What problem does it solve? Turning a rough feature idea into a complete, testable specification is slow and error-prone, often producing ambiguous requirements that derail planning. This Skill converts a natural language feature description into a structured spec.md file with user scenarios, functional requirements, and measurable success criteria. ## Core Features & Use Cases - Spec Generation: Parses a feature description, extracts actors, actions, data, and constraints, and writes a specification following the spec-kit template under a numbered specs/ directory. - Quality Validation: Creates a requirements checklist and iteratively validates the spec against completeness, testability, and technology-agnostic criteria, with up to 3 clarification questions for ambiguous points. - Extension Hooks: Supports before_specify and after_specify hooks from .specify/extensions.yml for optional git branch creation and post-processing. - Use Case: A product manager types a feature idea like "add OAuth2 login for the mobile app" and receives a ready-to-plan specification with acceptance scenarios and success metrics. ## Quick Start Ask the AI to run /speckit-specify with your feature description, for example: create a specification for adding user authentication with OAuth2.
