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reacechalmers
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`maybe_auto_compact` gated on `usage_tracker.cumulative_usage().input_tokens`, which is wrong in two independent ways: 1. It ignores cached input. With prompt caching a warm call reports `input_tokens: 2` and puts the real context in `cache_read_input_tokens`, so the counter barely moved and auto-compaction never fired at all, however large the conversation grew. Backends without prompt caching report the whole prompt as `input_tokens`, so the bug was invisible there. 2. A sum across calls is not a context measurement, and it never decreases. Once it did cross the threshold, every subsequent iteration compacted again, permanently, even after compaction had shrunk the context. Gate on the latest call's total input instead — input + cache_creation + cache_read — which is the live context window size. It rises with the real context and falls back below the threshold once compaction has done its job, so no counter reset is needed. `CLAUDE_CODE_AUTO_COMPACT_INPUT_TOKENS` now means what it reads like: compact when the live context reaches N tokens. The default of 100_000 is unchanged and still lands at 50% of a 200k window. Adds `TokenUsage::total_input_tokens()` (saturating) and four tests: the cached-usage shape that never fired, non-latching across three turns, and two unit tests for the new helper. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_013bVvRYn7CQKR6hT2j1L6Cs (cherry picked from commit aebba4e77eddf585fc5b21123967dbc4ebb6e6a1)