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Issue Metrics

Issue metrics provide insights into ticket management, story points, and team productivity in handling issues.

Available Metrics

string
Number of issues
string
Number of completed issues
string
Number of started issues
string
Number of backlog issues
string
Story points
string
Completed story points
string
Started story points
string
Issue cycle time
string
Issue comment interaction count
string
Number of issue comments

Completed Issues Count Metric

This endpoint provides the count of completed issues based on specified filters.

Story Points Metric

This endpoint provides information about story points.

Issue Cycle Time Metric

This endpoint provides data on issue cycle time (from creation to completion).

Parameter Notes

string
For issue metrics, the following date fields are available:
  • created_at: When the issue was created
  • started_at: When work on the issue started
  • completed_at: When the issue was completed
  • closed_at: When the issue was closed
string
Required for story point and cycle time metrics. Accepted values: SUM, MAX, MIN, AVG. Count-based metrics (issues-count, completed-issues-count, started-issues-count, backlog-issues-count, issue-comment-interactions-count, issue-comments-count) do not require an aggregation.
object
Applicable filters for issue metrics:
  • ticket_status: Filter by issue state — completed, started, backlog, etc.
  • issue_ids: Filter by specific issue IDs
  • project_ids: Filter by project IDs
  • team: Filter by team IDs
  • squad_ids: Filter by squad IDs
  • squad_levels: Filter by squad hierarchy level
  • manager_ids: Filter by manager user IDs
  • departments: Filter by department names
  • member: Filter by assignee/author merged user IDs
  • locations: Filter by employee location
  • levels: Filter by employee level

Common Use Cases

  • Sprint Velocity: Track completed story points per sprint
  • Ticket Resolution: Monitor the number of completed issues over time
  • Cycle Time Analysis: Identify bottlenecks in issue resolution
  • Backlog Management: Track the growth or reduction of backlog issues
  • Comment Analysis: Analyze communication patterns through issue comments
  • Team Performance: Compare team productivity based on issues completed and story points