docs: add ToolContext section for advanced tool metadata

[MuhammadSaqib786]

Summary

Added a short section in context.md explaining how to use ToolContext, which extends RunContextWrapper and gives access to tool metadata such as tool_name, tool_call_id, and tool_arguments.

Why

This helps developers understand when to use ToolContext for advanced cases, without replacing the existing RunContextWrapper examples.

Changes

• Added a new "Advanced: ToolContext" section under Local Context.
• Included a simple example with explanations.

Notes

This PR updates only the documentation. No code or API changes were made.

Thanks for reviewing!

[MuhammadSaqib786]

Thanks for reviewing! Please let me know if there’s anything you’d like me to adjust or clarify.

[MuhammadSaqib786]

Thanks for reviewing! Please let me know if there’s anything you’d like me to adjust or clarify.

[seratch]

the context object must be the first argument when you receive typed parameters. can you use this weather example instead?

from typing import Annotated

from pydantic import BaseModel, Field

from agents import Agent, Runner, function_tool
from agents.tool_context import ToolContext

class WeatherContext(BaseModel):
    user_id: str

class Weather(BaseModel):
    city: str = Field(description="The city name")
    temperature_range: str = Field(description="The temperature range in Celsius")
    conditions: str = Field(description="The weather conditions")

@function_tool
def get_weather(ctx: ToolContext[WeatherContext], city: Annotated[str, "The city to get the weather for"]) -> Weather:
    print(f"[debug] Tool context: (name: {ctx.tool_name}, call_id: {ctx.tool_call_id}, args: {ctx.tool_arguments})")
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

agent = Agent(
    name="Weather Agent",
    instructions="You are a helpful agent that can tell the weather of a given city.",
    tools=[get_weather],
)