speckit-clarify

To eliminate ambiguity in feature specifications, you can use a structured taxonomy-based scan that evaluates functional, technical, and non-functional requirements to identify gaps and missing decision points. It then guides you through an interactive questioning loop to finalize requirements.

The best way to clarify missing requirements in a GitHub Spec-Kit project structure is to execute an interactive clarification loop that targets high-impact gaps. This process automatically updates your feature specification file and re-validates project checklists for consistency.

A taxonomy-based scan identifies untestable requirements by evaluating feature specifications against a comprehensive taxonomy covering functional, technical, and non-functional categories. It systematically detects missing decision points and records clarifications directly into the project documentation.

Yes, you need access to constitution memory to maintain architectural alignment when clarifying specs. Along with the project root and specification files, it ensures that identified requirements remain testable, complete, and consistent with the overall project architecture.

Yes, specification clarification can automatically update project checklists and documentation. After resolving ambiguities through the interactive questioning loop, the process directly records clarifications into the feature specification file and re-validates related checklists.