hub-spoke

name	hub-spoke
description	Implement a central Coordinator (Hub) that manages, distributes, and merges tasks performed by specialized worker sessions (Spokes). Spokes communicate only with the Hub and not with each other. Useful for ad-hoc project management and complex workflow distribution. Triggers: "허브 스포크", "중앙 통제", "작업 배분", "hub and spoke", "coordinator pattern", "centralized workflow".

Hub-and-Spoke

The Hub-and-Spoke pattern designates a central Coordinator session (Hub) to manage planning, task distribution, progress checking, and final result merging. The Worker sessions (Spokes) execute their specific assignments independently and communicate only with the Hub.

5-Stage Workflow

         ┌───────────────┐
         │  Coordinator  │ ◄── Planning, task queue, and spoke bridging
         └───────┬───────┘
       ┌─────────┼─────────┐
       ▼         ▼         ▼
    Worker    Worker    Worker
     (A)       (B)       (C)

1. Role Definition: Spawn a dedicated Coordinator session (Hub) and define specialized Spoke Worker configs.
2. Task Planning: The Hub analyzes the goal, creates a task dependency list, and allocates work.
3. Execution Routing:
   • The Hub spawns Spokes asynchronously using agent__startSession(waitForResult=false).
   • Spokes work in isolation. If inter-spoke coordination is needed, the Hub routes messages. See routing.md.
4. Monitoring: The Hub polls Spoke statuses via agent__checkSession.
5. Synthesis: The Hub merges all finished spoke artifacts and runs integration checks.

🛠️ MCP Tools Guide

• Context Management: Do not let the Hub read all conversation logs from all Spokes to prevent context overflow. Instruct the Hub to only request summarized status reports and file list results.
• Message Bridging: If Worker B depends on Worker A's output, the Hub collects the artifact details from A and injects them to B via agent__messageToSession.

References

• Routing patterns
• Status polling
• Context budget