peter-zhou-mistake-bank

# Mistake Bank Use this subskill when a recognized result must become canonical local data. Core contract: - Persist one JSON file per subject under the mistake bank. - Keep `SourceDocument` state separate from subject mistake records. - Keep `is_wrong=false` records for audit, but exclude them from final stats and practice by default. - Generate review reports from canonical data; do not persist separate long-lived review tables. - Allocate ids and write JSON only through `scripts/allocate_id.py` and `scripts/json_store.py`; see `references/schema.md`. - After every successful `scripts/intake_recognition.py ingest`, present the returned `review_report` as the next skill step for user review. Focus the user on `needs_review=true`, low-confidence answers, ambiguous teacher marks, and crop screenshots. If the user does not review, leave the source status as `processed`; only `apply-review --confirm` moves it to `confirmed`. - Use `scripts/intake_recognition.py review-report` to regenerate the same derived report, `apply-review` for user corrections/confirmation, and `repair-crops` for script-owned screenshot bbox fixes.