speckit-clarify

To resolve ambiguities in a feature specification, you can run a structured clarification workflow that detects coverage gaps across functional, data, and UX domains, then records the accepted answers directly in the spec file. This ensures underspecified requirements become traceable bullets.

Structured clarification in requirements planning is a targeted process to uncover underspecified functional, non-functional, and edge-case gaps. It generates a prioritized queue of clarifying questions and integrates the explicit answers into the specification to ensure testable, measurable outcomes.

You document clarifications by generating a prioritized queue of questions, capturing the explicit answers, and updating the spec's Clarifications section with session-specific bullets. This maintains terminology consistency and ensures roles and acceptance criteria remain traceable.

Yes, managing specification clarifications requires a .specify directory structure and YAML frontmatter metadata in the SKILL.md file. This environment setup is necessary to execute the clarification workflow and record outcomes properly within the active feature specification.

The best way to identify edge-case gaps in requirements planning is to use a structured clarification workflow that scores ambiguity coverage across core scope, domain model, and interaction flows. This systematically targets and highlights missing edge-case definitions in the spec.