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🔄 Schema Converter

Convert JSON to YAML, simple YAML to JSON, JSON Schema to TypeScript, or infer a schema from sample JSON with clear subset warnings.

Schema conversion and inference checks · Supported subset · utilito.schema-contract.v1
Infers objects, arrays, required fields, and primitive types from sample JSON. YAML support is intentionally small and warns on unsupported anchors, tags, sequences, and multiline syntax. Normalization and exact-path comparison use the shared versioned contract.
 Runs in your browser
Schema Converter runs locally in your browser. JSON/YAML samples and schema drafts are not fetched or uploaded from the page.
What this tool does
Schema Converter handles small deterministic schema chores: JSON Schema inference, JSON to YAML, simple YAML to JSON, and schema-to-TypeScript output.
Why it is useful
It gives humans and agents one canonical workflow tool instead of several thin one-direction converters.
How it works
The shared core parses the selected input, performs a deterministic conversion, and returns output plus warnings about subset limitations.
Best input
Use valid JSON for inference and JSON-to-YAML. Use simple YAML key/value mappings only for YAML-to-JSON.
Agent workflow tip
Copy the JSON summary to preserve the mode, warning count, and generated output in automation logs.
Privacy note
Browser use is local; the API route submits the sample or schema to Utilito serverless for automation.
Important limitation
This is a lightweight converter, not a replacement for full YAML or TypeScript compiler tooling.
Quick answers
Can it infer perfect schemas from one sample?
No. It infers a useful draft from observed values only; review required fields and unions manually.
Does YAML conversion support every YAML feature?
No. It supports simple key/value mappings and reports unsupported complex lines.
Common Use Cases
Infer API response schema
Paste one representative JSON response and create a first-pass schema.
Convert config snippets
Turn small JSON config examples into readable YAML.
Generate TypeScript from schema
Create a lightweight interface from a JSON Schema draft for documentation.
API examples
Call the same deterministic core through Utilito’s compact API router. Send only data you intentionally submit to the server-side endpoint.
Try in API playground →Schema →
Infer a JSON Schema with curl
curl
curl -X POST https://utilito.dev/api/run \
  -H "Content-Type: application/json" \
  -d '{"tool_id":"schema-converter","input":{"input":"{\n  \"user\": {\n    \"id\": 123,\n    \"email\": \"[email protected]\"\n  },\n  \"active\": true,\n  \"tags\": [\n    \"trial\",\n    \"agent\"\n  ]\n}","mode":"infer_json_schema","name":"GeneratedSchema"}}'
Infer a JSON Schema from JavaScript
javascript
const res = await fetch('https://utilito.dev/api/run', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    tool_id: 'schema-converter',
    input: { input: "{\n  \"user\": {\n    \"id\": 123,\n    \"email\": \"[email protected]\"\n  },\n  \"active\": true,\n  \"tags\": [\n    \"trial\",\n    \"agent\"\n  ]\n}", mode: "infer_json_schema", name: "GeneratedSchema" }
  })
});
const data = await res.json();
console.log(data.result.output || data.result.report);
Infer a JSON Schema from Python
python
import requests
payload = {
    "tool_id": "schema-converter",
    "input": {"input":"{\n  \"user\": {\n    \"id\": 123,\n    \"email\": \"[email protected]\"\n  },\n  \"active\": true,\n  \"tags\": [\n    \"trial\",\n    \"agent\"\n  ]\n}","mode":"infer_json_schema","name":"GeneratedSchema"},
}
result = requests.post("https://utilito.dev/api/run", json=payload).json()["result"]
print(result.get("output") or result.get("report"))
Structured output prompt workflow
Move from prompt-first structured-output drafting to schema-first prompt binding, then validate JSON responses before using model output in agents or apps.
🧱Structured Output Prompt Builder🧱Prompt Template Schema Builder✅JSON Schema Validator{}JSON Formatter🔐Base64 Encode / Decode🔗URL Encoder / Decoder
View all in Code →