speckit-clarify

Spec gap identification works by applying a structured taxonomy across functional scope, domain data model, interaction UX, non-functional attributes, and integration concerns to surface underspecified areas and generate up to five targeted clarification questions.

Clarification answers are encoded back into the spec by appending them under a dedicated Clarifications section with a daily session header, applying accepted answers to relevant spec sections, and saving changes atomically back to the active spec.

The best way to prioritize clarification questions is by building a ranked priority queue that minimizes downstream rework and aligns with planning activities across functional scope, data model, interaction UX, and non-functional quality domains.

Yes, the spec clarification workflow handles non-functional requirements and integration concerns by applying a structured taxonomy that explicitly classifies gaps across these attributes alongside functional scope, domain data model, and interaction UX.

Yes, you can generate clarification questions for an existing active feature spec by loading the active spec into the workflow, which analyzes underspecified areas and outputs a prioritized queue of up to five targeted questions.

A limitation of automated spec gap detection is that it generates a maximum of five targeted questions per session and requires manual acceptance of answers to encode clarifications back into the spec file atomically.