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3d8214a147
PlannerLoopInput grows an optional compactor:
compactor?: {
maxContextTokens: number;
threshold?: number; // default 0.92, matches Claude Code wU2
compact: (messages) => Promise<{ messages, compactedTurns }>;
}
Before each LLM call the loop checks whether promptTokens+completion
has crossed threshold × maxContextTokens. If yes AND we haven't
compacted this run yet, the callback runs, its returned messages
REPLACE the live history, and compactionsDone flips to 1 so a
runaway tool can't re-trigger.
Design choices:
- Fires at most ONCE per loop run. If the fresh (compacted)
history hits the threshold again in the same run, the LLM
round budget will hit first; better to terminate than to
recursively compact a summary.
- No reminder emitted automatically — the caller can wire
that via reminderChannel by reading compactionsDone from
LoopState (next PR; compactionsDone isn't exposed yet to
keep the state surface small).
- compactor callback is injectable, not hardcoded to
compactHistory() from compact.ts. Lets mana-ai route the
compactor LLM call to a cheaper model (Haiku) without
changing the loop.
- Zero maxContextTokens → skip silently (same contract as
shouldCompact()).
Also cleaned up the isParallelSafe non-null-assertion warning by
hoisting the predicate to a local with proper narrowing.
5 new loop tests: below-threshold no-op, single-fire replacement,
once-per-run idempotency, zero-cap bail, no-op when compactor
returns 0 turns. 76 shared-ai tests total, green.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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