sprint-health-retro-analyzer

To generate a sprint retrospective report, this skill computes committed vs delivered story points and detects mid-sprint churn by querying Jira changelogs. It outputs a structured analysis.md file containing delivery rates, spill lists, and sprint goal attainment status.

Sprint churn tracking works by querying Jira issue changelogs for Sprint field changes to detect issues added or removed mid-sprint. It flags a churn rule violation when the net added story points exceed the net removed story points.

Analyzing sprint goal attainment requires local JSON inputs containing sprint issues, sprint metadata, and workflow-state definitions. The skill conservatively matches goal terms to issue summaries to classify goals as fully met, partially met, or not met.

Yes, this skill uses the Jira batch changelogs dependency to calculate sprint delivery rates and identify spilled items. It applies per-type done-state rules to determine which committed issues did not meet completion criteria.

Yes, sprint analysis requires reading local JSON inputs for sprint issues and metadata alongside reference law documents. These inputs provide the necessary sprint window data and workflow definitions to compute accurate delivery and churn metrics.

A limitation of automated sprint goal matching is its conservative approach, which matches goal terms to issue summaries. This may misclassify goals if issue summaries lack explicit goal terminology or if complex multi-issue dependencies exist.