What problem does it solve? Users often describe design preferences with vague words like "premium", "clean", or "modern", leaving designers and AI coding tools guessing. This Skill runs a structured designer-style interview that translates fuzzy aesthetic preferences into concrete, actionable design decisions, producing a Design-Brief.md that design tools and dev-builders can follow without ambiguity. ## Core Features & Use Cases - Guided Design Interview: Walks users through six phases (business/audience, mood/personality, references, visual tokens, core presentation, structure) using forced-choice questions anchored to real products like Linear, Notion, and Stripe. - Form-Aware Branching: Detects whether the product is a GUI app, terminal tool, conversational Agent, or hybrid, and adapts the question track accordingly (e.g., ANSI color depth and column-width degradation for terminals instead of border-radius). - Search-Augmented Reference Gathering: Performs two-pass web searches to bring current competitor and trend references into the interview rather than relying on stale memory. - Use Case: A founder says "I want a high-end feel for my CLI coding agent." The Skill asks whether that means Apple's whitespace or a dark engineering aesthetic, searches for current terminal-agent exemplars, forces trade-offs, and outputs a complete Design-Brief.md aligned with the existing Product-Spec.md. ## Quick Start Ask the AI to help you define the visual direction for your product and generate a Design-Brief.md based on your Product-Spec.md.