Add section on output tool use

Author: matthewfranglen

docs/models/openai.md

@@ -231,6 +231,25 @@ def i_like_iso_dates(date: str): ...
 
 There is a limit to the grammar complexity that GPT-5 supports, as such it is important to test your grammar.
 
+Freeform function calling, with or without a context free grammar, can be used with the output tool for the agent:
+
+```python
+from pydantic_ai import Agent, Tool
+from pydantic_ai.models.openai import OpenAIResponsesModel
+from pydantic_ai.tools import FunctionTextFormat
+
+sql_grammar_definition = "..."  # (1)!
+def database_query(sql: str) -> str:
+    return sql  # (2)!
+
+output_tool = Tool(database_query, text_format=FunctionTextFormat(syntax='lark', grammar=sql_grammar_definition))
+model = OpenAIResponsesModel('gpt-5')
+agent = Agent(model, output_type=output_tool)
+```
+
+1. An inline SQL grammar definition would be quite extensive and so it has been omitted, you can find an example SQL grammar [in the openai example](https://cookbook.openai.com/examples/gpt-5/gpt-5_new_params_and_tools#33-example---sql-dialect--ms-sql-vs-postgresql). There are also example grammars in the [lark repo](https://github.com/lark-parser/lark/blob/master/examples/composition/json.lark).
+2. Returning the input directly might seem odd, remember that it has been constrained to the provided grammar. This can be useful if you want GPT-5 to generate content according to a grammar that you then use extensively through your program.
+
 ##### Best Practices
 
 Lark grammars can be tricky to perfect. While simple grammars perform most reliably, complex grammars often require iteration on the grammar definition itself, the prompt, and the tool description to ensure that the model does not go out of distribution.