Jira Bug AI Analysis Assistant

Problem Addressed

Bug data in Jira is often scattered across projects, assignees, priorities, and statuses. A board view makes it hard to see long-lived backlog, repeat failure areas, or whether high-priority bugs are being resolved in time. Manual analysis can also use inconsistent rules for what counts as resolved, for example relying on resolution or status in different ways.

How It Works

The skill pulls bug data from Jira Server or Data Center and produces JSON containing metadata, aggregations, and issues. Analysis prefers the precomputed aggregation values and covers the executive summary, creation trend, priority and severity distribution, component hotspots, resolution time, assignee workload, unresolved aging, label patterns, and recommendations. It then generates a single-file HTML report: charts are drawn with inline SVG from the embedded data, the issue table supports search and sorting, and raw issue data can be exported to Excel client-side.

Boundaries and Notes

It fits projects that need regular bug-quality reviews. Confirm the Jira URL, authentication, Project Key, and, when needed, the actual Issue Type or severity field. If zero issues are returned, check the project key, date range, and issue type name first. If severity data is empty, the severity section is skipped.