State Loss in Hierarchical Multi-Agent System with Deep Agents and Custom AgentState

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LangGraph State Loss in a heirarchial multi agent system with deep agents and agent

Problem Summary

I’m experiencing state loss when using nested deep agents (create_deep_agent) with a regular agent (create_agent) that has a custom state schema (subagentstate). The custom state updates made via ToolRuntime and Command.update within tools are lost when control returns from the agent to the parent deep agent.

Architecture

1_DeepAgent(State) → 2_DeepAgent(State) → 3_Agent(subagentstate) → Tool(ToolRuntime)

State Schemas

Top-Level State

class State(TypedDict):
    subagentstate: Optional[subagentstate]
    call_trace: Annotated[List[str], operator.add]

Custom Subagent State

class subagentstate(TypedDict):
    user_id: str

Implementation

Top-Level Supervisor (Deep Agent 1)

top_level_supervisor = create_deep_agent(
    model=llm,
    system_prompt=supervisor_prompt,
    subagents=[Subagent1, Subagent2],
    context_schema=State,
    checkpointer=SHORT_TERM_MEMORY,
    store=LONG_TERM_MEMORY,
)

Second-Level Supervisor (Deep Agent 2)

second_level_supervisor = create_deep_agent(
    model=llm,
    system_prompt=second_supervisor_prompt,
    subagents=[agent1, agent2],
    context_schema=State
)

Agent with Custom State Schema (Regular Agent)

agent1 = create_agent(
    model=llm,
    system_prompt=agent_prompt,
    tools=[
        tool1,
        tool2
    ],
    middleware=[
        TodoListMiddleware(
            system_prompt=custom_todo_prompt,
            tool_description=custom_todo_description,
        ),
        SummarizationMiddleware(model=llm, summary_prompt=custom_summary_prompt)
    ],
    response_format=customAgentResponse,
    state_schema=subagentstate,
    name="agent1",
)

Tool Implementation

@tool(
    "tool1",
    description="manipulates the user id",
    args_schema=ToolInputschema
)
def tool1(
    runtime: ToolRuntime,
) -> Command:
    user_id = runtime.state.get("user_id")
    tool_call_id = runtime.tool_call_id
    
    return Command(
        update={
            "messages": [
                ToolMessage(
                    content=f"user id updated",
                    tool_call_id=tool_call_id,
                )
            ],
            "user_id": "new_user_123"  
        },
    )

Observed Behavior

  1. Tool executes and returns Command with state updates
  2. Updates are applied within the agent’s execution context
  3. When control returns from agent1 to second_level_supervisor, the custom state updates are lost
  4. The user_id field in subagentstate reverts to its previous value or becomes None

Expected Behavior

Custom state updates made within tools should propagate back through the agent hierarchy and be accessible in the parent deep agent’s state.

Question

Is this expected behavior when nesting deep agents with a regular agent that uses a custom state schema? What’s the recommended approach for maintaining custom state across this hierarchy?