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sprint-health

Convert Jira sprint data into structured sprint health reports.

7|15|Updated Jan 23, 2026
Search Tags:#retrospective#jira#story points#scrum#capacity planning#risk analysis#sprint health
One-click install
npx skills add https://github.com/openshift-eng/edge-tooling --skill sprint-health-openshift-eng
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sprint-health
Source: https://github.com/openshift-eng/edge-tooling/tree/main/plugins/edge-scrum/skills/sprint-health
Command: npx skills add https://github.com/openshift-eng/edge-tooling --skill sprint-health-openshift-eng

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It turns Jira sprint data into actionable sprint health insights so your team can spot capacity risks, delivery blockers, and churn patterns early.

Core Features & Use Cases

  • Mode-based sprint analysis: run capacity (start-of-sprint), mid-sprint (burndown/blockers/goal risk), or retro (delivery summary/churn/goal analysis).
  • Jira data pipeline with guardrails: fetches sprints and sprint issues via MCP Jira tools, persists raw responses to files, transforms them into structured JSON, and delegates analysis to specialized sub-agents.
  • Rosters and story-point capacity context: applies roster rules and custom field mappings from the Edge-Scrum laws to compute capacity and committed SP.

Use case: Analyze OCPEDGE Sprint health at the end of a sprint to quantify committed story points, compare against capacity targets, and identify churn signals and goal risks for the retro.

Quick Start

Run the sprint-health skill with the mode you want (capacity, mid-sprint, or retro) to generate a dated Sprint Health report for the active or specified sprint.

Frequently Asked Questions about sprint-health

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze sprint capacity and delivery risk from Jira data?▼

You can analyze sprint capacity and delivery risk by fetching Jira sprint planning and issue data, transforming it into structured JSON, and delegating it to specialized sub-agents to generate a report on capacity, progress, and churn.

What is the difference between capacity, mid-sprint, and retro modes in sprint health analysis?▼

Sprint health analysis modes serve different sprint phases: capacity mode evaluates start-of-sprint planning, mid-sprint mode tracks burndown and blockers, and retro mode summarizes delivery, churn signals, and goal risks post-sprint.

Can I use sprint health analysis for my active OCPEDGE scrum board sprint?▼

Yes, sprint health analysis applies to OCPEDGE scrum boards by selecting your active or specified sprint, querying relevant projects, and applying custom field mappings to compute committed story points against capacity targets.

How do story points and roster rules factor into sprint capacity planning?▼

Sprint capacity planning applies roster rules and custom field mappings to calculate available capacity and compare it against committed story points, helping teams identify potential over-commitment or under-utilization early.

What Jira data is required to generate a sprint health report?▼

Generating a sprint health report requires fetching sprint issues and related custom fields via inline MCP Jira calls, persisting the raw responses to files, and transforming them into structured JSON for analysis.

When should I run a mid-sprint health analysis instead of waiting for the retrospective?▼

Run mid-sprint health analysis during the sprint to identify current burndown progress, active blockers, and goal risks, allowing the team to adjust course before the sprint ends rather than only diagnosing issues during the retrospective.

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