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.