Playbook
llms.txt for AI discovery for code search platforms
A practical playbook for developer platform marketers to improve llms.txt—with checks, fixes, and measurement.
Why llms.txt matters in code search
developer platform 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 code search, common blockers include: Buyers ask AI assistants before visiting vendor sites; Category pages are thin or JS-only; Competitors appear in ChatGPT answers for “code search tools” first. Integrators and agencies sometimes get cited more than vendors when vendor sites block AI crawlers.
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
code search-specific page priorities
- Product overview — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code search tools for teams evaluating options”
- Security / trust — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code search tools for teams evaluating options”
- Comparison pages — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code search 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 code search platforms.
Measure with BatSignal
- Run a Visibility Scan on your code search 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
- code search hub
- crawl access for code search
- content readiness for code search
- ChatGPT citations for code search
- robots.txt AI policy for code search
- llms.txt for AI discovery
- All industries
FAQ
What is llms.txt for code search 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 code search, this shows up when buyers ask “best code search 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 Product overview, Security / trust, Comparison pages.
How does BatSignal score this?
Content readiness / discovery signals. See the [methodology](/methodology) and related guide: /guides/llms-txt.