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Cenk KURTOĞLU
Cenk KURTOĞLU

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I built an API-callable llms.txt generator after Lighthouse added an audit

Lighthouse made llms.txt harder to ignore

In May 2026, Chrome Lighthouse documented an optional llms.txt check in its new Agentic Browsing category.

That does not mean llms.txt is a guaranteed ranking factor. Lighthouse currently marks a missing file as N/A and flags server errors when it tries to retrieve one. The practical signal is narrower: machine-readable site summaries are becoming part of the tooling used to evaluate an agent-friendly web.

The file itself is simple Markdown at the root of a domain:

# Example Product

> One sentence explaining what the product does.

## Pages
- [Documentation](https://example.com/docs): Setup and API guides.
- [Pricing](https://example.com/pricing): Plans and limits.
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The companion llms-full.txt can include the full text of the selected pages for RAG and content-ingestion workflows.

The repetitive part was the reason I automated it

Creating one file by hand is easy. Repeating the work across client sites, documentation portals, or scheduled content snapshots is not.

So I built an Apify Actor that:

  • crawls same-domain pages up to a limit you choose;
  • prefers a site's sitemap when available;
  • extracts page titles, descriptions, and main content;
  • outputs both llms.txt and llms-full.txt;
  • stores a page-level dataset that can be exported as JSON or CSV;
  • runs from the Apify UI, API, schedules, or automation workflows.

Try it here: llms.txt Generator on Apify

Example input:

{
  "websiteUrl": "https://example.com",
  "maxPages": 50,
  "includeFullText": true
}
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When the run finishes, download the generated files from the run's key-value store and review them before publishing at your domain root.

When this is useful

  • You manage several client sites and want the same repeatable workflow for each.
  • You want a clean text snapshot for a RAG pipeline.
  • You want to regenerate files on a schedule as documentation changes.
  • You need a page inventory alongside the generated files.

The project is intentionally small and open source. If you try it on a site that exposes an edge case, open an issue or leave a comment with the URL pattern and expected output.

Source: GitHub

Reference: Chrome Lighthouse llms.txt audit documentation

Top comments (1)

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Marouane K

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