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kuhyx
5ffd035c21
Cache read is charged per API round-trip on the whole conversation so far, so a long session's cost is driven by TURN COUNT, not message length. One measured session spent 267M cache-read against 856k output — a ratio of 290:1. The report priced tokens but never counted the turns spending them. Across the 263 stored transcripts this now shows 33,508 tool turns at an 8% batching rate, of which 4,437 (13%) decided nothing: polling a counter, running a linter, checking whether a push landed. At 606k average context re-read per turn that is ~2.7B cache-read tokens on turns a script could have taken. - turns.py classifies a command as poll / lint_test / vcs_check / substantive, deliberately conservative: state-changing commands (git commit, push) count as substantive even though they are scriptable, so the reported waste is a floor. A turn is only mechanical when EVERY command in it is. - Batching is grouped by requestId, not by transcript line: one API response can span several lines, and counting per line reports every turn as single-tool (0% batching where the real rate is 12%). - records.py gains TurnEfficiency (schema v3, additive — old records read as zeros) with derived rates written into to_dict so readers need not recompute. - report.py gains a "Turn efficiency" section pricing each mechanical kind. - _TurnTracker owns both the totals and the open turn, after pylint flagged _Accumulator over its attribute budget; _Accumulator.turns is now a property, so every existing caller is unchanged. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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| .. | ||
| tests | ||
| __init__.py | ||
| __main__.py | ||
| cli.py | ||
| config.py | ||
| detectors.py | ||
| parse.py | ||
| records.py | ||
| report.py | ||
| signatures.py | ||
| stats.py | ||
| store.py | ||
| traces.py | ||
| turns.py | ||