What is JSON to Effect Schema Generator?
Effect Schema (@effect/schema) is a runtime validation and type inference library built for the Effect ecosystem in TypeScript. Unlike static-only type definitions, Effect Schema gives you both compile-time type safety and runtime data validation in a single, composable definition. It uses Schema.Struct to define object shapes and automatically extracts TypeScript types through Schema.Schema.Type<typeof Schema>. This generator takes your JSON data and produces ready-to-use Effect Schema definitions, handling nested objects as separate Schema.Struct declarations, arrays with proper element typing, optional field wrapping, and type alias exports — all following the children-first ordering convention that Effect requires for proper type resolution.
How to Use
- Enter a root schema name in the options bar — this becomes the top-level Schema.Struct variable name
- Toggle "Wrap with Schema.optional()" if your API responses may omit fields, which wraps every field definition in Schema.optional()
- Toggle "Export type aliases" to generate TypeScript type exports using Schema.Schema.Type for full type inference alongside runtime validation
- Paste your JSON payload into the input area — the generator inspects actual values to infer types
- Click "Generate Effect Schema" and the output appears with nested schemas defined before the root schema
- Copy the output into your TypeScript project and import from @effect/schema to start validating data
Why Use This Tool?
Tips & Best Practices
- Provide realistic sample data because type inference relies on actual JSON values — a string "123" becomes Schema.String, not Schema.Number
- For fields that can be either a value or null, manually adjust to Schema.Union(Schema.String, Schema.Null) after generation
- Chain refinements with Schema.pipe() to add constraints like Schema.String.pipe(Schema.minLength(1)) or Schema.Number.pipe(Schema.positive())
- Effect Schema integrates with the Effect runtime for composable error handling — use Effect.gen with Schema.decodeUnknown for async validation pipelines
- Use Schema.decodeUnknownSync(MySchema)(data) for synchronous validation at API boundaries, or Schema.decodeUnknownEither for Either-based error handling without exceptions
Frequently Asked Questions
What is Effect Schema and how does it differ from Zod or Yup?
Effect Schema (@effect/schema) is part of the Effect ecosystem, a comprehensive TypeScript library for building type-safe, composable applications. Unlike Zod or Yup which focus solely on validation, Effect Schema is designed to integrate deeply with the Effect runtime for composable error handling, concurrency, and resource management. It uses Schema.Struct for object definitions and Schema.Schema.Type for type extraction, offering tree-shakeable, high-performance schemas.
How does JSON map to Effect Schema types?
JSON strings map to Schema.String, numbers to Schema.Number, booleans to Schema.Boolean, null to Schema.Null, arrays to Schema.Array(Schema.Type), and objects to Schema.Struct({...}). When optional wrapping is enabled, fields are wrapped with Schema.optional(). Nested objects are extracted as separate Schema.Struct definitions with their own type aliases, following children-first ordering.
When should I NOT use Effect Schema?
If your project does not use the Effect ecosystem and you only need simple runtime validation, Zod or Valibot may be lighter choices with smaller bundle sizes. Effect Schema shines when you are already using Effect for composable error handling, concurrency, or resource management. Also, if you need browser-only validation without TypeScript, a simpler library may suffice.
How do I validate data with Effect Schema at runtime?
Use Schema.decodeUnknownSync(MySchema)(data) for synchronous validation that throws on failure. For Effect-based async validation, use Schema.decodeUnknown(MySchema)(data). For safe parsing without exceptions, Schema.decodeUnknownEither returns an Either type, and Schema.decodeUnknownOption returns an Option type — both integrate naturally with Effect pipelines.
What is Schema.optional() and when should I use it?
Schema.optional() wraps a schema to indicate the field may be omitted entirely from the data. This is distinct from nullable fields, which use Schema.Union with Schema.Null. Enable the "Wrap with Schema.optional()" option when your API responses may not include certain fields. For fields that are present but can be null, use Schema.Union(Schema.String, Schema.Null) instead.
Is my JSON data sent to a server?
No. All schema generation happens entirely in your browser using client-side JavaScript. Your JSON data never leaves your device, making this tool safe for use with sensitive or proprietary data structures.
Real-world Examples
API Response Validation for User Profile
Generate an Effect Schema from a user profile API response to validate incoming data at the boundary of your application.
{"id": 42, "name": "Jane", "email": "jane@acme.co", "isActive": true, "address": {"city": "Berlin", "zip": "10115"}}import { Schema } from "@effect/schema";
export const AddressSchema = Schema.Struct({
city: Schema.String,
zip: Schema.String,
});
export type Address = Schema.Schema.Type<typeof AddressSchema>;
export const RootSchema = Schema.Struct({
id: Schema.Number,
name: Schema.String,
email: Schema.String,
isActive: Schema.Boolean,
address: AddressSchema,
});
export type Root = Schema.Schema.Type<typeof RootSchema>;Optional Fields for Partial Update Payloads
Wrap all fields with Schema.optional() to model a PATCH request body where every field is optional.
{"title": "Draft", "priority": 3, "completed": false}import { Schema } from "@effect/schema";
export const RootSchema = Schema.Struct({
title: Schema.optional(Schema.String),
priority: Schema.optional(Schema.Number),
completed: Schema.optional(Schema.Boolean),
});
export type Root = Schema.Schema.Type<typeof RootSchema>;