Does a GitHub README help AI recommend you?

For any developer-facing product, library or API, the GitHub README is one of the highest-leverage AI-visibility assets you have. GitHub is among the most heavily-crawled and trained-on corpora, and the README is where a model learns — in the exact language developers use — what your tool is, what problem it solves, and how to use it. A clear README with a crisp one-line description, real usage examples, and honest positioning against alternatives feeds directly into how assistants describe and recommend solutions in your space. A vague or empty README leaves the model guessing, or reaching for a better-documented competitor.

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FAQ

Why does a README carry so much weight for dev tools?Because it's canonical, heavily-crawled, and written in developer language. When a model learns what your tool does and when to suggest it, the README is a primary source. Clear positioning and examples there shape how you get described and recommended.

What should a README include for AI visibility?A one-sentence description of what it is and who it's for up top, a quickstart with real code, concrete use cases, and honest notes on how it compares to alternatives. Specificity is what lets a model recommend you for the right query instead of hedging.

How do I check if AI recommends my tool?Run a free Cited scan — it checks the AI-search readiness signals on your website (crawler access, llms.txt, structured data and answer-ready content) and lists the fixes to make first.

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