speckit.clarify

Ambiguities in a feature specification are identified through structured scans across functional scope, data models, and UX flows. This process surfaces underspecified areas using targeted clarifications to minimize downstream rework.

Resolving spec gaps during requirements drafting is best handled by an interactive, one-question-at-a-time clarification loop. This guides decision-making and writes concise answers directly back into the spec for traceability.

A structured clarification loop improves spec traceability by automatically updating a dedicated Clarifications section within the spec. It tracks session-level answers and links them directly to the relevant spec sections.

Yes, you can review non-functional attributes and compliance considerations within a spec clarification workflow. The ambiguity scan explicitly targets these areas alongside functional scope and data models to ensure completeness.

You need to run a spec clarification process during spec drafting and review phases. It is required when you must surface ambiguities across functional scope, data models, UX flows, and compliance considerations to drive concrete clarifications.

Automated spec gap detection limits ambiguity resolution to up to 5 targeted questions per session. It requires structured questionnaire steps and existing spec sections to trace clarifications, meaning entirely unstructured documents lack sufficient context.