docs: Use a trimmed ADK AgentConfig schema in Agent Builder Assistant

This trimmed schema includes only the fields relevant to agent shells, tool wiring, and common generation parameters, improving efficiency and focus.

The default model for the assistant has also been updated to "gemini-2.5-pro"

Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 829513627

Author: GWeale

contributing/samples/adk_agent_builder_assistant/agent_builder_assistant.py

@@ -45,9 +45,28 @@
 class AgentBuilderAssistant:
   """Agent Builder Assistant factory for creating configured instances."""
 
+  _CORE_SCHEMA_DEF_NAMES: tuple[str, ...] = (
+      "LlmAgentConfig",
+      "LoopAgentConfig",
+      "ParallelAgentConfig",
+      "SequentialAgentConfig",
+      "BaseAgentConfig",
+      "AgentRefConfig",
+      "CodeConfig",
+      "ArgumentConfig",
+      "ToolArgsConfig",
+      "google__adk__tools__tool_configs__ToolConfig",
+  )
+  _GEN_CONFIG_FIELDS: tuple[str, ...] = (
+      "temperature",
+      "topP",
+      "topK",
+      "maxOutputTokens",
+  )
+
   @staticmethod
   def create_agent(
-      model: Union[str, BaseLlm] = "gemini-2.5-flash",
+      model: Union[str, BaseLlm] = "gemini-2.5-pro",
       working_directory: Optional[str] = None,
   ) -> LlmAgent:
     """Create Agent Builder Assistant with embedded ADK AgentConfig schema.
@@ -127,11 +146,9 @@ def create_agent(
   def _load_schema() -> str:
     """Load ADK AgentConfig.json schema content and format for YAML embedding."""
 
-    # CENTRALIZED ADK AGENTCONFIG SCHEMA LOADING: Use common utility function
-    # This avoids duplication across multiple files and provides consistent
-    # ADK AgentConfig schema loading with caching and error handling.
-    schema_dict = load_agent_config_schema()
-    return AgentBuilderAssistant._build_schema_reference(schema_dict)
+    schema_dict = load_agent_config_schema(raw_format=False)
+    subset = AgentBuilderAssistant._extract_core_schema(schema_dict)
+    return AgentBuilderAssistant._build_schema_reference(subset)
 
   @staticmethod
   def _build_schema_reference(schema: dict[str, Any]) -> str:
@@ -300,6 +317,38 @@ def add(text: str = "", indent: int = 0) -> None:
 
     return "```text\n" + "\n".join(lines) + "\n```"
 
+  @staticmethod
+  def _extract_core_schema(schema: dict[str, Any]) -> dict[str, Any]:
+    """Return only the schema nodes surfaced by the assistant."""
+
+    defs = schema.get("$defs", {})
+    filtered_defs: dict[str, Any] = {}
+    for key in AgentBuilderAssistant._CORE_SCHEMA_DEF_NAMES:
+      if key in defs:
+        filtered_defs[key] = defs[key]
+
+    gen_config = defs.get("GenerateContentConfig")
+    if gen_config:
+      properties = gen_config.get("properties", {})
+      filtered_defs["GenerateContentConfig"] = {
+          "title": gen_config.get("title", "GenerateContentConfig"),
+          "description": (
+              "Common LLM generation knobs exposed by the Agent Builder."
+          ),
+          "type": "object",
+          "additionalProperties": False,
+          "properties": {
+              key: properties[key]
+              for key in AgentBuilderAssistant._GEN_CONFIG_FIELDS
+              if key in properties
+          },
+      }
+
+    return {
+        "$defs": filtered_defs,
+        "properties": schema.get("properties", {}),
+    }
+
   @staticmethod
   def _load_instruction_with_schema(
       model: Union[str, BaseLlm],