design-taste-frontend-v2-experimental
Provides frontend design rules for websites and portfolios. It focuses on design audits, design systems, and a strict process to ensure a high-quality final result.
What it does
This tool helps AI create the look and feel for websites focused on landing pages, portfolios, and redesigns. It prioritizes understanding your needs before starting, ensuring the final output matches the site's purpose and audience.
When to use it
- ✓When creating a homepage for a new product or service.
- ✓When building an online portfolio to showcase your work.
- ✓When redesigning the look of an existing website.
Example of what to ask your AI
“I want to create a website for my design studio, with a modern and creative look that attracts other artists.”
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 AI understands the page type, desired style, and target audience. Then, it adjusts 'dials' (settings) to control balance, motion, and visual density, selecting the best design tools for the outcome.
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 Leonxlnx/taste-skill --skill design-taste-frontend-v2-experimentalOr download just the file:
curl -L https://raw.githubusercontent.com/Leonxlnx/taste-skill/main/skills/taste-skill-v2-experimental/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?
'Anti-slop' means avoiding generic or low-quality results. The tool focuses on creating intentional, well-thought-out designs instead of using common defaults that don't fit.
What are the 'dials'?
The 'dials' are settings like 'Design Variance,' 'Motion Intensity,' and 'Visual Density.' They help the AI fine-tune the overall website style based on your requirements.
Why does the AI need to understand the audience?
The target audience greatly influences design. A website for business professionals might need a different look than one for a younger, creative audience. Understanding the audience ensures the design is effective.
Details
Original description by the author
Old v2 (experimental) of taste-skill, the single-file dial-driven version, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2). Use this install name only if you need the earlier behavior. Anti-slop frontend rules for landing pages, portfolios, and redesigns, with real design systems when applicable, audit-first redesigns and a strict pre-fli
repo: Leonxlnx/taste-skill
Popularity
- GitHub stars
- 97k
- Ranking position
- #838
- License
- MIT
- Updated
- 10/14/2026
Comments
- …
More skills from this repository
brandkit
Creates high-quality images for brand kits. It helps develop logos, visual identity systems, and brand presentations.
Leonxlnx/taste-skill
industrial-brutalist-ui
Develops interfaces with an industrial and brutalist style. It's perfect for data-heavy dashboards or sites that need a technical look.
Leonxlnx/taste-skill
gpt-taste
Improves user experience and website animation. It ensures varied layouts, readable typography, and smooth animations for pleasant navigation.
Leonxlnx/taste-skill
image-to-code
Transforms images into website code. It creates the design, analyzes it, and builds the website to match the image as closely as possible.
Leonxlnx/taste-skill
Similar skills
accessibility
Helps your agent create interfaces that everyone can use. Ensures websites and apps work well for people with disabilities, like those who are blind or have reduced mobility.
affaan-m/ECC
design-system
Helps your agent create a design system from existing code. It extracts visual information and checks for consistency, generating a report and an interactive preview.
affaan-m/ECC
liquid-glass-design
Helps your agent create iOS user interfaces with a 'Liquid Glass' effect. Allows adding dynamic and interactive visual effects in SwiftUI and UIKit.
affaan-m/ECC