What problem does it solve? LLM-generated frontend code tends to repeat the same narrow layouts, produce headings that wrap into 4-6 lines, leave empty gaps in bento grids, and ship static pages without motion. This Skill enforces a rigorous design engineering process that breaks those defaults and produces varied, motion-rich, well-spaced landing pages. ## Core Features & Use Cases - Deterministic Layout Randomization: Simulates a Python RNG seeded by prompt length to select hero architectures, typography stacks, components, and GSAP paradigms so no two pages look alike. - Structural Design Rules: Enforces AIDA page structure, ultra-wide hero containers with a 2-3 line heading limit, gapless bento grids via grid-flow-dense, and massive section spacing. - Advanced GSAP Motion: Implements scroll pinning, scrubbing text reveals, image scale-and-fade effects, and card stacking with @gsap/react and ScrollTrigger. - 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 layout math. ## 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 animated React code.
