Schema Inference

Work out the schema of a JSON array or CSV: field types, nulls, uniqueness and completeness, plus minimum, maximum and mean for numbers.

Pay by wallet (x402) schema-infer

Example

Example answer

{
  "fields": [
    {
      "max": 30,
      "min": 25,
      "mean": 27.5,
      "name": "age",
      "type": "number",
      "unique": true,
      "nullable": false,
      "sample_values": [
        30,
        25
      ],
      "completeness_percent": 100
    },
    {
      "name": "city",
      "type": "string",
      "unique": true,
      "nullable": false,
      "sample_values": [
        "Stockholm",
        "Oslo"
      ],
      "completeness_percent": 100
    },
    {
      "name": "name",
      "type": "string",
      "unique": true,
      "nullable": false,
      "sample_values": [
        "Alice",
        "Bob"
      ],
      "completeness_percent": 100
    }
  ],
  "total_rows": 2,
  "total_fields": 3,
  "format_detected": "json"
}

Inputs

Field	Type	Required	What it is
`data`	any	Yes	JSON array or CSV string

Output fields

How reliably each field appears in a successful answer.

Field	Type	Appears
`fields`	array	Always (present in every successful answer)
`total_rows`	integer	Always (present in every successful answer)
`total_fields`	integer	Always (present in every successful answer)
`format_detected`	string	Always (present in every successful answer)

How to call it

The same tool through each route. MCP clients reach it through Strale’s server at https://api.strale.io/mcp; the call below is what the agent sends.

# Needs an API key. max_price_cents caps what this call may cost.
curl -X POST https://api.strale.io/v1/do \
  -H "Authorization: Bearer $STRALE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "capability_slug": "schema-infer",
    "inputs": {
      "data": [
        {
          "age": 30,
          "city": "Stockholm",
          "name": "Alice"
        },
        {
          "age": 25,
          "city": "Oslo",
          "name": "Bob"
        }
      ]
    },
    "max_price_cents": 5
  }'

{
  "tool": "strale_execute",
  "arguments": {
    "slug": "schema-infer",
    "inputs": {
      "data": [
        {
          "age": 30,
          "city": "Stockholm",
          "name": "Alice"
        },
        {
          "age": 25,
          "city": "Oslo",
          "name": "Bob"
        }
      ]
    },
    "max_price_cents": 5
  }
}

import { Strale } from "straleio";

const strale = new Strale({ apiKey: process.env.STRALE_API_KEY! });
const result = await strale.do({
  capability_slug: "schema-infer",
  inputs: {
    "data": [
      {
        "age": 30,
        "city": "Stockholm",
        "name": "Alice"
      },
      {
        "age": 25,
        "city": "Oslo",
        "name": "Bob"
      }
    ]
  },
  max_price_cents: 5,
});

import os
from straleio import Strale, DoRequest

strale = Strale(api_key=os.environ["STRALE_API_KEY"])
result = strale.do(DoRequest(
    capability_slug="schema-infer",
    inputs={
        "data": [
            {
                "age": 30,
                "city": "Stockholm",
                "name": "Alice",
            },
            {
                "age": 25,
                "city": "Oslo",
                "name": "Bob",
            },
        ],
    },
    max_price_cents=5,
))

# No account. The first request answers 402 with the price in USDC;
# an x402 client pays it from your wallet and repeats the request.
curl -i -X POST https://api.strale.io/x402/v2/schema-infer \
  -H 'Content-Type: application/json' \
  -d '{
    "data": [
      {
        "age": 30,
        "city": "Stockholm",
        "name": "Alice"
      },
      {
        "age": 25,
        "city": "Oslo",
        "name": "Bob"
      }
    ]
  }'

Limitations

Samples can omit optional fields and rare types
Infers schema from sample data — optional fields or rare value types may not appear in the inferred schema
What to do instead: Provide a representative sample including edge cases and null values for more accurate schema inference