Playbook

llms.txt for AI discovery for open-core companies

A practical playbook for open-core marketers to improve llms.txt—with checks, fixes, and measurement.

Why llms.txt matters in open-core

open-core marketers cannot win AI shortlists on content alone if llms.txt is broken. llms.txt is a root-level orientation file that summarizes your product, key URLs, and citation preferences for AI systems—without replacing crawlable pages.

In open-core, common blockers include: Pricing is unclear to crawlers; llms.txt is missing or outdated; Share of voice lags larger incumbents. Analyst notes and G2-style roundups fill the answer gap when your own comparison pages are thin or blocked.

What to check

  1. /llms.txt present at the site root with an accurate product summary
  2. Optional /llms-full.txt for longer documentation
  3. Links to pricing, docs, and canonical product pages
  4. Consistency between llms.txt claims and live page content

open-core-specific page priorities

  • Pricing — ensure this URL is crawlable HTML with facts assistants can quote when answering “best open-core platforms for teams evaluating options”
  • Integrations — ensure this URL is crawlable HTML with facts assistants can quote when answering “best open-core platforms for teams evaluating options”
  • Use-case landing pages — ensure this URL is crawlable HTML with facts assistants can quote when answering “best open-core platforms for teams evaluating options”

Fix guidance

Ship a truthful llms.txt, keep it updated after launches, and still maintain crawlable HTML for every URL you list.

Deep dive: llms.txt for AI discovery. Industry hub: AI visibility for open-core companies.

Measure with BatSignal

  1. Run a Visibility Scan on your open-core site
  2. Inspect the pillar tied to llms.txt
  3. Ship the prioritized fixes and copy-paste deliverables
  4. Re-verify within 30 days to confirm movement

Related

FAQ

What is llms.txt for open-core companies?

llms.txt is a root-level orientation file that summarizes your product, key URLs, and citation preferences for AI systems—without replacing crawlable pages. For open-core, this shows up when buyers ask “best open-core platforms for teams evaluating options” and when AI crawlers attempt to fetch your commercial pages.

How do we improve llms.txt?

Ship a truthful llms.txt, keep it updated after launches, and still maintain crawlable HTML for every URL you list. Industry-specific must-have pages include Pricing, Integrations, Use-case landing pages.

How does BatSignal score this?

Content readiness / discovery signals. See the [methodology](/methodology) and related guide: /guides/llms-txt.