Schema is built to be readable by AI tools — not just by designers. The file's variable architecture, naming conventions, and metadata are structured so that AI models and MCP servers can interpret your design and generate accurate ACSS-compatible code.

What makes Schema AI-ready

Web-syntax on every variable

Every variable in Schema has its web-syntax field populated with the actual ACSS variable name (e.g., --primary, --space-m, --h2, --bg-dark). This is the key bridge between Figma and code.

If you create custom variables, always fill in the web-syntax field with the corresponding CSS variable name.

Semantic layer naming

Layers in Schema use semantically relevant names - section, container, hero-content. AI tools parse the layer tree to understand structure, and meaningful names give them a clear model of the intended layout.

Component structure

Components use consistent variant patterns, predictable layer hierarchies, and descriptive naming. This means AI can identify a "card pattern" or "section intro" reliably - rather than guessing from loose frames.

Description fields

Schema uses description fields on both variables and components to provide additional context, annotations, and usage instructions. These help AI tools understand relationships between variables and how components are intended to be used.

Best practices for AI workflows

For the best results when using AI tools with Schema:

• Use variables, not raw values — every hard-coded hex or pixel value breaks the chain AI uses to understand your design system
• Use Color Assignments over Palette — assignments carry semantic meaning (bg-dark, text-light) that AI can reason about
• Keep components linked — linked instances give AI a single source of truth for recurring elements
• Name your frames — hero-homepage tells AI more than Frame 12
• Maintain consistent Canvas structure — desktop and mobile contexts side by side help AI identify responsive pairs

See Tips to improve AI contextualization for a deeper dive into these practices.