docs: add multi-tool agent tutorial

[zeel2104]

Checklist

🚨 Please review this repository's contribution guidelines.

• I've read and agree to the project's contribution guidelines.
• I'm requesting to pull a topic/feature/bugfix branch.
• I checked that my code additions will pass code linting checks and unit tests.
• I updated unit and integration tests (if applicable).
• I'm ready to notify the team of this contribution.

Description

This change adds a new end-to-end tutorial guide for mocking a multi-tool LangGraph agent with StuntDouble.

It covers:

->setting up a LangGraph agent with multiple tools
->configuring per-tool mocks with matchers and dynamic resolvers
->using CallRecorder in pytest to assert tool call order and arguments
->common patterns and edge cases such as conditional responses, hybrid real/mock flows, and error simulation
->It also links the new tutorial from the docs index so it appears in the guides navigation.

Fixes #40

[ChiefArchitect]

This tutorial is an end-to-end guide that builds on concepts from quickstart, matchers, call-recording, etc. It would make more sense to place it after the individual concept guides (near the end of the toctree), not in the middle between call-recording and context-aware-mocks.

[ChiefArchitect]

This is a well-structured, comprehensive tutorial that fills a real gap — showing how all the StuntDouble pieces fit together in a realistic multi-tool scenario. The writing is clear and the progression from setup through assertions is logical.

[ChiefArchitect]

The tutorial doesn't mention the Python 3.12+ requirement from the project conventions. A brief note at the top (or in prerequisites) would help.

[ChiefArchitect]

validate_registry_mocks signature mismatch
The actual signature is:
def validate_registry_mocks(tools: list[BaseTool], scenario_metadata: dict) -> dict[str, list[str]]

But the test
errors = validate_registry_mocks([get_customer, list_bills, create_invoice],config["configurable"]["scenario_metadata"])

[ChiefArchitect]

Add a clear comment like # your LLM node — see langgraph-integration.md with an explicit note that this is left to the reader

[ChiefArchitect]

mock_fn is a positional arg, not keyword-only. using mock_fn=failing_invoice_mock works but is slightly unusual — this is fine since Python allows passing positional args as kwargs.

[zeel2104]

@ChiefArchitect
Updated the PR based on feedback:

• moved the tutorial later in the guides toctree
• added a Python 3.12+ prerequisite note
• clarified that agent_node is an app-specific LLM/planner node and linked to the LangGraph integration guide
• cleaned up the validation example to validate scenario_metadata directly before injecting config
• simplified the custom register() example for consistency

[Bbenchaya]

Thanks @zeel2104, looks good, we may need to tweak it a bit in the future, Thanks for the help!

Addressed