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Convert JSON data structures into TypeScript Effect Schema code to provide a type-safe data validation solution.
Overview
Understand what the tool solves, how it works, and the boundaries of its data.
Paste a valid JSON value and this page produces TypeScript code in the Effect Schema format. The generated structure follows the fields and values in the sample: for instance, strings, numbers, booleans, arrays, and nested objects give the generator evidence about the shapes it can express. A root type name can be edited; the default is Root. The code is a useful model draft, while a schema is a programmatic description that can participate in decoding and encoding data in an Effect application.
A sample describes what happened to be present in that example. It cannot establish which properties are required across every response, or supply application-specific rules such as valid email formats, allowed status values, or numeric limits.
Guide
Follow the workflow and verify inputs and outputs with practical examples.
Root or enter a clearer type name for the generated top-level schema.For example, {"name":"Rae","active":true,"score":12} provides evidence for a string, boolean, and number field. If a field is absent in the only example, the generator cannot infer that field or tell you whether it is optional. Add separate contract knowledge deliberately after generation.
Use cases
See how the tool fits into real work and everyday tasks.
Use a sanitized response example to sketch nested records and arrays. Compare the draft with the API specification and examples from multiple response states before relying on it.
Generate a first pass from an existing configuration file, then add rules for allowed values, defaults, and required settings from the configuration’s actual requirements.
Share generated code as a starting point for review. Product and engineering teammates can identify missing cases and record which fields are optional or constrained.
Before using a production payload, replace personal or secret values with safe representative examples while preserving the shape. A single example may hide optional fields, null cases, alternate variants, or backwards compatibility requirements.
Q&A
Find concise answers to common questions and confusing cases.
No. It shows that the field appeared in this sample. Requiredness across all records must come from your real data contract.
The sample provides a string value, not proof of a date rule. Review and explicitly add the desired parsing or validation behavior in your application.
Not from example values alone. Rules such as ranges, formats, permissions, and relationships between fields must be specified separately.
Correct the JSON syntax and wait for generation again. When parsing fails, the page reports an error instead of showing code for the current input.
Notes
Review scope, result limitations, and important precautions before use.
Generated output is inferred from the JSON you provide, not from a service’s complete API contract. Compare it with authoritative project documentation, real records, and the Effect version installed in your project. Add and test rules for optional or nullable values, enumerations, date parsing, bounds, and cross-field conditions where needed.
Do not paste secrets or personal records into an online editor. Use representative, minimized examples when the data is sensitive. A successful generation step does not itself validate an external API or guarantee the schema matches every future response.
Related
Discover related tools, collections, and available API capabilities.