Agent status protocol enables real-time state updates across AI systems
Agent Status Protocol (ASP): A Lightweight Specification for State Reporting in Multi-Agent Systems
Artificial IntelligenceMultiagent Systems
Summary
Many AI systems involve multiple agents working together, but it can be hard to know what each agent is doing or if it's working properly. The authors propose a simple way for different AI agents to send updates about their current situation to a central server. This system also watches for agents that stop responding or run into problems, offering a more reliable view than just listening to what the agents say about themselves. Their method organizes agent states into categories like health, task progress, and control status to give a detailed picture.
What this means in practice
- •For ai system operators: Monitor heterogeneous AI agents’ real-time states and detect failures beyond self-reported data by integrating diverse observations in one dashboard.
- •For distributed software architects: Design monitoring layers for multi-agent AI systems that infer agent health and progress using lightweight event protocols and peer reports.
A position paper. It proposes an approach and reports no results.
Authors
Diego Gosmar, Deborah A. Dahl, Emmett Coin, Csaba Bolyós, Andreas Zettl
Abstract
The Agent Status Protocol (ASP) defines a lightweight way for heterogeneous AI agents to report their operational state to a status server, and for observers such as dashboards to receive that state as soon as it changes. Agents push small JSON events over HTTP POST; the server exposes the aggregated state to observers over Server-Sent Events (SSE). Because an agent that has crashed, hung or been compromised cannot be trusted to report its own failure, ASP does not rely on self-reports alone: the server infers liveness from missed heartbeats, can detect agents that are alive but no longer making progress, and accepts observations from supervisors, guardrails, operators and peers, some of which take precedence over what the agent says about itself while others are shown alongside it. ASP models state along independent dimensions (lifecycle, health, task, floor, governance), so that an agent can be, for example, online, degraded, working on a task and waiting for the floor at the same time. It reuses existing vocabularies: task states from the Agent2Agent (A2A) protocol, floor states from the Open Floor Protocol (OFP), and attribute conventions from the OpenTelemetry GenAI semantic conventions. This paper presents version 0.1 of ASP as a proposal, not as an approved standard. It is a working draft intended to open a discussion, and the authors invite comments, alternative proposals and independent implementations from the community.