speckit-clarify

To remove ambiguity from a feature specification, you scan for underspecified goals and edge cases using a structured taxonomy. The tool asks up to five targeted questions and writes accepted answers directly into the spec to prevent downstream rework.

Specification clarification resolves missing decisions in a feature spec by classifying gaps across data models, UX flows, and quality attributes. Updating the spec in-place with these decisions ensures acceptance criteria are fully defined before implementation begins.

Yes, you need a .specify directory to clarify requirements in spec-kit projects. The clarification process requires this prerequisite directory structure to scan existing specifications, validate post-write updates, and honor before_clarify or after_clarify extension hooks.

You identify underspecified requirements by scanning an active feature specification using an ambiguity taxonomy. This classifies coverage gaps across goals, integrations, edge cases, tradeoffs, terminology, and acceptance signals to find areas that would break implementation.

Yes, a requirements clarification process should limit itself to five high-impact, decision-driving questions. This constraint focuses on resolving partial or missing items in the specification without overwhelming the user during the interactive questioning loop.