[BUG]: output_schema=str combined with tools causes infinite call_llm/execute_tools loop

## Description

Using bare `str` type as `output_schema` on an `Agent` that also has `tools` causes an infinite `call_llm → execute_tools → call_llm` loop. The LLM repeatedly calls tools instead of producing the final structured response via `set_model_response`.

This does not happen with `BaseModel` subclasses as `output_schema`, only with primitive types like `str`.

## Reproduction

```python
from google.adk import Agent, Workflow, Event

def plan_visualization(approach: str, technology: str, key_elements: list[str]) -> str:
"""Plan a visualization."""
return f"Plan: {approach} using {technology}"

def query_data(query: str) -> list[dict]:
"""Query the database."""
return [{"q": "Q1", "revenue": 100}]

# This agent loops infinitely:
plan_agent = Agent(
name="plan_agent",
model="gemini-2.5-pro",
instruction="Call plan_visualization with approach, technology, and key elements.",
tools=[plan_visualization, query_data],
output_schema=str, # <-- bare str causes the loop
mode="single_turn",
)

# Use in a Workflow or with Runner — agent calls tools repeatedly
# without ever settling on a final string response
```

## Expected Behavior

Either:
1. `output_schema=str` works correctly with tools — the LLM calls tools, then uses `set_model_response` to return a plain string, OR
2. ADK raises a validation error at agent creation time: `"output_schema must be a BaseModel subclass when tools are specified"`

## Actual Behavior

The agent enters an infinite loop:
1. LLM generates a `function_call` (e.g., `plan_visualization`)
2. ADK executes the tool and returns the result
3. LLM generates another `function_call` instead of calling `set_model_response`
4. Repeat endlessly — burns API credits silently

## Analysis

ADK auto-adds `set_model_response` when both `output_schema` and `tools` are specified ([documented here](https://github.com/google/adk-python/blob/v2.0.0a1/contributing/samples/output_schema_with_tools/README.md)). With `BaseModel` schemas, the model correctly calls `set_model_response` with structured JSON. With bare `str`, the `set_model_response` schema may be malformed or confusing to the model, causing it to fall back to repeated tool calls.

## Workaround

Remove `output_schema` from agents that have tools. Use other mechanisms to suppress unwanted text output if needed.

## Related Issues

- #3413 — Agent with output_schema + tools enters infinite loop (model regression, fixed)
- #3969 — Output Schema consistently ignored by LLM Agent with tools
- #4868 — output_schema + Tool with structured arg causes infinite loop

## Environment

- `google-adk` 2.0.0a2
- Model: `gemini-2.5-pro` (also tested with `gemini-2.5-flash`)
- Python 3.14

> Context for this issue was developed with AI assistance (Claude).