AI Engineering

Structured Output / JSON Schema Builder

Build an object schema from a list of field names and JSON types.

Calculations run in your browser. The tool does not send your inputs to a server.

01Your inputs

Local workspace

Start with the sample below, or enter your own values.

name:type, one per linePut each entry on its own line, following the example format.

02Your result

Your result will appear here. Choose an action after checking your inputs.

A quick guide

How to use this tool

Check the example and the unit beside each input.
Enter your values and choose Build.
Review the result and assumptions, then copy what you need.

Reset example restores the starting values. Clear removes text and number inputs, returns choices to their first valid option, and removes the result.

Reference guide

Explanation and worked examples

Each listed field is required and additional properties are disabled. Add meaningful value constraints before using it as a complete application contract.

Use in day-to-day IT work

Estimate the resources for an AI-assisted IT workflow or draft its review and fallback steps.

Checks before applying the result

Use current provider limits, prices and tokenizer measurements for the intended model.
Evaluate representative support tasks, access controls and failure handling before connecting operational systems.

New to the terminology?

LLM: Large language model: a model that generates or interprets language.
Token: A unit of text counted by a model tokenizer.
RAG: Retrieval-augmented generation: supplying retrieved evidence to a model.

Keep exploring

How calculations work and where the models stop →