Convert JSON data structures into TypeScript Effect Schema code to provide a type-safe data validation solution.

JSON to CSV & CSV to JSON Converter
Convert seamlessly between JSON arrays and CSV tabular data. Ideal for data analysis and software development.

JSON to XML & XML to JSON Converter
A two-way conversion tool for JSON and XML data structures, designed for development, testing, and data processing.

JSON to Java POJO Generator
Automatically convert JSON strings into standard Java POJO class code for API integration, data modeling, and other development scenarios.
When building a type-safe data validation layer for your TypeScript projects, manually writing Effect Schemas can be tedious and error-prone. This tool parses JSON data structures and automatically generates TypeScript code that complies with Effect Schema specifications, outputting Schema classes complete with field type definitions and validation logic. Effect Schema is a core module in the Effect-TS ecosystem used for defining data models, and it processes objects that conform to JSON specifications.
Q: Will empty fields in the JSON generate optional properties?
A: No. The tool generates required fields based on the provided JSON values. If you need optional properties, you must manually add Schema.optional.
Q: How are date format strings handled?
A: Currently, they are uniformly identified as string types. You will need to manually adjust them to Schema.Date or implement custom validation logic.
Please ensure your input is in a valid JSON format. Complex types like enums and custom validations require manual adjustments to the generated results. The generated code does not include runtime dependency imports; you will need to install the @effect/schema package yourself. For sensitive data, we recommend processing it locally to avoid network transmission risks.
For API response modeling, we recommend generating a base Schema using real response data first, then adding additional constraints based on your business requirements. For example, an email field in user data can be extended to Schema.string.pattern(emailRegex) for format validation. A common example: Input {"id":1,"name":"Alice"} outputs Schema.struct({id: Schema.number, name: Schema.string}).