Function Calling Builder - OpenAI & Anthropic Tool Definition Tool
Function Calling (Tool Use) allows LLMs to connect with external databases, third-party APIs, and real-time computation services. The model does not execute the function itself; instead, it outputs structured JSON arguments adhering to a rigid JSON Schema you provide. Writing nested JSON Schema tools configurations manually is notoriously verbose and syntax-heavy. This builder creates compliant function calling definitions visually with instant code export in TypeScript and Python.
When to Use This Tool
- External REST API Integration: Define schemas for weather lookup, payment processing, or customer database queries.
- Database SQL / NoSQL Querying: Equip models with structured tools to query enterprise databases safely with validated parameters.
- Deterministic Output Extraction: Force the model to return structured data matching your function parameters rather than conversational text.
- Multi-Tool Agent Architectures: Configure toolsets for autonomous agents orchestrating search, calculations, and ticketing.
How to Use
- Name & Describe Function: Provide a clear, semantic function name (e.g. get_weather) and thorough purpose description.
- Add Parameters: Define parameter names, primitive types (string, number, boolean, array), and descriptions.
- Mark Required Fields: Check which parameters are mandatory to enforce proper JSON validation.
- Export Tool Code: Copy the ready-to-use tools array in Python or TypeScript for OpenAI or Anthropic SDKs.
Input & Output Example
Input:
Function: get_current_weather(location: string, unit: enum["celsius", "fahrenheit"])
Output:
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather for a given location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City and country"},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
},
"required": ["location"]
}
}
}
Frequently Asked Questions (FAQ)
Q. Why is the function description so critical?
A. The LLM decides whether or not to call a tool based almost entirely on the function description. A vague description leads to the model ignoring the tool or passing malformed arguments.
Q. What is the difference between OpenAI Tools and Anthropic Tools format?
A. OpenAI nests the definition under {"type": "function", "function": {...}}, whereas Anthropic's Claude API accepts {"name": "...", "description": "...", "input_schema": {...}}. This tool exports clean formats for both.
Q. Does the model execute the code on my server?
A. No. The model only generates the argument JSON. Your backend code receives the tool call, executes the function locally, and returns the result back to the model.
Engineering & Privacy Notes
- Compliant with standard JSON Schema specifications used by OpenAI, Anthropic, and Google GenAI.
- Runs completely offline on client-side memory ensuring your internal APIs remain confidential.
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