speckit-clarify

To clarify ambiguous requirements in a feature spec, this Skill runs a structured coverage scan across functional scope, data models, and edge cases, then prompts up to 5 targeted questions to resolve ambiguities and encode the answers back into the spec.

You can identify underspecified areas in an engineering spec by scanning for ambiguities across interaction flows, non-functional quality attributes, and integration dependencies. The Skill maintains an in-memory representation to surface gaps and prompt focused clarifications one at a time.

The best way to capture clarification answers is to append them to a persistent Clarifications section and apply accepted answers directly to relevant spec sections like Functional Requirements and Edge Cases. The Skill saves these integrations after each answer to minimize spec drift.

Yes, you can use this spec clarification workflow within a spec-kit project structure. The Skill is specifically designed to apply within that environment, maintaining per-session history and updating the active spec iteratively until all ambiguities are resolved.

The spec ambiguity scan covers functional scope and behavior, domain and data models, interaction and UX flow, non-functional quality attributes, integration dependencies, edge cases, constraints, tradeoffs, and terminology.

The spec clarification workflow generates a prioritized queue of up to 5 candidate clarifications. It operates in a one-question-at-a-time loop, capturing answers and updating the spec after each response until the ambiguities are resolved.