Automation

Overview

The Automation page provides visibility into automated pull request activity across your repositories. Use this page to review which automations are running, how often they are triggered, and how automation activity changes over time.

Automation data helps engineering teams understand how automated actions, such as adding labels, requesting reviews, approving pull requests, or adding comments, are being applied across pull requests.

Automation Page Overview

The Automation page includes a summary chart and automation cards.

• Actions over time: Shows the number of pull requests with automation actions during the selected time period.
• Automation cards: Show individual automations, the action performed, the number of pull requests processed, and the repositories where the automation ran.
• Filters: Allow you to narrow the page by action type, team, time range, repository, or automation name.

Actions Over Time

The Actions over time chart shows automation activity grouped by action type. Each color represents a different automation action, such as:

• Add Comment
• Add Label
• Approve
• Code Review
• Describe Changes

Hover over a bar segment to view the exact number of pull requests affected by that action on a specific date.

Automation Cards

Each automation card represents a specific automation rule or automation-driven action. The card shows:

• Automation name: The name of the automation, such as LinearB AI Review, Estimated Time to Review, or Tag Claude in PR.
• Action type: The action performed by the automation, such as adding a label, reviewing code, or describing changes.
• PRs processed: The number of pull requests processed by that automation in the selected time period.
• Repository coverage: The number of repositories where the automation ran, out of the total number of repositories available in the selected scope.
• Trend chart: A time-based view of how many pull requests were processed by the automation.

Filtering Automations

Use the filters at the top of the page to focus the Automation page on the relevant scope.

• Action filter: Filter automations by action type.
• Team filter: View automation activity for a specific team or for all teams.
• Date range: Select the week or time period you want to review.
• Search: Search for a specific automation by name.
• Sort: Sort automations, for example by popularity.

Understanding Automation Counts

Automation counts represent pull requests processed by automations within the selected filters and time range.

These counts may not always match pull request counts shown in other LinearB areas, such as gitStream, pull request metrics, or repository-level dashboards. Differences can occur because each area may use a different scope, filter, team membership, repository configuration, or data source.

Troubleshooting PR Count Differences

If the Automation page shows different pull request counts than gitStream or another LinearB view, check the following:

1. Confirm the Repository Is Monitored

Go to the relevant Git integration settings and confirm that the repository is monitored by LinearB.

If the repository is not monitored, LinearB may not include its pull request activity in automation reporting.

2. Confirm the User Belongs to a Team

Automation data can be affected by team scope. If a user is not assigned to a team, their pull request activity may not appear as expected when viewing team-filtered data.

To check this, go to:

Settings → Users & Teams → Users

Search for the user and confirm that they are assigned to the relevant team.

3. Merge Duplicate User Accounts

If the same developer appears under multiple Git accounts, email addresses, or usernames, use Merge Account to consolidate the user’s activity.

To merge accounts:

1. Go to Settings → Users & Teams → Users.
2. Search for the user.
3. Click the three-dot menu next to the relevant user.
4. Select Merge Account.

Merging duplicate accounts helps ensure that pull request activity is attributed to the correct developer and team.

Best Practices

• Review automation activity weekly to confirm that automations are running as expected.
• Use the action filter to understand which automation types are used most often.
• Check repository monitoring before investigating automation count discrepancies.
• Keep user accounts merged and assigned to the correct teams to improve reporting accuracy.