agent-team-protocol

Multi-agent coordination is achieved by standardizing agent registration on startup, enabling structured messaging, task creation, and context sharing via set_context and get_context functions. This protocol allows autonomous agents to discover team roles, orchestrate tasks, and update progress collaboratively.

Standardizing multi-agent messaging and task management involves applying a protocol where orchestrators create tasks and specialists update progress with structured data. Agents register on startup, assume defined team roles, and exchange messages to maintain synchronized task tracking and contextual awareness.

Agent registration and context sharing work by requiring agents to register on startup to discover team roles, followed by utilizing set_context and get_context methods to store and access shared data. This mechanism ensures teammates coordinate work effectively by maintaining a shared contextual state.

Yes, a multi-agent protocol supports assigning and tracking tasks across different agent roles by defining a set of roles per team. Orchestrators create tasks and specialists update progress using structured data, ensuring clear task management and role-based coordination across autonomous agents.

You need a standardized protocol for multi-agent coordination in environments where autonomous agents must register on startup, exchange messages, assign and track tasks, and share contextual data. It is essential for orchestrating specialized agents that require structured role discovery and synchronized context sharing.