metadata-schema-generator

To generate JSON schemas for design system components, you can use automated schema generation tooling that extracts component data from Figma, Storybook, and source code to synthesize machine-readable definitions encoding props, behavioral rules, and accessibility contracts.

Machine-readable component metadata is used to bridge human documentation and machine understanding, providing structured JSON data for programmatic consumption by AI agents, linters, MCP servers, and code generators to automate UI governance.

Yes, you can extract component composition constraints and accessibility rules by integrating schema generation tooling with Storybook and Figma to synthesize source code data, encoding constraints like child element limits and mandatory aria-labels into JSON.

You encode behavioral rules and props for AI agents by generating structured JSON metadata schemas that programmatically define component properties, valid states, and composition limits, allowing automated tooling to understand and interact with UI components correctly.

Source code access is highly beneficial for generating accurate JSON metadata schemas, as the generation process integrates directly with source code alongside Figma and Storybook to extract and synthesize comprehensive component data into machine-readable formats.