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Leonxlnx taste-skill
Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop
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License: MIT License
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Need help integrating this stack?
Our team builds with modern open-source stacks. Tell us what you are shipping.
Get a quote →The Anti-Slop Frontend Framework for AI Agents
Thanks to Kimi (Moonshot AI), our Open Source Friend, for supporting taste-skill! With 2.8T parameters, native vision, and a 1-million-token context window, Kimi K3 delivers frontier performance across long-horizon coding, knowledge work, and reasoning.
Get a Kimi API key. Taste-skill users get 10% bonus API credits on their first purchase.
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interfaces.dev · A design engineering magazine by Jakub Krehel |
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React Bits · animated React components for creative interfaces |
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Emil Kowalski · animations.dev |
| IMG.LY · CreativeEditor SDK | |
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Sent.dm · messaging APIs for SMS, WhatsApp, and RCS |
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Portable Agent Skills that upgrade AI-built interfaces: stronger layout, typography, motion, and spacing instead of boilerplate-looking UIs. This repo also includes image-generation skills for reference boards (web, mobile, brand kits). Pair them with ChatGPT Images or similar generators, then hand the frames to Codex, Cursor, or Claude Code for implementation.
Taste Skill has no official token, coin, or crypto project. Any token using my name, image, or project is unaffiliated and not endorsed by me.
Disclaimer · Install · Skills · Settings · Examples · Sponsors · Research · FAQ · License
We would love your feedback. Suggestions and bug reports:
- Open a Pull Request or Issue on GitHub
- DM @lexnlin or @blueemi99
- Email us at hello@tasteskill.dev
The npx skills add CLI scans the skills/ folder in this repo, so all skills below (code and image-generation) install the same way.
npx skills add https://github.com/Leonxlnx/taste-skillInstall a single skill by its install name (the name: field inside the SKILL frontmatter, not the folder name):
npx skills add https://github.com/Leonxlnx/taste-skill --skill "design-taste-frontend"You can also copy any SKILL.md into your project or paste it into ChatGPT / Codex conversations.
The default taste-skill (install name design-taste-frontend) is now v2 (experimental), a substantial rewrite of the original v1. If you already have v1 installed, just re-run the install command and you will be upgraded:
npx skills add https://github.com/Leonxlnx/taste-skill --skill "design-taste-frontend"The install name did not change, so no script updates are needed. The newer SKILL.md replaces the older one in place.
If you depend on the exact behavior of v1 and want to pin to it explicitly:
npx skills add https://github.com/Leonxlnx/taste-skill --skill "design-taste-frontend-v1"See CHANGELOG.md for the full v1 to v2 diff and the rationale.
Each skill does one job; you do not need all of them at once. Implementation skills output code. Image-generation skills output reference images only.
The Install name column is the exact value you pass to --skill.
| Skill (folder) | Install name | Description |
|---|---|---|
| taste-skill | design-taste-frontend |
🆕 v2 (experimental) - substantial rewrite of the default skill. Reads the brief, infers the design language, tunes three dials (VARIANCE / MOTION / DENSITY). Brief inference, design-system map, hard em-dash ban, canonical GSAP code skeletons, redesign-audit protocol, strict pre-flight check. Actively iterating toward v2.0.0 stable. |
| taste-skill-v1 | design-taste-frontend-v1 |
The original v1 of taste-skill, preserved for projects depending on its exact behavior. Use only if the v2 default breaks something specific in your workflow. |
| gpt-tasteskill | gpt-taste |
Stricter variant for GPT/Codex: higher layout variance, stronger GSAP direction, aggressive anti-slop. |
| image-to-code-skill | image-to-code |
Image-first pipeline: generate site references, analyze them, then implement the frontend to match. |
| redesign-skill | redesign-existing-projects |
Existing projects: audit the UI first, then fix layout, spacing, hierarchy, styling. |
| soft-skill | high-end-visual-design |
Polished, calm, expensive UI with softer contrast, whitespace, premium fonts, spring motion. |
| output-skill | full-output-enforcement |
When the model ships half-finished work: full output, no placeholder comments. |
| minimalist-skill | minimalist-ui |
Editorial product UI (Notion/Linear vibes), restrained palette, crisp structure. |
| brutalist-skill | industrial-brutalist-ui |
Hard mechanical language: Swiss type, sharp contrast, experimental layout. |
| stitch-skill | stitch-design-taste |
Google Stitch-compatible rules, including optional DESIGN.md export format. |
These produce design images only (no code). Use with ChatGPT Images, Codex image mode, or any agent that generates images.
| Skill (folder) | Install name | Description |
|---|---|---|
| imagegen-frontend-web | imagegen-frontend-web |
Website comps: hero, landing, multi-section with strong typography, spacing, anti-slop art direction. |
| imagegen-frontend-mobile | imagegen-frontend-mobile |
Mobile screens and flows: iOS/Android/cross-platform, mockups, readable type, coherent sets. |
| brandkit | brandkit |
Brand-kit boards: logo directions, palettes, type, identity applications across categories. |
- Start with taste-skill for the safest general default. (Now v2 experimental - see what changed in the CHANGELOG.)
- If you depend on the exact behavior of the original taste-skill, install taste-skill-v1 instead.
- Use gpt-taste when you want the stricter GPT/Codex-oriented rules and motion/layout enforcement.
- Use image-to-code-skill for image → analyze → code website workflows.
- Use redesign-skill to improve an existing codebase instead of greenfield styling.
- Add soft-skill, minimalist-skill, or brutalist-skill when the visual direction is already chosen.
- Add output-skill if the agent keeps truncating output.
- Use imagegen-frontend-web, imagegen-frontend-mobile, or brandkit when the deliverable is images (comps, flows, identity boards), then pass results to your coding agent.
For image-to-code-skill, state the pipeline in the prompt, e.g.: follow the skill: generate images, then analyze, then code.
Attach or paste imagegen-frontend-web, imagegen-frontend-mobile, or brandkit and ask for the frames you need, then feed the renders to Codex, Cursor, or Claude Code. Use image-to-code-skill when you want one workflow that both generates references and implements the site in code.
Numbers at the top of the file are 1-10 dials:
- DESIGN_VARIANCE: Layout experimentation (lower: centered/clean · higher: asymmetric/modern).
- MOTION_INTENSITY: Animation depth (lower: hover · higher: scroll/magnetic).
- VISUAL_DENSITY: Information per viewport (lower: spacious · higher: dense dashboards).
Created with taste-skill:
If Taste Skill helps you, consider sponsoring:
dnakov
AkramReshad
ajmalaksar25
krikkkk
navanchauhan
robinebers
JKc66
u2393696078-rgb
a-human-created-this
AtharvaJaiswal005
ghughes7
mccun934
techmedic5
bytewerk-dev
LuisGot
oskar-collab
Background writing that shaped these skills lives in research/.
How is this different from other AI design skills?
Multiple specialized variants, adjustable dials in key skills, anti-repetition rules informed by dedicated research. All are framework agnostic across major coding agents.
Does it work with React, Vue, Svelte?
Yes. Rules target design intent, not a single framework API.
What is SKILL.md?
A portable instruction file agents can load automatically; install via npx skills add or by copying into a repo or conversation.
Do image-generation skills install with npx skills add?
Yes. They live under skills/ alongside the code skills so the same CLI discovers them.
MIT License · Copyright (c) 2026 Leonxlnx
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- Maintained recently (last push 4 weeks ago).
Who should use it
- Developers working primarily with JavaScript
- Teams exploring AI tooling, agents, or ML infrastructure
- Frontend engineers comparing UI frameworks and tools
Potential use cases
- Reference or evaluate JavaScript open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
Strengths
- Recent repository activity
- README present in our index
- Declared license: MIT License
- Substantial fork count (5,743) suggests reuse and contribution interest
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Strong signals: Active maintenance
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.
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