Building in public feels uncomfortable. Sharing half-baked features? Even worse. But here we go.

We're adding Insights to CodeReviewr — a static analyzer that maps your codebase health before AI reviews even start.

https://vimeo.com/1136120639?share=copy&fl=sv&fe=ci

What you'll see:

• Cyclomatic complexity and file metrics

• Dependency graphs (fan-in/fan-out, circular deps)

• Unused exports and isolated files

• Issue hotspots by severity and risk score
  

That's useful on its own. But here's where it gets interesting.

When our AI reviewer has access to these Insights, it knows:

• Which files are critical vs. experimental

• Where coupling creates risk

• What your actual pain points are (not just the current PR)

• How aggressive to be based on file complexity
  

Same code review. Radically more context.

We're still testing this with a handful of early users. Expect rough edges. But the results so far are promising enough that we wanted to share.

If you're already registered at codereviewr.app, you'll get early access when we roll this out. If not, now's a good time to claim your $5 in free credits.

What would you want to see in a codebase health dashboard? Drop a comment!