Dataset: Issues & Pull Requests
Entity: Pull Requests, Issues
Field ID: recommended_actor_usernames
Type: List of text values
Description: The list of people's usernames who are expected to perform the recommended action. Note that usernames are app-specific.
Source: Calculated
Transformation logic:
The list of actors depends on the recommended action.
The recommended action field is a part of the Issues & Pull Requests dataset. It provides an estimated course of action for each issue and pull request based on their context.
For recommended actions on pull requests, the mapping of actions to actors is as follows:
Assign reviewer: Author
Assign missing reviewers: Author
Fix build: Author
Fix code: Author
Merge: Suggested Mergers
None: Empty array
Rebase: Author
Review: Requested reviewers
For recommended actions on issues, the mapping of actions to actors is as follows:
Close: Assignees
Implement: Assignees
None: Empty array
Wait for implementation: The list of authors from resolving pull requests. Resolving pull requests are pull requests that reference the issue via auto-closing keywords.
From: |
|
Github (PRs, Issues) | Calculated |
Gitlab (PRs, Issues) | Calculated |
Bitbucket (PRs) | Calculated |
Azure DevOps (PRs, Issues) | Calculated |
JIRA (Issues) | Calculated |
ClickUp (Issues) | Calculated |
Trello (Issues) | Calculated |
Reporting Use Cases
The Recommanded Actors field is a powerful computed attribute that identifies the specific individuals expected to perform the Recommended Action on an item. This makes it the ideal field for creating highly personalized and actionable "To-Do" lists and for analyzing team workload with unparalleled precision.
Creating Personalized "My Action Items" Widgets: This is the primary and most powerful use of this field. It allows you to build a dynamic list of tasks that are relevant right now for the person viewing the dashboard.
By applying a filter where
Recommanded Actors includes me, you can create a widget that automatically shows each user only the items where they are the ones expected to act next. This cuts through the noise of all assigned items and focuses on immediate responsibilities.
Analyzing Actionable Workload Distribution: To understand who is responsible for moving work forward at any given moment, you must use the
FLATTENfunction to report on each recommended actor individually.Action Items per Person: You can create a bar chart showing the number of pending actions for each team member. Use a custom formula dimension like
FLATTEN(recommended_actor_usernames)withCOUNT()as the metric to see who has the most items waiting for their input.Workload by Action Type: For a more detailed view, you can create a stacked bar chart with
FLATTEN(recommended_actor_usernames)as the first dimension andRecommanded Actionas the second. This will show not just how many actions each person has, but also what kind of actions they are (e.g., John has 5 items to "REVIEW" and 2 items to "MERGE").
Identifying Blocked Teams: The absence of a recommended actor on an open item can signal a process gap.
A report filtered where
Recommanded Actors length = 0 and state = "OPEN"can help you find items that are stalled because ownership of the next step is unclear (e.g., a PR that needs a reviewer, but no one has been assigned).