speckit-clarify

To clarify underspecified feature specifications, you can scan the document for ambiguity across data models and edge cases, then use an interactive loop to ask up to five targeted clarification questions and encode the answers back into the spec.

Finding missing requirements in a feature spec involves running an ambiguity and coverage scan across functional, non-functional, and integration gaps to identify missing data models and constraints before generating acceptance criteria.

You update a feature spec incrementally by integrating each accepted clarification answer into the appropriate sections and saving the file safely after every response to minimize rework risk during requirements gathering.

Yes, the spec-kit clarification process supports extension hooks by optionally executing pre- and post-clarification custom actions defined within the .specify/extensions.yml configuration file.

Automated requirements clarification requires compatibility with the spec-kit directory layout to properly map accepted answers into the correct feature spec sections and validate iterative spec updates.

Feature specification clarification stops after five questions because the interactive loop uses a strict question quota to collect only high-impact decisions early, reducing ambiguity without overwhelming the user.