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Workflow Playbook
Generate typed models from JSON or schema evidence for TypeScript, Go, Rust, Kotlin, Java, C#, and Zod validation workflows.
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Typed code generation works best when the team agrees on the source contract before choosing a language. If the only evidence is a payload sample, use json-schema-generator to make the implicit structure reviewable. If the source is an operational spreadsheet, xlsx-sheet-to-json-schema can turn columns and examples into a contract that code generators can share.
Use json-to-typescript, json-to-go, or json-to-rust when those runtimes read, validate, or emit the payload first. Review the generated names, nullable fields, arrays, nested models, and serialization annotations before adoption. Generated code is a strong starting point, but it still needs project-specific naming and compatibility review.
When clients also need models, generate platform types with json-to-kotlin, json-to-java, and json-to-csharp. For TypeScript boundaries that handle untrusted input, convert the shared schema with json-schema-to-zod-schema-converter so runtime checks match the documented contract. The final handoff should include the source examples or schema, the selected generators, and the assumptions that future regeneration must preserve.
Workflow playbook
Start from representative JSON samples, generate a JSON Schema when the contract is still implicit, or derive one from spreadsheet columns when the data source is XLSX.
Create the model for the runtime that owns the data boundary, then review field names, optionality, nested object naming, and serialization behavior before copying it into the project.
When the same payload crosses platform or SDK boundaries, generate matching Kotlin, Java, or C# models and compare nullable fields and collection types across languages.
Convert the shared JSON Schema into Zod when a TypeScript API, form, worker, or ingestion boundary must validate untrusted input instead of relying on types alone.
Compare generated code against the original examples, document assumptions about nullability and naming, and keep the schema or sample that should drive future regeneration.
Use JSON Schema Generator when examples must become a shared contract first, or start from the language generator when the sample is already stable enough for one codebase.
Pick the generator that matches the service or SDK language so names, nullable fields, enums, and collections are reviewed in the same environment where the code will run.
Generate language models for compile-time safety, then use JSON Schema to Zod Schema Converter when a TypeScript boundary must parse and reject invalid input at runtime.