# Defining Tools — LangChain / LlamaIndex

Source: https://www.geekswithgeeks.com/en/langchain-llamaindex/a-tools

> Turn a function into a tool with a name, description and schema.

## A function the model can ask for

A **tool** is a function with a **name**, a **description** and an **argument schema** that the model can request. The `@tool` decorator builds all three from the function: the name from the function name, the description from the **docstring** and the schema from the **type hints**. Good docstrings matter because the model reads them to decide when to call the tool. With a tool-calling chat model, `model.bind_tools([...])` lets the model reply with a structured request ("call `add` with a=2, b=40"); **your code** (or an agent loop) executes it and returns the result. Validate arguments and limit what each tool can do.

## Act, decide, recover

Tools let models act, routing picks a path, and retries and fallbacks keep chains running.

![Four tools: tools, branch, retry, trace.](assets/figures/langchain-llamaindex/section-3-map.svg) — Figure 3.1 — Tools, branch, retry and trace.

## A tool from a function, run

I ran this offline in a Python virtual environment with langchain-core 1.6.6, langchain-text-splitters 1.1.2 and llama-index-core 0.14.25. No API key or network call is needed because a fake model or a toy embedding stands in for the real one. The decorator derived the tool name `add`, its description from the docstring, and an argument schema from the type hints. Invoking it with a dict returns 42.

```python
from langchain_core.tools import tool

@tool
def add(a: int, b: int) -> int:
    """Add two integers."""
    return a + b

print(add.name, "|", add.description)
print(add.args)
print(add.invoke({"a": 2, "b": 40}))

```

Output:

```
add | Add two integers.
{'a': {'title': 'A', 'type': 'integer'}, 'b': {'title': 'B', 'type': 'integer'}}
42
```

## Write the docstring for the model

Say what the tool does, when to use it and what each argument means. Vague descriptions cause wrong or missing tool calls.

**Quiz:** Where does the @tool decorator get the tool description from?

- [x] The function's docstring
- [ ] The file name
- [ ] A random string
- [ ] The GPU

*Answer:* The function's docstring. The docstring becomes the description the model reads.