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. ## 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 the user can react instead of generating answers from scratch. - Want-vs-Should Detection: Identifies convention-driven or sophistication-signaling answers ("scalable", "best practice") and probes what the user would want without justification. - Confirmed Intent Output: Produces a structured restatement (Outcome, User, Why now, Success, Constraint, Out of scope) gated on an explicit yes, with optional persistence to docs/intent/. - 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, avoiding building the wrong artifact. ## Quick Start Ask the AI to interview you about your request before writing any plan or code, for example by saying "interview me about this feature idea before we start."