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Kevin Codex
865bd5c22b
Compaction summarization was the single most expensive recurring event
in a long run: the full elided middle — verbatim tool bodies included —
went to the session's main model at full price (a ~100k-token call near
a 200k window, recursively multiplied on overflow).
Four changes, each independently safe:
- Dedicated summarizer model. Compaction summaries route to a cheap
model resolved as ZERO_COMPACTION_MODEL > preferences.compactionModel
> a curated default on official endpoints (Haiku 4.5 / Gemini
Flash-Lite / gpt-4.1-mini; custom-endpoint catalogs are unknowable so
they get none). Built lazily on the first paid compaction; ANY
failure permanently falls back to the main provider for the run, so a
misconfigured summarizer can never break compaction. "main" at any
level forces the old behavior.
- Summarizer input caps. renderTranscript clamps tool-result bodies to
2,000 chars and tool-call arguments to 500 (head+tail, rune-safe) —
the summary needs what was done and decided, not raw payloads. Cuts
summarizer input 5-10x on tool-heavy sessions.
- Free reactive prune. recover() now runs the same prune-first stage as
the proactive path: a context-limit error is first answered by
pruning stale tool bodies at zero cost, without consuming the
one-shot reactive budget; the paid summarizer only runs when a later
error finds nothing left to prune.
- Window re-derivation on model switch. Options.ContextWindowFor
(wired to the model registry in exec and the TUI) lets the loop
re-derive the compaction threshold after escalate_model, closing the
documented KNOWN LIMITATION where a switch to a smaller-window model
could overflow and a larger one over-compacted.
## Rebase notes (2026-08-25, onto 2749447c)
Rebased across 214 commits. main now summarizes through the context planner
(#879) and switches models via turn sessions, so the agent side was reworked
rather than merged textually:
- Summarizer selection lives on compactionState and is resolved lazily per
main model through summarizeWithPlanner (planner + trace preserved); a
failing dedicated summarizer is marked broken and the same slice is
retried once on the main provider.
- Options.Summarizer now receives the main model in force:
`func(ctx, mainModelID string) (Provider, error)`, and may return
(nil, nil) when no dedicated model applies. After a successful
escalate_model switch the loop calls compactor.switchModel, which
re-derives the window and re-resolves the summarizer — a run that started
on the cheap model and escalated regains cheap summaries (review P2).
- recover()'s free prune stage runs before the one-shot reactive guard
(pruning is free and cannot loop) and mirrors maybeCompact's two prune
passes; the free retry is taken only when the pruned history fits the
window the provider enforces (with a 5% estimate margin), otherwise the
same call falls through to the paid summarizer. Gating on the 70%
proactive threshold would have sent histories in the 70-95% band to the
summarizer unnecessarily (review P1 and the follow-up question).
- ContextWindowFor is wired through the turn-session switch path; the
planner's window is updated alongside the compactor's.
Tests: the PR's suite is ported to the new seams, plus insufficient-prune
fall-through, free prune after the budget is spent, window-vs-threshold
gating, and summarizer re-resolution across a model switch.