What problem does it solve? Users often describe solutions instead of real problems, leading teams to build features that treat symptoms rather than root causes. This Skill digs beneath surface-level feature requests, challenges patch-style solutions, and translates validated needs into prioritized, testable requirement lists. ## Core Features & Use Cases - Root-Cause Analysis: Infers the user's true motivation and scenarios, identifies "solutions disguised as requirements", and critically evaluates whether a proposed feature actually solves the underlying problem. - Visual Change Comparison: Produces "current vs expected" diagrams (Mermaid flows, ASCII UI mockups) during the analysis phase so stakeholders can spot misunderstandings early. - Structured Requirement Translation: Outputs prioritized requirement lists (P0/P1/P2) with dependencies, acceptance criteria, feasibility assessment, and complexity scoring to recommend the next step (quick implementation, design, or work breakdown). - Use Case: A user says "add a progress bar to our slow export feature". The Skill reveals the real pain is uncertainty during long waits, recommends async export with completion notification as the root fix, and delivers a full requirement report with diagrams and verification metrics. ## Quick Start Ask the AI to analyze a feature request like "our export is too slow, add a progress bar" and confirm or correct its inferred requirement understanding.
