Apply Cuts

Apply cuts

Mechanical pass — no LLM call. Reads <novel-dir>/edit_logs/chNN_cuts.json produced by adversarial-edit and removes matching quotes from chapters.

Common invocations

# Dry run on all chapters with cuts files
AUTONOVEL_NOVEL_DIR=<novel-dir> python scripts/apply_cuts.py all --dry-run

# Apply only OVER-EXPLAIN and REDUNDANT cuts (the safest/most common types)
AUTONOVEL_NOVEL_DIR=<novel-dir> python scripts/apply_cuts.py all --types OVER-EXPLAIN REDUNDANT

# Apply all cuts to chapters where adversarial-edit found ≥17% fat
AUTONOVEL_NOVEL_DIR=<novel-dir> python scripts/apply_cuts.py all --min-fat 17

# Single chapter
AUTONOVEL_NOVEL_DIR=<novel-dir> python scripts/apply_cuts.py 12

Failure modes

• not found — the quote doesn't appear in the chapter (often because a previous cut already shifted whitespace; the script tries whitespace-normalised match before giving up)
• ambiguous (N matches) — the quote appears more than once; the script refuses to guess which instance was meant
• Skipped if quote < 25 chars

The script collapses runs of 3+ newlines down to 2 after applying cuts.

After running

Report:

• Total words removed across chapters
• Per-chapter applied / failed / skipped breakdown
• Which chapters had the highest cut counts (revision priorities)

Suggest:

• Re-evaluate any heavily-cut chapter with evaluate-chapter to confirm the score moved in the right direction
• If failed count is high, manually inspect the cuts file — some quotes may need rephrasing in the cuts JSON before retrying