Tool Calling

Reviewed by Proof · Updated

Definition

Tool calling lets a model ask your code to run a function you described, then use the result in its reply.

Key takeaways

  • You describe tools (name, purpose, JSON parameters) in the request's tools list.
  • The model doesn't run anything. It replies with a tool_calls entry naming the tool and its arguments.
  • Your code runs the tool and sends the result back in a message with the tool role.
  • The model then writes its answer using that result.
  • For what luv13 supports, see Tool Calling on luv13.

The loop

  1. You send the conversation plus a list of tools, each with a JSON Schema for its arguments.
  2. The model decides. If a tool would help, it returns an assistant message with tool_calls instead of plain text. Each call has an id, the function name and arguments as a JSON string.
  3. You run it. Parse the arguments, call your real function, and capture the output.
  4. You reply with a message of role tool, the matching tool_call_id, and the output as content.
  5. The model answers, or asks for another tool. Repeat until it replies with text.

Tips

  • Write clear tool descriptions. The model picks tools based on them.
  • Always validate the arguments. The model can produce missing or wrong values.
  • Never let a tool do something risky, like deleting data or spending money, without a check in your own code.
  • Coding tools such as Roo Code depend on tool calling, so a model's tool support matters when you choose one.

Example

This request offers one tool. Check Tool Calling on luv13 to confirm which models and options luv13 supports.

curl https://api.luv13.ai/v1/chat/completions \
  -H "Authorization: Bearer $LUV13_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "luv13/glm-5.3-flash",
    "messages": [{"role": "user", "content": "What is the weather in Phoenix?"}],
    "tools": [{
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get the current weather for a city.",
        "parameters": {
          "type": "object",
          "properties": {"city": {"type": "string"}},
          "required": ["city"]
        }
      }
    }]
  }'

If the model wants the tool, the reply's choices[0].message.tool_calls holds the call. get_weather here is only an example. You write the real function.