Comparison
Design Taste Frontend (leonxlnx) vs GPT Taste (leonxlnx)
Design Taste Frontend (leonxlnx) and GPT Taste (leonxlnx) are both Visual skills, so an agent choosing between them is matching on descriptions that overlap. Here is where they actually diverge.
Design Taste Frontend
leonxlnx
Builds the persuasion surface of a website - a launch page, a personal or studio portfolio, a visual overhaul of a site that already exists - and ships the working page, steered hard away from the templated look a model reaches for by default: a stated aesthetic read of the brief, a committed type and colour language, and motion that has to justify itself. Its scope stops at surfaces meant to be scrolled and read; dashboards, data grids, and multi-step wizards are handed off to a product-UI system rather than restyled.
4 scenarios in the bank answer to it
GPT Taste
leonxlnx
The same push away from templated pages, aimed at Codex and GPT because they drift differently: it forces a fresh pick of hero shape, type stack and scroll choreography each build instead of reaching for last time's, and leans hard on scroll-driven motion. What separates it from the general version is the model it corrects, not the work it covers.
1 scenario in the bank answers to it
What is the difference between Design Taste Frontend (leonxlnx) and GPT Taste (leonxlnx)?
- Design Taste Frontend (leonxlnx)
- Builds the persuasion surface of a website - a launch page, a personal or studio portfolio, a visual overhaul of a site that already exists - and ships the working page, steered hard away from the templated look a model reaches for by default: a stated aesthetic read of the brief, a committed type and colour language, and motion that has to justify itself. Its scope stops at surfaces meant to be scrolled and read; dashboards, data grids, and multi-step wizards are handed off to a product-UI system rather than restyled.
- GPT Taste (leonxlnx)
- The same push away from templated pages, aimed at Codex and GPT because they drift differently: it forces a fresh pick of hero shape, type stack and scroll choreography each build instead of reaching for last time's, and leans hard on scroll-driven motion. What separates it from the general version is the model it corrects, not the work it covers.
Should I use Design Taste Frontend or GPT Taste?
The clearest answer is a situation each one is unambiguously right for. Both of these are drawn from the game's question bank.
Reach for Design Taste Frontend when
The direction for the studio's new site was agreed weeks ago and written down: editorial, warm greys, a serif display face, almost no motion. Someone now has to build the thing - hero, work grid, about, contact, one long scroll.The deciding is done, which removes both skills that decide: frontend-design settles look and feel before the build, and design-consultation proposes a whole system from scratch. What is left is the build, on exactly the surface design-taste-frontend is scoped to - a portfolio site that has to hold a committed type and colour language instead of drifting back to the default. web-artifacts-builder also builds, but it is aimed at claude.ai artifacts with real state and routing, and this is one scrolling site.
Reach for GPT Taste when
The team's frontend pipeline runs on Codex end to end, and every landing page it emits arrives with the same hero shape and the same type stack as the last one. They want the pressure against templated output applied where the repetition is actually coming from, and switching models is not on the table.This is the same anti-templating job aimed specifically at Codex and GPT, on the argument that they drift differently, and it forces a fresh pick of hero shape, type stack and scroll choreography on every build rather than reaching for last time's. What separates it from its sibling is the model it corrects rather than the work it covers, and this brief turns on precisely that. The most tempting wrong answer is design-taste-frontend, the general version of the same push, which would be right if the model were not the variable named in the problem. image-to-code changes the order the work happens in, not what the pipeline keeps repeating. redesign-existing-projects improves pages that exist; here every page is new and arrives identical.
What they have in common
Both are filed under Visual, the axis along which they collide. That shared ground is what makes an agent pick between them on description alone - and what makes it pick wrong.
Nearby comparisons
Reading the difference is not the same as spotting it at speed. That is the game.
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