Free agent developer tool
JSON to AI Tool Schema Generator
AI function calling describes tool arguments with a machine-readable schema. This generator infers a JSON Schema from an example object, then wraps it in a common function-tool definition containing a name, description, and parameters. It is deterministic, runs in the browser, and produces a draft that must be reviewed for descriptions, constraints, and provider compatibility.
Last updated: July 19, 2026 · No sign-up · Runs in your browser
Describe the function tool
Generated draft
Function tool definition
From example JSON to a function schema
The generator maps JSON strings, booleans, integers, numbers, nulls, objects, and arrays to JSON Schema types. Object properties are inferred recursively; fields can be marked required; array item schemas are deduplicated and combined with anyOf when examples contain multiple shapes. Example data cannot reveal semantic constraints such as formats, enums, ranges, descriptions, or conditional rules, so the output is only a structural starting point.
| Example value | Inferred schema | Review needed |
|---|---|---|
"open" | { "type": "string" } | Could need an enum, pattern, or format. |
10 | { "type": "integer" } | Could need minimum and maximum. |
| Object | properties plus optional required | Required fields and extra-property policy. |
| Array | items, or anyOf for mixed examples | Empty arrays reveal no item shape. |
Primary references
- JSON Schema getting started — schema structure, types, properties, descriptions, and validation constraints.
- JSON Schema type reference — object, array, string, number, integer, boolean, and null types.
- OpenAI function calling guide — current provider-specific function-tool shape and guidance; verify it before integration.
Frequently asked questions
Can JSON examples fully define an AI tool schema?
No. An example can reveal structure and observed value types, but not intent, descriptions, allowed ranges, enums, formats, conditional rules, authorization, or side-effect policy. Add those constraints manually.
Should every inferred property be required?
Only if the tool truly cannot operate without it. Marking every observed field required can make calls brittle; leaving important fields optional can produce unsafe or ambiguous calls.
What happens when an example array contains different types?
The generator deduplicates the inferred item shapes and uses anyOf. Review heterogeneous arrays carefully because one small example rarely captures all valid or invalid items.
Does a valid tool schema make an AI agent action safe?
No. Schema validation checks argument shape, not authorization, intent, business rules, rate limits, reversibility, or side effects. Enforce those controls outside the model.
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