JSON ke Skema Zod

(Documentation in English)

What it does

Generate a Zod validation schema from JSON. Scalars map to their validator (z.string, z.number, z.boolean, z.null), objects recurse into inline z.object({...}), arrays become z.array(...) — and a mixed-type array becomes z.union([...]) of each distinct element type. Drop the output straight into a TypeScript project that uses Zod for runtime validation: API responses, config files, form payloads, fixtures. 100% client-side.

How to use it

1. Paste JSON into the JSON box (a sample is prefilled — Sample restores it, Clear empties it).
2. Optionally set a Root name (defaults to Root, used for the const Root = ... binding).
3. The schema renders live on the right, pinned while you scroll the input.
4. Copy it, or Download it as schema.ts.

Examples

A flat object — {"id":1,"name":"Ada","active":true,"tags":["a","b"]} →

const Root = z.object({
  id: z.number(),
  name: z.string(),
  active: z.boolean(),
  tags: z.array(z.string()),
});

Nested objects recurse inline — {"user":{"name":"Ada"}} →

const Root = z.object({
  user: z.object({
    name: z.string(),
  }),
});

Mixed arrays become array-of-union — {"xs":[1,"a"]} →

const Root = z.object({
  xs: z.array(z.union([
    z.number(),
    z.string(),
  ])),
});

Edge cases — empty arrays become z.array(z.unknown()); null maps to z.null(); anything the parser rejects shows in the error box instead of the schema.

Good to know

• Private: parsing is local — safe for sensitive payloads.
• The generated schema is a starting point: add .min()/.max() refinements where your real data has constraints the sample didn’t show.
• Related tools: JSON to TypeScript, JSON Validator.