What problem does it solve? LLMs produce repetitive, low-quality frontend designs: narrow containers causing 6-line wrapped headings, gappy bento grids, cheap meta-labels, invisible button text, and identical left/right layouts. This Skill enforces a rigorous design engineering discipline to break those defaults. ## Core Features & Use Cases - Deterministic Layout Randomization: Simulates Python RNG selection of hero architectures, typography stacks, components, and GSAP paradigms so no two pages repeat the same layout. - Strict Structural Rules: Enforces AIDA page structure, 2-3 line H1 limits with wide containers, gapless bento grids via grid-flow-dense, and massive section spacing. - Advanced GSAP Motion: Implements scroll pinning, scrubbing text reveals, card stacking, and image scale/fade effects with real GSAP and ScrollTrigger code. - 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 sections, and a pre-flight design plan verifying all constraints. ## Quick Start Ask the AI to build a landing page for your product using the gpt-taste skill and it will output a verified design plan followed by the full UI code.
