What problem does it solve? LLMs repeatedly produce generic, cramped frontend layouts with narrow headings, gappy bento grids, invisible button text, and static pages. This Skill enforces a rigorous design engineering workflow that breaks those defaults and produces varied, motion-rich, editorial-grade UI code. ## Core Features & Use Cases - Deterministic Layout Randomization: Simulates a Python RNG seeded by prompt character count to select hero architectures, typography stacks, components, and GSAP paradigms so no two outputs repeat. - Strict Layout Rules: Enforces AIDA page structure, 2-3 line H1 limits via wide containers, gapless bento grids with grid-flow-dense, and massive section spacing. - Advanced GSAP Motion: Implements ScrollTrigger pinning, scrubbing text reveals, image scale-and-fade, and card stacking animations. - Use Case: Ask for a landing page for a SaaS product and receive a complete React/Tailwind page with a cinematic hero, dense bento feature grid, pinned scroll gallery, and a pre-flight design plan verifying every layout constraint. ## Quick Start Use the gpt-taste skill to build a landing page for my product with a cinematic hero, bento grid, and GSAP scroll animations.