Skip to main content

AI Code Review Metrics

Track how your team is using gitStream AI—see how many pull requests are reviewed, how often suggestions are accepted, and how many lines of code are improved through AI-assisted reviews.

Steven Silverstone
Updated by Steven Silverstone

This article provides detailed descriptions of the four core usage metrics available on the AI Code Review dashboard in LinearB. These metrics help teams measure the adoption and activity of AI-assisted code review workflows.

Reviewed PRs

This metric counts the number of pull requests that received at least one AI-generated review from gitStream.

  • Each line in the graph represents one day.
  • Hover on a specific point in the line to view a list of all reviewed PRs for that date.
  • This metric helps track daily AI engagement across repositories.

Total Reviews

This card displays the total number of review comments added by gitStream across all PRs.

  • Includes all review events, regardless of whether the suggestion was accepted.
  • Indicates how actively gitStream is contributing to the review process.

Total Suggestions Accepted

This metric reflects how many AI-generated code suggestions were accepted and committed by developers.

  • Accepted suggestions reflect alignment between AI guidance and developer decisions.
  • Hover over chart points for daily counts.

Total Lines Accepted

Shows the total number of code lines that were both suggested by gitStream and committed.

  • Measures the volume of AI-generated code actually adopted.
  • Useful for understanding the scope of changes introduced via AI.

Interactivity and Filters

  • All charts support filtering by repository, date range, or contributor.
  • Use the share icon to export a snapshot of the chart for collaboration.
  • Hover over individual bars or lines to view relevant PRs and their review context.

How did we do?

AI Code Review Findings

Active Branches Metric

Contact