What problem does it solve? Developer agents often fail because stories lack context: wrong libraries, wrong file locations, missed regressions, and vague acceptance criteria. This Skill builds a complete story file that gives the dev agent everything needed for implementation by exhaustively analyzing epics, PRD, architecture, UX docs, previous stories, and git history. ## Core Features & Use Cases - Automatic story discovery: Reads sprint-status.yaml to find the next backlog story, or accepts an explicit epic-story number like 1-2-user-auth. - Exhaustive context extraction: Analyzes epics, architecture, previous story learnings, recent git commits, and current library versions to build developer guardrails. - Quality validation checklist: Validates the generated story against a competitive review checklist that catches critical misses, enhancements, and LLM-optimization issues before finalizing. - Use Case: A team using the BMAD method runs sprint-planning, then invokes this Skill to auto-generate the next story file with full technical requirements, architecture compliance notes, and testing standards, marked ready-for-dev. ## Quick Start Ask the AI to create the next backlog story from sprint-status.yaml using the bmad-create-story workflow.
