Reuse native parallel child logs

Pass each parent-visible child log into direct parallel worker execution so tool before_execution reuses it instead of creating a second generic tool log.

This keeps native badge types such as wait/progress (HDL) intact through execution, updates the parallel helper DOX contract, and adds a regression test for log reuse.

helpers/parallel_tools.py

@@ -487,13 +487,24 @@ async def _run_direct_tool_job(parent_context_id: str, job: ParallelJob) -> str:
 
         worker_agent = worker_context.agent0
         worker_agent.loop_data = LoopData()
-        return await execute_tool_call(worker_agent, job.tool_name, job.tool_args)
+        return await execute_tool_call(
+            worker_agent,
+            job.tool_name,
+            job.tool_args,
+            log_item=job.log_item,
+        )
     finally:
         if worker_context:
             await _remove_context(worker_context.id)
 
 
-async def execute_tool_call(agent: "Agent", tool_name: str, tool_args: dict[str, Any]) -> str:
+async def execute_tool_call(
+    agent: "Agent",
+    tool_name: str,
+    tool_args: dict[str, Any],
+    *,
+    log_item: "LogItem | None" = None,
+) -> str:
     if tool_name == "parallel":
         raise ValueError("`parallel` cannot be nested inside a parallel worker.")
 
@@ -501,6 +512,11 @@ async def execute_tool_call(agent: "Agent", tool_name: str, tool_args: dict[str,
     if not tool:
         raise ValueError(f"Tool '{tool_name}' not found or could not be initialized.")
 
+    original_get_log_object = None
+    if log_item is not None:
+        original_get_log_object = tool.get_log_object
+        tool.get_log_object = lambda: log_item
+
     agent.loop_data.current_tool = tool
     try:
         await agent.handle_intervention()
@@ -524,6 +540,8 @@ async def execute_tool_call(agent: "Agent", tool_name: str, tool_args: dict[str,
         await agent.handle_intervention()
         return response.message
     finally:
+        if original_get_log_object is not None:
+            tool.get_log_object = original_get_log_object
         agent.loop_data.current_tool = None
 
 

helpers/parallel_tools.py.dox.md

@@ -32,6 +32,7 @@
 - Parent-visible child log items are created for each wrapped call so the WebUI can inspect concurrent children separately while the wrapper result remains model-history-only.
 - Child tool logs mirror normal tool-call visible args; job ids remain available through wrapper results and prompt extras rather than visible process-step args.
 - Wrapped tool child logs use each tool's native `get_log_object()` output when available, preserving special log rendering (for example: `code_execution_tool` uses `code_exe`, `wait` uses `progress`, MCP tools use `mcp`, and regular tools use `tool`).
+- Direct parallel worker execution reuses the parent-visible child log item so tool `before_execution()` cannot create a second generic worker log or lose the native badge type.
 - Job IDs are stable handles for later await, collect, or cancel operations.
 - Prompt extras must stay bounded and expose only job IDs, tool names, status, and compact result/error summaries.