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Krzysztof kuhy Rudnicki
c5cd63fb80
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Counting transcript records reports 1.00 tool calls per message no matter what the model did: the harness writes one JSONL record per tool_use block, all sharing message.id. A hand-rolled per-record count read the real 1.9% batching rate as 0.0%, which nearly shipped as a headline finding. Group by message.id instead, and report it, so the number comes from a tested code path with the window handled by find_transcripts rather than an ad-hoc timestamp. Three snapshot fields give next week's run a baseline. Axes was at the 12-attribute cap, so the counters live in their own Batching dataclass with the two ratios as properties. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NiSSDu4gKbp9GGxTTtXvYW |
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| .. | ||
| __init__.py | ||
| test_attribute.py | ||
| test_checkup.py | ||
| test_cli.py | ||
| test_model.py | ||
| test_parse_events.py | ||
| test_parse.py | ||
| test_probe.py | ||
| test_report.py | ||
| test_surfaces.py | ||
| test_unused.py | ||