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Novus Examples
json362 B

OpenAI Tools Schema (JSON)

OpenAI function tools definition JSON paired with the tool-calling traces.

Tool calling / function callingSchema / OpenAPI testing
Preview — first 22 linesjson
{
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "parameters": {
          "type": "object",
          "properties": {
            "city": {
              "type": "string"
            }
          },
          "required": [
            "city"
          ]
        }
      }
    }
  ]
}

Specifications

Tools
1

What is a .json file?

JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.

How to use this file

Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.

How to use this file for testing

“OpenAI Tools Schema (JSON)” is a deterministic Novus Examples fixture for Tool calling / function calling, Schema / OpenAPI testing. JSONL traces of function/tool calls with arguments and results — for testing agent harnesses and tool routers.

Documented properties for this file: JSON · 362 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.

AI/ML fixtures are fully synthetic with documented schemas — no real people or data. Test data loaders, tokenizers, annotation converters, embedding/vector stores, or eval-metric parsers against the known structure and fixed seeds.

These JSON fixtures are synthetic SAMPLE auth or tool-call shapes for harnesses — never production secrets or live tokens. Validate schema fields and alg variants against the documented role.

Code examples

import json

with open("openai-tools-schema.json") as f:
    data = json.load(f)
print(type(data), len(data))

Related files

Generated by generation/ai_wave_f.py. Free for any use, no attribution required — license.