Materials Workbench
VerifiedMaterials editor workbench — React UI and Express server to render JSON schemas to images and generate schemas with AI (declare-render + materials-agents).
$ Add to .claude/skills/ About This Skill
# Materials Workbench
Use this skill when the user wants to run the materials editor workbench: a local web app with a React client and Express server that renders JSON schemas to images (declare-render) and can generate or edit schemas using AI (materials-agents).
What it is
- Client — React + Vite app for editing and previewing render schemas.
- Server — Express API that renders schemas to PNG/JPG and uses materials-agents (OpenAI) for schema generation or refinement.
When to use
- User wants to "run the workbench", "start the materials editor", or "open the schema editor UI".
- User needs a local dev environment for rendering schemas and AI-assisted schema creation.
Run
From the workbench root:
```bash pnpm install pnpm run install:all # install root, server, and client deps pnpm run dev # start server + client (concurrently) ```
- Client usually: http://localhost:5173
- Server usually: http://localhost:3000 (or port in server config)
Set `OPENAI_API_KEY` for AI/generate features.
Project layout
- `client/` — React frontend (Vite).
- `server/` — Express backend (declare-render, materials-agents, canvas).
Schema format
Same as materials-cli: declare-render format with `id`, `width`, `height`, `layers` (text, image, container, shape, etc.).
Use Cases
- Edit and render JSON schemas to images via a React UI materials editor
- Generate material schemas using AI-powered design agents
- Build visual material design workflows with Express server backend
- Preview and iterate on material designs in a browser-based workbench
- Integrate AI-generated schemas into material design pipelines
Pros & Cons
Pros
- +Compatible with multiple platforms including claude-code, openclaw
- +Well-documented with detailed usage instructions and examples
- +Purpose-built for ai & machine learning tasks with focused functionality
Cons
- -No built-in analytics or usage metrics dashboard
- -Configuration may require familiarity with ai & machine learning concepts
FAQ
What does Materials Workbench do?
What platforms support Materials Workbench?
What are the use cases for Materials Workbench?
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Next Step
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