# Apply Cuts

> Apply adversarial-edit cuts to chapter files (mechanical quote-matching removal). Wraps scripts/apply_cuts.py. Filters by cut type (OVER-EXPLAIN, REDUNDANT typically yield ~55-60% of cuts). Use after adversarial-edit during revision cycles.

- **Type:** Skill
- **Install:** `agentstack add skill-tchr-dev-autonovel-apply-cuts`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [tchr-dev](https://agentstack.voostack.com/s/tchr-dev)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [tchr-dev](https://github.com/tchr-dev)
- **Source:** https://github.com/tchr-dev/autonovel/tree/main/.claude/skills/revision/apply-cuts

## Install

```sh
agentstack add skill-tchr-dev-autonovel-apply-cuts
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Apply cuts

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

## Common invocations

```bash
# Dry run on all chapters with cuts files
AUTONOVEL_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= python scripts/apply_cuts.py all --types OVER-EXPLAIN REDUNDANT

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

# Single chapter
AUTONOVEL_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

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [tchr-dev](https://github.com/tchr-dev)
- **Source:** [tchr-dev/autonovel](https://github.com/tchr-dev/autonovel)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-tchr-dev-autonovel-apply-cuts
- Seller: https://agentstack.voostack.com/s/tchr-dev
- Browse the marketplace: https://agentstack.voostack.com/browse

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