Random JSON Schema Example Fixture Generator

Description

Synthesize flat string-enum, safe-integer-range and boolean schema examples with controlled missing-field or wrong-type labels.

A parser corpus pairs literal input spellings or structured documents with observable parser results or explicitly constructed expectations. Successful parsing, semantic validity, and exact round-trip preservation are separate properties, so test records retain the relevant evidence.

Synthesize flat string-enum, safe-integer-range and boolean schema examples with controlled missing-field or wrong-type labels.

When to use this tool

Use this generator to create reproducible json schema example fixture cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply fields, control, count in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read documents. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Generate primitive string-choice, bounded-integer, or Boolean fields from the supplied specifications. A control either leaves the document valid, removes a required field, or replaces one value with a different type; return expected issue field and code.^[1]

Input field	Meaning and units	Accepted input
fields	Fields	Required. Array of Object; no unknown keys. or Object; no unknown keys. or Object; no unknown keys.; minimum items 1; maximum items 16.
control	Control	Required. Text; one of "valid", "missing-required", "wrong-type".
count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 32.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
documents	Documents	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
documents[].document	Document	Required. Object.
documents[].pretty	Pretty	Required. Text; maximum UTF-16 length 65536.
documents[].valid	Validity under the specific model or delegated checker described above.	Required. Boolean.
documents[].issueField	Issue Field	Required. Text; maximum UTF-16 length 65536.
documents[].issueCode	Issue Code	Required. Text; maximum UTF-16 length 65536.
randomness	Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.	Required. Object; no unknown keys.
randomness.seed	Optional numeric replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "fields": [
      {
        "key": "count",
        "required": true,
        "kind": "integer",
        "minimum": 2,
        "maximum": 4
      },
      {
        "key": "color",
        "required": false,
        "kind": "string",
        "choices": [
          "red",
          "blue"
        ]
      }
    ],
    "control": "valid",
    "count": 1,
    "seed": 42
  },
  "output": {
    "documents": [
      {
        "document": {
          "count": 3,
          "color": "red"
        },
        "pretty": "{\n  \"count\": 3,\n  \"color\": \"red\"\n}\n",
        "valid": true,
        "issueField": "",
        "issueCode": ""
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

All fields are initially generated, including optional ones. Missing-required mode needs a required field. Validity labels follow the supplied small model rather than arbitrary JSON Schema evaluation.
A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random JSON Schema Example Fixture Generator — tool.io

Similar or alternative tools

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