Found docs updates needed from ADK python release v1.22.1 to v1.23.0

https://github.com/google/adk-python/compare/v1.22.1...v1.23.0

### 1. **Add Data Agent tool to the Google Cloud tools index page.**

**Doc file**: docs/tools/google-cloud/index.md

**Current state**:
> The list of Google Cloud tools does not include the new Data Agents tool.

**Proposed Change**:
> Add a new card for 'Data Agents' pointing to '/adk-docs/tools/google-cloud/data-agent/'.
> Example HTML:
>
>

>

>

Data Agents

>

Analyze data using natural language with Data Agents

>

>

**Reasoning**:
New Data Agent toolset introduced in v1.23.0 needs to be discoverable in the Google Cloud tools index.

**Reference**: src/google/adk/tools/data_agent/data_agent_toolset.py

### 2. **Create documentation for the new DebugLoggingPlugin.**

**Doc file**: docs/observability/debug-logging.md

**Current state**:
> No documentation for the new `DebugLoggingPlugin`.

**Proposed Change**:
> Create a new documentation page for `DebugLoggingPlugin`.
>
> Structure:
> 1. **Overview**: Explains that `DebugLoggingPlugin` captures detailed interaction data (LLM requests/responses, tool calls, events, session state) to a YAML file for debugging.
> 2. **Usage**:
> ```python
> from google.adk.plugins import DebugLoggingPlugin
>
> debug_plugin = DebugLoggingPlugin(output_path="debug_logs.yaml")
> runner = Runner(agent=my_agent, plugins=[debug_plugin])
> ```
> 3. **Output Format**: Describe the YAML structure (per-invocation documents).
> 4. **Configuration**: Document parameters `output_path`, `include_session_state`, `include_system_instruction`.

**Reasoning**:
New `DebugLoggingPlugin` is a significant feature for observability and debugging that requires dedicated documentation.

**Reference**: src/google/adk/plugins/debug_logging_plugin.py

### 3. **Document environment variables for trace content capture and privacy.**

**Doc file**: docs/observability/cloud-trace.md

**Current state**:
> The documentation does not mention environment variables for controlling data capture in traces.

**Proposed Change**:
> Add a section "Privacy and Data Capture" explaining how to control the logging of sensitive content in traces.
>
> Explain two environment variables:
> 1. `ADK_CAPTURE_MESSAGE_CONTENT_IN_SPANS`: Set to 'false' or '0' to disable capturing potentially PII data (LLM requests/responses/tool args) in ADK spans. Defaults to 'true'.
> 2. `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT`: Set to 'true' or '1' to enable logging of prompt/response content in GenAI instrumented spans.
>
> Also mention that ADK tracing now aligns with OpenTelemetry Semantic Conventions for Generative AI.

**Reasoning**:
New tracing implementation introduces environment variables to control data capture, which is critical for privacy and compliance. Users need to know how to configure this.

**Reference**: src/google/adk/telemetry/tracing.py

### 4. **Document `adk eval_set` CLI commands.**

**Doc file**: docs/evaluate/index.md

**Current state**:
> The documentation mentions `adk eval` but not the `adk eval_set` commands for creating and managing eval sets via CLI.

**Proposed Change**:
> Add a section "Managing Eval Sets via CLI" (or similar) describing the new commands:
> - `adk eval_set create`: Creates an empty EvalSet.
> - `adk eval_set add_eval_case`: Adds eval cases to an eval set, e.g., from a conversation scenarios file.
>
> Mention that these commands allow programmatic creation of evaluation datasets.

**Reasoning**:
New CLI commands `adk eval_set create` and `adk eval_set add_eval_case` allow users to manage evaluation datasets from the command line, complementing the web UI approach.

**Reference**: src/google/adk/cli/cli_tools_click.py

### 5. **Document Express Mode deployment for Agent Engine.**

**Doc file**: docs/deploy/agent-engine/deploy.md

**Current state**:
> The documentation for deploying to Agent Engine does not mention support for Vertex AI Express Mode (using an API key).

**Proposed Change**:
> Add a section or note about deploying with Express Mode.
> Mention the `--api_key` option for `adk deploy agent_engine`.
> Explain that this initializes `vertexai` with the API key instead of project/location credentials.

**Reasoning**:
The CLI now supports deploying to Agent Engine with an API key (Express Mode), enabling usage without full GCP project credentials setup in some cases. This option should be documented.

**Reference**: src/google/adk/cli/cli_deploy.py

### 6. **Document Custom Metrics configuration for evaluation.**

**Doc file**: docs/evaluate/criteria.md

**Current state**:
> The documentation lists standard evaluation criteria but does not mention how to define custom metrics using Python code.

**Proposed Change**:
> Add a section "Custom Metrics" explaining how to define metrics backed by custom Python functions.
> Show how to configure them in `test_config.json` using the `custom_metrics` field with `code_config` pointing to the function path.
> Include the JSON example from `EvalConfig` docstring.

**Reasoning**:
New feature `custom_metrics` in `EvalConfig` allows users to define their own evaluation logic using Python functions. This is a powerful extensibility feature that should be documented.

**Reference**: src/google/adk/evaluation/eval_config.py

### 7. **Update MCP Tools docs with StreamableHTTP and timeout params.**

**Doc file**: docs/tools-custom/mcp-tools.md

**Current state**:
> The documentation for `McpToolset` mentions `StdioConnectionParams` and `SseConnectionParams` but omits `StreamableHTTPConnectionParams` in the overview. It also doesn't mention the new timeout configuration options.

**Proposed Change**:
> Update the `McpToolset` class overview to include `StreamableHTTPConnectionParams` as a connection option.
> Add a section or note about configuring timeouts (`timeout`, `sse_read_timeout`) in connection parameters for better stability in production.

**Reasoning**:
`StreamableHTTPConnectionParams` is a supported and important connection method (especially for Cloud Run). New timeout parameters were added to connection params to handle network issues better. These should be documented.

**Reference**: src/google/adk/tools/mcp_tool/mcp_session_manager.py

### 8. **Update LiteLLM docs with file upload support and Gemini warning.**

**Doc file**: docs/agents/models/litellm.md

**Current state**:
> The documentation covers basic usage but doesn't mention file handling capabilities or the warning about using Gemini via LiteLLM.

**Proposed Change**:
> 1. Mention that file inputs (images, PDFs, etc.) are automatically handled for supported providers (OpenAI, Azure) by uploading them as files when necessary.
> 2. Add a note about the warning when using `LiteLlm(model="gemini/...")` suggesting the native `Gemini` model class for better performance.

**Reasoning**:
LiteLLM integration has been updated to support automatic file uploads for OpenAI/Azure, and now warns users when using Gemini models via LiteLLM instead of the native integration. These are important for usability and performance.

**Reference**: src/google/adk/models/lite_llm.py

### 9. **Document `include_plugins` parameter for `AgentTool`**

**Doc file**: docs/agents/multi-agents.md

**Current state**:
> The documentation for `AgentTool` does not mention the `include_plugins` parameter.

**Proposed Change**:
> Add a note or update the `AgentTool` example to mention the `include_plugins` parameter.
> Explain that `include_plugins` (default: True) controls whether the child agent inherits plugins from the parent runner. Setting it to False allows for isolated execution.

**Reasoning**:
New parameter `include_plugins` added to `AgentTool` allows controlling plugin propagation in multi-agent setups. This is important for configuring agent isolation.

**Reference**: src/google/adk/tools/agent_tool.py

### 10. **Update logging guide to reference logging plugins.**

**Doc file**: docs/observability/logging.md

**Current state**:
> `docs/observability/logging.md` focuses on standard Python logging configuration.

**Proposed Change**:
> Add a section "Logging Plugins" or "Advanced Debugging" that links to the new `DebugLoggingPlugin` documentation.
> Also briefly mention `LoggingPlugin` for console-based summary logging.

**Reasoning**:
Users looking for logging information should be made aware of the dedicated logging plugins available in ADK.

**Reference**: src/google/adk/plugins/logging_plugin.py