speckit-clarify

You can identify underspecified areas in a feature specification by running a structured ambiguity scan that assesses functional goals, data models, UX flows, and integration points to surface gaps and generate targeted clarification questions.

You record clarifications and decisions directly in a spec by creating a dedicated Clarifications section with daily session tagging and traceable bullets for each accepted answer during the interactive clarification loop.

The best way to update requirements with a prioritized clarification queue is to generate up to five targeted questions, accept concise answers, and apply those accepted answers directly back into the spec after each interaction.

Yes, you can validate spec updates against an optional post-update quality checklist that re-evaluates the specification and surfaces outstanding risks after applying accepted clarifications.

Yes, spec clarification works within a spec-kit project structure by detecting and loading extension hooks and governance constraints from the .specify/ directory to guide the clarification flow.