What problem does it solve? Scrum Masters and engineering leads spend hours manually compiling sprint metrics, tracking burndown progress, and preparing standup summaries from scattered tool data. This Skill automates sprint analytics by parsing exports from Linear, Jira, GitHub Projects, or Azure DevOps and producing token-efficient reports for planning, standups, reviews, and retrospectives. ## Core Features & Use Cases - Sprint Analytics: Calculates velocity trends, burndown forecasts, capacity plans, priority scores, and a 0-100 sprint health score from structured sprint data. - Multi-Tool Input: Accepts JSON, CSV, and YAML exports with adapters for Linear, Jira, GitHub Projects, and Azure DevOps field mappings. - Context-Aware Output: Detects Claude AI Desktop vs Claude Code and formats reports accordingly, with optional Slack or MS Teams webhook notifications. - Use Case: Export your current sprint from Jira as JSON, then ask for a mid-sprint health check to get velocity status, blocked-item alerts, and prioritized recommendations in under 500 tokens. ## Quick Start Attach your Linear or Jira sprint export and ask the agent to generate a daily standup summary for your current sprint.