speckit-clarify

To eliminate ambiguity in feature documentation, you can use a structured taxonomy to scan specifications for gaps in logic and scope, then resolve missing decision points through interactive questioning. This ensures requirements are consistent, testable, and unambiguous.

Taxonomy-based analysis detects missing decision points by scanning feature specifications against a comprehensive category framework. It identifies underspecified areas in logic, scope, and edge cases before implementation planning begins.

The best way to clarify underspecified feature requirements is engaging with up to five high-impact interactive questions. This targeted approach resolves uncertainties efficiently while maintaining focus on critical specification gaps.

Yes, you can automatically record clarification answers directly into a specification file. Automated integration updates the source documentation and project checklists to ensure development alignment without manual copy-pasting.

Yes, this clarification process works for quality assurance workflows. It satisfies the need for high-fidelity, testable feature specifications by resolving unspecified edge cases before the implementation phase begins.

You should avoid interactive questioning when feature documentation is completely missing rather than underspecified, as this process targets existing specifications to resolve specific ambiguities rather than generating initial requirements from scratch.