What problem does it solve? LLM-generated frontend code tends to look templated: purple gradients, centered heroes, three equal feature cards, and generic glassmorphism. This Skill forces the agent to read the brief first, infer the right design direction, and apply strict anti-default rules so the output does not look like generic AI slop. ## Core Features & Use Cases - Brief Inference and Design Read: Analyzes page kind, vibe words, references, audience, and constraints, then declares a one-line design direction before writing code. - Three-Dial Configuration: Tunes DESIGN_VARIANCE, MOTION_INTENSITY, and VISUAL_DENSITY based on the brief, with presets for SaaS landings, portfolios, editorial sites, and public-sector services. - Design System Mapping: Selects official packages (Fluent, Material, Carbon, Polaris, shadcn/ui, Tailwind v4) when the brief matches a real system, and gives honest implementation guidance for aesthetics like glassmorphism, bento, and brutalism. - Hard Layout and Pre-Flight Rules: Enforces hero viewport fit, eyebrow restraint, CTA contrast and single-intent rules, palette locks, and layout-family diversification. - Use Case: Ask for a redesign of a premium consumer landing page and receive a Next.js + Tailwind v4 implementation with a non-default palette, real image assets, and a passing pre-flight audit. ## Quick Start Redesign my landing page so it feels like a Linear-style minimalist SaaS site and does not look AI-generated.
