groundx-design-standards

Document EyeLevel and GroundX brand invariants across color, typography, logos, and principles.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/eyelevelai/groundx-skills --skill groundx-design-standards
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: groundx-design-standards
Source: https://github.com/eyelevelai/groundx-skills/tree/main/skills/groundx-design-standards
Command: npx skills add https://github.com/eyelevelai/groundx-skills --skill groundx-design-standards

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The EyeLevel brand and GroundX product rely on consistent design language across web, slides, documents, and marketing. This skill defines and protects the invariants that ensure brand fidelity without forcing medium-specific implementations.

Core Features & Use Cases

  • Centralized tokens.json as the canonical source of truth for color, typography, spacing, radii, and logos.
  • Narrative references in references/tokens.md to explain rules and rationale while keeping values in sync with the machine-readable tokens.json.
  • Medium-specific skills (groundx-web-ui, groundx-slides, etc.) auto-generate their mirrors and consume these invariants to maintain brand consistency across outputs.

Quick Start

Run the standard mirrors generator to propagate token changes to all medium-specific skills.

Frequently Asked Questions about groundx-design-standards

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do design tokens maintain brand consistency across multiple media formats?

Design tokens act as a centralized source of truth for color, typography, and spacing. Medium-specific skills consume autogenerated mirrors from a canonical tokens.json file to enforce brand fidelity across web, slides, and documents.

How do I update brand guidelines and regenerate style mirrors for downstream skills?

To update brand guidelines, modify the canonical tokens.json file and run the standard mirrors generator. This propagates token changes to all medium-specific skills, ensuring brand invariants remain synchronized across all outputs.

What are brand invariants and when do I need to document them for CI verification?

Brand invariants are the core visual rules for color, typography, and logos. You need to document them when setting up CI pipelines to automatically verify design drift and enforce brand guidelines across all generated media.

Can I use a tokens.json file to enforce design language across web and slide outputs?

Yes, a canonical tokens.json file serves as the single source of truth for your design language. Medium-specific skills auto-generate and consume mirrors from this file to maintain strict brand consistency across web and slide outputs.

Why does my brand style-guide drift across different document formats?

Brand style-guide drift occurs when medium-specific implementations lack a centralized source of truth. Using a canonical tokens.json file to autogenerate mirrors for each medium prevents this drift and maintains brand fidelity.

What's the best way to structure design tokens for a multi-platform brand?

The best way to structure design tokens is using a machine-readable tokens.json file paired with narrative references. This separates values from rationale while allowing medium-specific skills to consume autogenerated mirrors for consistency.