What problem does it solve? When a game project ships, hits a major milestone, or gets cancelled, teams often lose the lessons learned because reflection is unstructured and memory is selective. This Skill runs a five-phase post-mortem workflow that turns git history, sprint data, and team reflection into concrete, actionable lessons for the next project. ## Core Features & Use Cases - Automated Data Collection: Pulls commit counts, contributor stats, file churn, tag history, and issue data directly from git and GitHub CLI to ground the analysis in facts. - Five-Phase Workflow: Guides the analysis through data collection, structured team reflection, pattern analysis, lesson extraction, and action item archival. - Structured Output: Produces a Post-Mortem Report with quantitative overview tables, root-cause findings, categorized lessons, and trackable action items with owners and deadlines. - Use Case: After shipping a vertical slice or cancelling a project, run the post-mortem to identify systemic estimation, scope, and communication patterns, then archive the report in production/milestones/ so the next project starts with those lessons already applied. ## Quick Start Ask the AI to run a post-mortem on the completed project or a named milestone, for example by saying run a post-mortem for the alpha milestone.
