cross-agent

Cross-Agent Delegation

Enable agents to delegate tasks to peer agents using auto-generated tools like ask_agent_researcher and broadcast_to_agents.

Quick Example

import asyncio
from promptise import build_agent
from promptise.config import HTTPServerSpec
from promptise.cross_agent import CrossAgent

async def main():
    # Build a specialist peer agent
    researcher = await build_agent(
        servers={"search": HTTPServerSpec(url="http://localhost:8001/mcp")},
        model="openai:gpt-5-mini",
        instructions="You are a web research specialist.",
    )

    # Build the main agent with delegation to the peer
    agent = await build_agent(
        servers={"files": HTTPServerSpec(url="http://localhost:8002/mcp")},
        model="openai:gpt-5-mini",
        cross_agents={
            "researcher": CrossAgent(agent=researcher, description="Web research"),
        },
    )

    result = await agent.ainvoke({
        "messages": [{"role": "user", "content": "Research the latest trends in AI safety"}]
    })
    print(result["messages"][-1].content)

    await agent.shutdown()
    await researcher.shutdown()

asyncio.run(main())

Concepts

Cross-agent delegation lets a primary agent call peer agents as if they were regular tools. When you pass the cross_agents parameter to build_agent(), Promptise generates two kinds of tools:

1. Per-peer ask tools -- For each peer named <name>, a tool called ask_agent_<name> is created. The primary agent calls this tool to forward a message to that specific peer and receive its response.
2. Broadcast tool -- A single broadcast_to_agents tool that sends the same message to multiple peers in parallel and returns a mapping of peer name to response.

Peers are standard LangChain Runnable objects (typically PromptiseAgent instances returned by build_agent()). No new infrastructure is required -- delegation happens in-process via async calls.

Primary Agent
  |
  |-- ask_agent_researcher(message="...")  --> Researcher Agent --> response
  |-- ask_agent_analyst(message="...")     --> Analyst Agent   --> response
  |-- broadcast_to_agents(message="...")   --> [all peers]     --> {name: response}