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