od-contribute
One-click contribution flow for OpenDesign (nexu-io/open-design) — even for non-coders. Pick one of four cards (ship a Skill or…
The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility.
Claude Code
$ npx -y skills add nexu-io/open-design --skill taste-skill-v1 --agent claude-code
Codex
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a codex -y
Cursor
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a cursor -y
Gemini CLI
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a gemini-cli -y
GitHub Copilot
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a github-copilot -y
OpenCode
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a opencode -y
Windsurf
$ npx skills add nexu-io/open-design --skill taste-skill-v1 -a windsurf -y
name: design-taste-frontend-v1
description: |
The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility.
triggers:
- "design taste v1"
- "high agency frontend"
- "anti slop v1"
- "visual density"
od:
mode: prototype
surface: web
platform: desktop
scenario: marketing
category: creative-direction
upstream: "https://github.com/Leonxlnx/taste-skill"
preview:
type: html
design_system:
requires: true
craft:
requires:
- typography
- color
- anti-ai-slop
- animation-discipline
example_prompt: |
Create a polished marketing page using design-taste-frontend-v1 with strong typography, spacing, motion, and anti-slop guardrails.**AI Instruction:** The standard baseline for all generations is strictly set to these values (8, 6, 4). Do not ask the user to edit this file. Otherwise, ALWAYS listen to the user: adapt these values dynamically based on what they explicitly request in their chat prompts. Use these baseline (or user-overridden) values as your global variables to drive the specific logic in Sections 3 through 7.
Unless the user explicitly specifies a different stack, adhere to these structural constraints to maintain consistency:
LLMs have statistical biases toward specific UI cliché patterns. Proactively construct premium interfaces using these engineered rules:
**Rule 1: Deterministic Typography**
**Rule 2: Color Calibration**
**Rule 3: Layout Diversification**
**Rule 4: Materiality, Shadows, and "Anti-Card Overuse"**
**Rule 5: Interactive UI States**
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