Context size, compaction, and budgets

As a conversation runs, the model’s context keeps growing: more customer turns, more agent replies, more tool calls and results. The runtime automatically manages that context so it stays within model limits — compressing large tool results, replacing older tool results with placeholders, and shortening earlier turns — according to a set of compaction policies you can tune per agent, per project, or per tool. This page lists the default budgets, shows where to set them, and walks through diagnosing a prompt that’s grown too large. For what actually determines which values reach the model in the first place — visibility modes and ## Current Context — see How a turn is built.

Size limits and compaction

Three policies set how much the model reads on a given turn:

tool_results — how tool output is shaped, both this turn and on later turns.
prior_turns — how earlier turns in the conversation history are compacted.
prompt_context — how ## Current Context values are sized and projected.

They merge in this order: platform defaults, then the voice low-latency profile (voice channels only), then project settings, then the agent’s EXECUTION.compaction, then per-tool hints. Nothing trims the conversation to a token budget automatically, so a long-running conversation keeps growing unless you set bounds.

Default values

Policy	Setting	Default	Voice latency profile
`tool_results`	`strategy`	`summarize`	`structured`
	`max_chars`	102,400	16,000
	`structured_threshold`	10,000	4,000
	`keep_recent`	2	1
	`max_description_length`	200	80
	`summary_timeout_ms`	5,000 (1,000 to 30,000)	1,500
`prior_turns`	`strategy`	`compact`	`compact`
	`assistant_preview_chars`	200	120
`prompt_context`	`value_max_chars`	8,000 (40,000 max)	6,000
	`total_max_chars`	24,000 (100,000 max)	16,000
	`auto_tool_result_value_max_chars`	4,000	2,000
	`projection_strategy`	`preview`	`preview`

Prior-turn strategies

Strategy	Effect on earlier turns
`none`	Earlier replies are kept as written. Tool results in history are still placeholders.
`placeholder`	Each earlier tool result is replaced by `[Prior turn result — summarized]`.
`compact` (default)	As `placeholder`, and each reply that followed a tool result is shortened to `assistant_preview_chars`. The agent’s latest reply is kept whole if it is 2,000 characters or less.
`summarize`	Behaves the same as `compact`. No model call is made for this strategy.

Projection strategies for Current Context

A ## Current Context value over its limit is replaced by a marker object (_contextLimited: true) carrying its original type and size, plus one of three levels of detail:

preview (the default) — the first part of the value, as text.
summary — the value’s shape: types, lengths, key names, and up to three sample items.
metadata — type and size only.

Where to set compaction policies

Per agent, in ABL — the EXECUTION.compaction block. See Compaction policy overrides for the full property reference.
Per project — the project runtime configuration, set by API or project import. Studio’s Runtime Config tab exposes these controls only for the voice latency profile overrides; the project-wide section is not editable from Studio.
Per tool — compaction: essential_fields, summary_timeout_ms, and, for knowledge bases, max_search_tokens. See Result compaction.

EXECUTION:
  models:
    summarization: gpt-4.1-mini
  compaction:
    tool_results:
      strategy: summarize
      max_chars: 32000
      structured_threshold: 8000
      keep_recent: 2
      essential_fields:
        search_orders: [id, status, total, createdAt]
      summarize_prompt: "Keep order IDs, totals and statuses."
    prior_turns:
      strategy: compact
      assistant_preview_chars: 300
    prompt_context:
      value_max_chars: 8000
      total_max_chars: 24000
      auto_tool_result_value_max_chars: 4000
      projection_strategy: preview

The compaction policy is resolved once per conversation. In a multi-agent project, set compaction at the project level, or set it the same way on every agent in a handoff chain — it is not re-resolved on handoff.

Memory sections (## Session Memory, ## Granted Memory, ## Gather Progress) are not covered by these limits. Keep declared memory small — see Memory and state. For a single large tool result, a MODEL_CONTEXT view is a better tool than raising a size limit: it’s exact, and it costs no extra model call.

Controlling context size

You control three things: which values may enter the prompt, how large each piece may be, and how long tool output stays around. Most parts of the prompt have a default size limit you can change. Two parts have none — the conversation history and declared session memory — so uncontrolled growth usually starts there. Most cuts leave a marker you can find in a trace; knowledge-base chunk drops and the structural shortening of long lists before a summary do not.

Where context grows

Source	Grows with	Default limit	Your lever
Conversation history	Every turn	None: no token cap, and auto-summarization is off	`prior_turns` (previews of earlier replies), a response `MODEL_CONTEXT` on rich responses, `history: last_n` or `summary_only` on handoffs
Declared session memory (`## Session Memory`, `## Granted Memory`, `## Gather Progress`)	The size of the values you store	None	Declare only what the model needs. Keep large objects in tool results or persistent memory, and use `RESET: per_activation` for scratch values.
`## Current Context`	The number of values visible	8,000 per value, 24,000 in total	Explicit visibility mode, named references instead of `{{context}}`, `prompt_context` budgets
Tool results, this turn	The size of the API payload	Summarized above 10,000 characters; 102,400 at most	`MODEL_CONTEXT` first, then the `tool_results` strategy and `essential_fields`. Avoid `strategy: none` on unbounded APIs.
Tool calls in history	Tool use per turn	Arguments kept for 6 rounds; results become a marker	Hide bulky arguments with `default_source: runtime`
Knowledge-base results	Chunk count and size	40,000 tokens when more than 10 chunks come back	`max_search_tokens`, Top K, Similarity threshold — see Tool-level search settings
Explicit mode	Each declared value	A value can appear in both `## Session Memory` and `## Current Context`	Keep declared memory small
Recall and notes	Cross-channel recall, resolved-intent ledgers, recall instructions	30 messages of 500 characters each; 8 ledger entries	Recall settings; keep `INSTRUCTION` text short

Where context gets cut

Cut point	Default	Marker in the trace	Lever
One `## Current Context` value	8,000 characters	`_contextLimited: true` with a preview, summary, or size	`value_max_chars` (up to 40,000), `projection_strategy`
The whole `## Current Context` block	24,000 characters	Values left out are listed by name	`total_max_chars` (up to 100,000)
An earlier tool result in Current Context	4,000 characters	`_contextLimited`, plus a `## Prior Tool Result Context` note	`auto_tool_result_value_max_chars`
A tool result this turn	Summarized above 10,000 characters; cut at 102,400	`"_summarized": true` or `...[truncated: N chars, showing first M]`	`MODEL_CONTEXT`, `structured_threshold`, `max_chars`, `strategy`
An older result within a long turn	Only the last 2 rounds stay whole	`[Result available — see earlier in conversation]`	`keep_recent`
Tool results on later turns	Always replaced	`COMPACTED FOR CHAT HISTORY`, `[Prior turn result — summarized]`	Save what you need with `on_result: SET`
Earlier tool-backed replies	200-character preview	`[Prior response: "…"]`	`assistant_preview_chars`, or `prior_turns: placeholder`
A `MODEL_CONTEXT` view	16,000 characters or 1,000 items	An “unavailable” marker — the view fails rather than being cut	Select fewer fields
Knowledge-base results	The token budget	Whole chunks dropped from the end	`max_search_tokens`
Handoff history	Full by default	The receiver’s history starts later	`history:` — see History strategies

A budget recipe for a production agent

Declare BEHAVIOR: role: so only declared and granted values reach ## Current Context.
Give every tool with a large or nested result a MODEL_CONTEXT, and save the fields later turns need with on_result: SET.
Keep declared session memory to small scalars. Use RESET: for scratch values.
Use history: last_n or summary_only with a summary on handoffs in long conversations. Pass state with pass, not history.
Set max_search_tokens on every knowledge base, lower for voice.
Set compaction once at the project level so every agent in a handoff chain uses the same budgets, then tune each agent only where needed.
Run a 20-turn test conversation, then check the trace’s Request view and the session Overview’s Token Breakdown for growth from turn to turn.

Debugging a bloated or truncated prompt

Open a session’s Traces tab, pick an LLM step, and open its Request view (see LLM step request and response). Search systemPrompt and messages for _contextLimited, truncated, _summarized, COMPACTED FOR CHAT HISTORY, and Prior response. Also look for Prior turn result, Result available, and an “unavailable” marker. Knowledge-base results leave no marker in the trace, so compare their size against max_search_tokens directly. If the prompt is large and none of these markers explain it, the size is coming from conversation history or a memory section, and the levers in Where context grows apply.

Common mistakes

There is no per-entry switch to hide one declared memory value from the model. Either don’t declare it, or supply it through a runtime-supplied tool parameter instead.
There is no automatic token cap on conversation history. A long-running conversation needs prior_turns, MODEL_CONTEXT, and handoff history settings to stay bounded.
Compaction settings are resolved once per conversation, the first time they’re needed — usually by the agent that starts it — and are not refreshed on handoff. Set them consistently across a handoff chain instead of relying on the receiving agent’s own settings.
The automatic first knowledge-base search for a single-KB agent can’t be turned off. Control its size with max_search_tokens instead.
Studio’s Runtime Config tab edits project compaction only inside the voice profile. Set the project-wide section by API or project import.

Related articles:

How a turn is built — visibility modes and what reaches ## Current Context in the first place.
Compaction policy overrides — the full EXECUTION.compaction property reference.
Result compaction and Store result — per-tool compaction and last_<tool>_result.
Tuning for latency — smaller, stable prompts as a speed lever.

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References

Context size, compaction, and budgets

Size limits and compaction

Default values

Prior-turn strategies

Projection strategies for Current Context

Where to set compaction policies

Controlling context size

Where context grows

Where context gets cut

A budget recipe for a production agent

Debugging a bloated or truncated prompt

Common mistakes

​Size limits and compaction

​Default values

​Prior-turn strategies

​Projection strategies for Current Context

​Where to set compaction policies

​Controlling context size

​Where context grows

​Where context gets cut

​A budget recipe for a production agent

​Debugging a bloated or truncated prompt

​Common mistakes

Size limits and compaction

Default values

Prior-turn strategies

Projection strategies for Current Context

Where to set compaction policies

Controlling context size

Where context grows

Where context gets cut

A budget recipe for a production agent

Debugging a bloated or truncated prompt

Common mistakes