# Structured Output via Tools — AI Agents and Tool Use

Source: https://www.geekswithgeeks.com/en/ai-agents-mcp/use-structured-output

> Force a tool call to get guaranteed-shape JSON instead of parsing prose.

## A tool you never run

Need clean JSON, such as an extracted invoice? Define a tool whose input schema is the shape you want (`record_invoice` with fields for vendor, date and total) and force it with `tool_choice`. The model fills the arguments, which arrive as a parsed object. You do not actually run anything; the arguments are the result. Still validate values, because the schema controls shape, not truth.

## Forcing the extraction tool

`INVOICE_TOOL` is a schema like the earlier examples. The structured data is in `block.input`.

```python
reply = client.messages.create(
    model=MODEL, max_tokens=512,
    tools=[INVOICE_TOOL],
    tool_choice={"type": "tool", "name": "record_invoice"},
    messages=[{"role": "user", "content": invoice_text}],
)
block = next(b for b in reply.content if b.type == "tool_use")
data = block.input        # {"vendor": ..., "date": ..., "total": ...}
```

## Keep extraction schemas small

A schema with forty fields invites mistakes. Extract a few well-named fields per call, mark uncertain ones as optional, and let the model return null instead of inventing a value.

**Quiz:** Does a schema guarantee the extracted values are correct?

- [ ] Yes, always
- [ ] Only for numbers
- [x] No, it fixes the shape, so you still validate the values
- [ ] Only in Hindi

*Answer:* No, it fixes the shape, so you still validate the values. A well-formed object can still hold a wrong date or total.