Playbook
llms.txt for AI discovery for experimentation platforms
A practical playbook for product growth marketers to improve llms.txt—with checks, fixes, and measurement.
Why llms.txt matters in feature experimentation
product growth 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 feature experimentation, common blockers include: Product docs are behind login walls; robots.txt blocks AI search bots unintentionally; Comparison queries cite review sites instead of the brand. Category leaders win citations when their public pages answer buyer questions more clearly than yours.
What to check
- /llms.txt present at the site root with an accurate product summary
- Optional /llms-full.txt for longer documentation
- Links to pricing, docs, and canonical product pages
- Consistency between llms.txt claims and live page content
feature experimentation-specific page priorities
- Pricing — ensure this URL is crawlable HTML with facts assistants can quote when answering “best feature experimentation tools for teams evaluating options”
- Integrations — ensure this URL is crawlable HTML with facts assistants can quote when answering “best feature experimentation tools for teams evaluating options”
- Use-case landing pages — ensure this URL is crawlable HTML with facts assistants can quote when answering “best feature experimentation tools 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 experimentation platforms.
Measure with BatSignal
- Run a Visibility Scan on your feature experimentation site
- Inspect the pillar tied to llms.txt
- Ship the prioritized fixes and copy-paste deliverables
- Re-verify within 30 days to confirm movement
Related
- feature experimentation hub
- crawl access for feature experimentation
- content readiness for feature experimentation
- ChatGPT citations for feature experimentation
- robots.txt AI policy for feature experimentation
- llms.txt for AI discovery
- All industries
FAQ
What is llms.txt for experimentation platforms?
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 feature experimentation, this shows up when buyers ask “best feature experimentation tools 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.