speckit-clarify

You clarify ambiguous feature specs by generating up to five targeted questions that identify missing constraints and edge cases. The workflow detects underspecified areas across functional, data, UX, and non-functional dimensions to reduce ambiguity before planning.

Identifying missing acceptance criteria involves applying a structured taxonomy for ambiguity to prompt focused clarification questions. This process highlights concrete constraints and edge cases required for downstream planning.

Keeping a single source of truth requires updating the specification after each accepted answer. The workflow automatically integrates responses directly into the spec to ensure all constraints and acceptance criteria remain centralized.

Yes, you can use structured questions to cover edge cases across functional, data, UX, and non-functional dimensions. The workflow prioritizes these clarification questions by impact to address the most critical ambiguities first.

If a feature spec has more than five underspecified areas, the workflow poses a maximum of five targeted questions. It prioritizes these questions by impact to resolve the most critical ambiguities and constraints first.

Clarifying a specification does not require any external dependencies. The workflow operates independently to identify ambiguities, generate acceptance criteria, and update the spec without needing additional tools or components.