clarify

To clarify vague requirements into precise specifications, you apply a phased workflow that captures initial prompts, decomposes them, and researches codebase evidence to resolve ambiguities. This methodology uses persistent questioning and tiered decision handling to drive actionable product specs.

Handling subjective feature trade-offs during UX scoping requires coupling codebase exploration with best-practice research to generate evidence-based decision points. This approach classifies decisions into tiered resolutions and uses advisory notes to guide teams through ambiguous product requirements.

Codebase research evidence supports requirement analysis by providing concrete references that validate decision points during the clarification workflow. It couples technical findings with best-practice guidance to classify tiered resolutions, ensuring vague requirements become precise, actionable specifications with cited evidence.

Yes, you can use persistent questioning to surface ambiguities in product requirements by driving advisory collaboration and consensus. This technique works alongside codebase research to identify decision points and classify tiered resolutions for precise specifications.

Requirement clarification works without hardcoded codebase dependencies, but utilizing codebase evidence significantly enhances the precision of feature trade-off resolutions. The workflow integrates available codebase research with best-practice guidance to support tiered decision handling and produce actionable specifications.