audit-ml-pipeline

Owns the audit/ folder: one # %% (jupytext percent) Python file per experiment, aligned 1:1 with experiments/NN_<short_name>.py and journal/NN_<short_name>.md, that loads the experiment's skore report read-only and uses bare-last-expression cells whose __repr__ carries the audit's signal. The agent executes the audit file via the bundled in-process runner (audit-ml-pipeline/scripts/run_cells.py — IPython InteractiveShell.run_cell), which streams a markdown digest of each cell's stdout + last-expression repr to stdout (optionally also to a file). The digest fuels narrative work (the JOURNAL.md Status + History update, follow-up questions about a past experiment, cross-experiment comparison). Stops at "audit/NN_*.py is placed, executed, and the digest is available." Never calls skore.evaluate(...) or project.put(...).