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22 lines
1.2 KiB
Markdown
22 lines
1.2 KiB
Markdown
# Third independent review of the autonomous candidate
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A third fresh reviewer rejected the candidate on two concrete findings:
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1. `derive_trajectory_signals()` can count one tool result as two errors when a
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valid envelope contains both top-level `"success": false` and nested
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`content.success: false`. Each recognized tool result must contribute at
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most one to `tool_errors`.
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2. `mini_swe_runner.py` directly persists converted ShareGPT trajectories and
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still omits the new evaluation metadata. Inspect this path and either bring
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it under the shared entry contract without changing its existing output
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behavior, or explicitly narrow and justify the feature boundary if it is a
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genuinely different artifact. The current report must not claim consistent
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coverage while silently excluding it.
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Add regression coverage for the per-result count invariant and the selected
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handling of the mini-SWE path. Search once more for equivalent direct
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ShareGPT/trajectory persistence sites so the report can state its scope
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accurately. Run the focused and relevant existing tests, compilation, and
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`git diff --check`; update the report with exact results. Do not commit, push,
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or edit the book repository.
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