.
• Security and compliance.
• Changelog.
• Support center.

Useful entries might describe what the software does, who it serves, and where technical details live.

Pair this with Structured Data Validator and Knowledge Panel Checker so the same product identity appears in schema and page copy.

E-commerce Example

For an e-commerce site, prioritize:

• Main product categories.
• Shipping and returns.
• Size guides.
• Warranty information.
• Brand story.
• Contact and support.

Do not list every product if you have thousands of SKUs. Link to category pages and canonical product discovery pages instead.

Run Canonical URL Checker to make sure the linked pages are the preferred versions.

Blog or Publisher Example

For a blog, prioritize:

• Main topic hubs.
• Editorial policy.
• Author pages.
• Best evergreen guides.
• Recent research or data pages.
• Contact or corrections policy.

AI systems are more likely to trust content when author, dates, and editorial ownership are clear. Use Citation Readiness to review those signals.

Documentation Site Example

For docs, prioritize:

• Getting started.
• Installation.
• API reference.
• Authentication.
• Troubleshooting.
• Release notes.
• Migration guides.

Documentation sites benefit from concise descriptions because AI assistants often use docs to answer exact implementation questions.

Common Mistakes

Avoid these patterns:

• Listing hundreds of URLs with no descriptions.
• Linking to pages blocked by robots.txt.
• Using marketing claims that do not match page content.
• Forgetting to update the file after major navigation changes.
• Publishing llms.txt without validating it.

Validation Workflow

After publishing:

1. Open the file at yourdomain.com/llms.txt.
2. Confirm it returns HTTP 200.
3. Check that every listed URL is canonical and indexable.
4. Run llms.txt Checker.
5. Run AI Readiness Check on linked pages.

The best llms.txt files are boring, clear, and maintained.