Compare agent skills before installing.

Source the next ML experiment proposal by **reading the audit digest** at `scratch/audit/<stem>/audit.md` (produced by `audit-ml-pipeline` at § 4 record-outcome). For every row in the digest's `## Checks summary` whose `severity` is `issue` or `tip`, follow the row's `documentation_url` to draft a Backlog row whose `Item` is the mitigation the docs recommend. The `## Metrics summary` provides context for the human summary paragraph but does not drive Backlog rows on its own. Returns the enriched Backlog rows + a one-paragraph summary back to `iterate-ml-experiment`, which writes the rows into `JOURNAL.md` and re-presents the sourcing menu so the user can promote a `B<N>` row. Stops at "Backlog enriched, summary returned"; never writes a per-experiment design note, never picks the "winning" finding — the user picks via `B<N>`. TRIGGER when: `iterate-ml-experiment` is picking a sourcing strategy and the user picks `skore` from the menu; the user says "mine the report", "what does skore s

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