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Every non-tool_use stop reason was logged as 'LLM output truncated', mislabelling end_turn/stop_sequence responses that carried a complete tool block.
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Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015rnEEjXWDBdePRhKMmZr1w
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015rnEEjXWDBdePRhKMmZr1w # Conflicts: # tests/test_client.py
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This change is already in Generated by Claude Code |
Summary
_call_anthropiclogged theLLM_OUTPUT_TRUNCATEDwarning for every stop reason other thantool_use, includingend_turnandstop_sequence, so a plain "no tool_use block" failure was misreported as truncation. This narrows the warning tostop_reason == "max_tokens"and emits a debug-levelLLM_UNEXPECTED_STOPline for the other stop reasons.Stacked on #100 (
fix/openai-failed-status).Test plan
test_client.pycase:end_turnwith no tool block raises the "no tool_use block" error and does not log the truncation warning (fails on base, passes here)