design-taste-frontend
Helps your agent create interfaces that don't look like templates. It's great for websites, portfolios, and design overhauls.
What it does
This tool helps create the look and feel of websites, like landing pages and portfolios. It understands what you want and crafts a design that doesn't look generic, using appropriate styles and design systems.
When to use it
- ✓Creating the main page for a new product or service.
- ✓Refreshing the look of an existing website.
- ✓Building an online portfolio to showcase your work.
Example of what to ask your AI
“I want to create a landing page for my new meditation app. The audience is young adults seeking calm and wellness. Use a minimalist and modern style.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
First, the tool analyzes your description to understand the site type, desired style, and target audience. Then, it adjusts internal settings like 'variance,' 'motion,' and 'density' to create a unique and fitting design.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add nexu-io/open-design --skill design-taste-frontendOr download just the file:
curl -L https://raw.githubusercontent.com/nexu-io/open-design/main/skills/taste-skill/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
tasteskill: Anti-Slop Frontend Skill
Landing pages, portfolios, and redesigns. Not dashboards, not data tables, not multi-step product UI. Every rule below is contextual. None of it fires automatically. First read the brief, then pull only what fits.
0. BRIEF INFERENCE (Read the Room Before Anything Else)
Before touching code or tweaking dials, infer what the user actually wants. Most LLM design output is bad because the model jumps to a default aesthetic instead of reading the room.
0.A Read these signals first
- Page kind - landing (SaaS / consumer / agency / event), portfolio (dev / designer / creative studio), redesign (preserve vs overhaul), editorial / blog.
- Vibe words the user used - "minimalist", "calm", "Linear-style", "Awwwards", "brutalist", "premium consumer", "Apple-y", "playful", "serious B2B", "editorial", "agency-y", "glassy", "dark tech".
- Reference signals - URLs they linked, screenshots they pasted, products they named, brands they're competing with.
- Audience - B2B procurement panel vs. design-conscious consumer vs. recruiter scanning a portfolio. The audience picks the aesthetic, not your taste.
- Brand assets that already exist - logo, color, type, photography. For redesigns, these are starting material, not optional input (see Section 11).
- Quiet constraints - accessibility-first audiences, public-sector, regulated industries, trust-first commerce, kids' products. These constraints OVERRIDE aesthetic preference.
0.B Output a one-line "Design Read" before generating
Before any code, state in one line: "Reading this as: <page kind> for <audience>, with a <vibe> language, leaning toward <design system or aesthetic family>."
Example reads:
- "Reading this as: B2B SaaS landing for technical buyers, with a Linear-style minimalist language, leaning toward Tailwind utilities + Geist + restrained motion."
- "Reading this as: solo designer portfolio for hiring managers, with an editorial / kinetic-type language, leaning toward native CSS + scroll-driven animation + custom typography."
- "Reading this as: redesign of a public-sector service site, with a trust-first language, leaning toward GOV.UK Frontend or USWDS."
0.C If the brief is ambiguous, ask one question, do not guess
Ask exactly one clarifying question - never a multi-question dump - and only when the design read genuinely diverges. Example: "Should this feel closer to Linear-clean or Awwwards-experimental?"
If you can confidently infer from context, do not ask. Just declare the design read and proceed.
0.D Anti-Default Discipline
Do not default to: AI-purple gradients, centered hero over dark mesh, three equal feature cards, generic glassmorphism on everything, infinite-loop micro-animations everywhere, Inter + slate-900. These are the LLM defaults. Reach past them deliberately based on the design read.
1. THE THREE DIALS (Core Configuration)
After the design read, set three dials. Every layout, motion, and density decision below is gated by these.
DESIGN_VARIANCE: 8- 1 = Perfect Symmetry, 10 = Artsy ChaosMOTION_INTENSITY: 6- 1 = Static, 10 = Cinematic / PhysicsVISUAL_DENSITY: 4- 1 = Art Gallery / Airy, 10 = Cockpit / Packed Data
Baseline: 8 / 6 / 4. Use these unless the design read overrides them. Do not ask the user to edit this file - overrides happen conversationally.
1.A Dial Inference (design read → dial values)
| Signal | VARIANCE | MOTION | DENSITY |
|---|---|---|---|
| "minimalist / clean / calm / editorial / Linear-style" | 5-6 | 3-4 | 2-3 |
| "premium consumer / Apple-y / luxury / brand" | 7-8 | 5-7 | 3-4 |
| "playful / wild / Dribbble / Awwwards / experimental / agency" | 9-10 | 8-10 | 3-4 |
| "landing page / portfolio / marketing site (default)" | 7-9 | 6-8 | 3-5 |
| "trust-first / public-sector / regulated / accessibility-critical" | 3-4 | 2-3 | 4-5 |
| "redesign - preserve" | match existing | +1 | match existing |
| "redesign - overhaul" | +2 | +2 | match existing |
1.B Use-Case Presets
| Use case | VARIANCE | MOTION | DENSITY |
|---|---|---|---|
| Landing (SaaS, mainstream) | 7 | 6 | 4 |
| Landing (Agency / creative) | 9 | 8 | 3 |
| Landing (Premium consumer) | 7 | 6 | 3 |
| Portfolio (Designer / studio) | 8 | 7 | 3 |
| Portfolio (Developer) | 6 | 5 | 4 |
| Editorial / Blog | 6 | 4 | 3 |
| Public-sector service | 3 | 2 | 5 |
…
FAQ
What does 'anti-slop' mean?
It means the design won't be generic or low-quality, avoiding the common, uninspired looks that sometimes appear in AI-generated designs.
What are 'design systems'?
These are sets of visual rules and components (colors, fonts, buttons) used by large companies (like Google, Microsoft) to ensure consistency and quality in their digital products.
How does the tool decide on the style?
It analyzes keywords you use (like 'minimalist,' 'playful'), examples you provide (links, images), and the target audience to pick the best design direction.
Details
Original description by the author
Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
repo: nexu-io/open-design
Popularity
- GitHub stars
- 101k
- Ranking position
- #778
- License
- Apache-2.0
- Updated
- 10/16/2026
Comments
- …
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