speckit-clarify

To identify underspecified areas in a feature specification, run a structured clarification workflow that generates up to five targeted questions across functional scope, data models, and UX flow. This surfaces gaps early and aligns stakeholders around concrete decisions to reduce downstream rework.

The best way to track specification clarifications with stakeholders is using a session-based workflow that records decisions and rationale. It integrates accepted answers directly back into the spec within a clearly defined Clarifications section, ensuring full traceability for future reference.

You integrate stakeholder answers back into an active spec by executing the clarification workflow, reviewing generated questions, and encoding accepted responses directly into the document. The system then saves these changes automatically to maintain a single source of truth.

Yes, specification clarification explicitly covers non-functional requirements and constraints. The workflow applies structured ambiguity detection across multiple dimensions including functional scope, data models, UX flow, non-functional attributes, and system constraints to ensure comprehensive coverage.

Up to five highly targeted clarification questions are generated per feature spec. This limit ensures the workflow focuses on the most critical ambiguities across functional scope, data models, UX flow, non-functional attributes, and constraints without overwhelming stakeholders.

You can use this workflow on existing planning documents by loading the current active spec. The workflow requires executing a prerequisite check and loading the existing specification before generating targeted questions and integrating accepted answers back into the document.