materials-cli

What This Skill Does

The materials-cli skill is a powerful command-line tool designed for developers and designers who need to bridge the gap between structured JSON data and visual imagery. By utilizing the declare-render framework, this tool allows users to define complex visual layouts using simple, standard JSON schemas. It provides three primary functionalities: rendering static JSON schema files into high-quality PNG or JPG images, using OpenAI's AI capabilities to translate natural language prompts into valid rendering schemas, and ensuring the structural integrity of your JSON via a robust validation command.

Installation

You can easily integrate this tool into your OpenClaw environment by running the following command in your terminal: clawhub install openclaw/skills/skills/cai-zhuo/materials-cli Alternatively, for standalone system use, ensure you have Node.js installed and execute: npm install -g materials-cli

Use Cases

• Automated Design Systems: Generate consistent image assets like badges, certificates, or social media cards dynamically from database entries.
• Rapid Prototyping: Describe a visual layout to an AI assistant and have it generate a renderable schema instantly.
• QA Testing: Validate your generated JSON schemas before pushing them to production rendering pipelines to catch errors in structure, layer hierarchy, or attribute types.
• Dynamic UI Generation: Use the CLI in CI/CD pipelines to auto-generate previews for UI components defined in code.

Example Prompts

1. "materials-cli: Please render the schema located at ./assets/banner.json to an output file named landing-page.png with a width of 1200."
2. "Generate a JSON schema for a blue square with the text 'Welcome Home' in the center, and save the result as welcome.png."
3. "Can you validate the structure of config-schema.json to ensure it conforms to the declare-render format?"

Tips & Limitations

• Always validate your JSON files using the validate command before running a render command to avoid silent failures or distorted images.
• When using the generate command, provide specific details like color codes, font sizes, and layer positions to get the most accurate results from the AI model.
• Ensure your OPENAI_API_KEY is set in your environment variables for seamless operation; otherwise, pass it explicitly as a flag.
• Note that this tool creates local files, so ensure your environment has the necessary write permissions in the target directory.