What problem does it solve? Turning a rough product idea into a structured, testable feature specification is slow and inconsistent. This Skill converts a natural language feature description into a complete spec.md with prioritized user stories, Given/When/Then acceptance scenarios, functional requirements (FR-XXX), measurable success criteria, and a quality checklist. ## Core Features & Use Cases - Structured Spec Generation: Creates a feature branch and directory, then writes a specification following a standard template with user stories (P1/P2/P3), edge cases, requirements, and success criteria. - Phase Separation Validation: Scans the draft for implementation details that belong in the planning phase and auto-fixes violations so specs stay technology-agnostic. - Bug-Fix Intent Detection: Analyzes the description to distinguish bug fixes from new features and suggests the appropriate workflow. - Use Case: A product manager types a feature idea like "add user authentication with OAuth" and receives a ready-to-review spec.md with acceptance scenarios, a requirements checklist, and the recommended next workflow step. ## Quick Start Ask the AI to run /iikit-01-specify followed by a plain-language description of the feature you want to specify.