Playbook
llms.txt for AI discovery for code review platforms
A practical playbook for engineering productivity marketers to improve llms.txt—with checks, fixes, and measurement.
Why llms.txt matters in code review
engineering productivity 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 review, 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 review tools” first. Vertical specialists with strong llms.txt and structured data often punch above their SEO traffic in AI answers.
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 review-specific page priorities
- Solutions by persona — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code review tools for teams evaluating options”
- Industry examples — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code review tools for teams evaluating options”
- Support docs — ensure this URL is crawlable HTML with facts assistants can quote when answering “best code review 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 review platforms.
Measure with BatSignal
- Run a Visibility Scan on your code review 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 review hub
- crawl access for code review
- content readiness for code review
- ChatGPT citations for code review
- robots.txt AI policy for code review
- llms.txt for AI discovery
- All industries
FAQ
What is llms.txt for code review 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 review, this shows up when buyers ask “best code review 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 Solutions by persona, Industry examples, Support docs.
How does BatSignal score this?
Content readiness / discovery signals. See the [methodology](/methodology) and related guide: /guides/llms-txt.