maister:requirements-critic

You can validate user stories by applying a 4-point requirement validation check to detect solution-focused language, CRUD-disguised domain logic, and rigid quantifier edge cases. This process reformulates vague tickets into actionable user stories with explicit observable behavior and concurrency rules.

CRUD-disguised domain logic in requirement analysis occurs when specifications only describe database status changes without defining observable system behavior. Targeted probing questions help rebuild these vague specs into clear, testable user stories with explicit reversibility logic.

Refining product tickets into actionable user stories requires interactive requirement rebuilding to ask targeted probing questions. This transforms ambiguous specifications into clear, testable user stories featuring explicit observable behavior, concurrency rules, and reversibility logic for cross-functional teams.

Yes, requirement critique works with product tickets, user stories, specification documents, and business requirement briefs. It applies an extensible signal map to find hidden domain decisions and delivers actionable feedback with reformulated user stories for cross-functional software development teams.

Automated requirement validation focuses on identifying gaps, solution-focused language, and rigid quantifier edge cases, but it relies on the initial text provided. It cannot discover unstated business needs outside the text, requiring human collaboration to answer targeted probing questions for ambiguous requirements.

Checking problem-vs-solution framing in requirement analysis is needed when tickets focus on implementation details instead of business needs. Applying this validation prevents non-functional implementation by ensuring the requirement defines the actual business value and observable behavior.