What problem does it solve? Users often ask for what they think they should want rather than what they actually need, and building on those unstated assumptions locks in the wrong solution. This Skill closes the gap between the stated ask and the real intent before any plan, spec, or code exists, when changing direction is still free. ## Core Features & Use Cases - Hypothesis-Driven Questioning: States a one-sentence hypothesis with an explicit confidence number, then asks one focused question at a time with a guess attached so the user can react instead of generating answers from scratch. - Want vs. Should-Want Detection: Probes past convention-signaling answers like "scalable" or "best practice" to surface what the user actually wants. - Confirmed Intent Restatement: Produces a structured restatement (Outcome, User, Why now, Success, Constraint, Out of scope) gated on an explicit yes, with a 95% confidence stop condition. - Use Case: A user says "build me a dashboard for our metrics." Instead of proposing chart libraries, the Skill interviews them and discovers the real need is a personal experiment tracking list, avoiding an entirely wrong artifact. ## Quick Start Tell the AI "interview me before we start" when your request is underspecified or you want your thinking stress-tested.