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 costs nothing. ## Core Features & Use Cases - Hypothesis-Driven Interviewing: States a one-sentence hypothesis with an explicit confidence number, then asks one focused question at a time with a guess attached so users can react instead of generating answers from scratch. - Want-vs-Should Detection: Identifies convention-signaling answers ("scalable", "best practice", "the standard approach") and probes what the user would want if they didn't have to justify it. - Confirmed Intent Output: Produces a structured restatement (Outcome, User, Why now, Success, Constraint, Out of scope) that requires an explicit yes before any downstream spec or plan is written. - Use Case: A user says "build me a dashboard for our metrics." Instead of proposing chart libraries, the Skill interviews them and discovers the actual need is a personal experiment tracker list — a completely different artifact. ## Quick Start Ask the AI to interview you about your request before building anything, for example by saying "interview me about this idea before we start."
