novel-editing-patterns

Diagnose and repair web novel chapters for pacing, word count, and consistency.

Updated Jul 31, 2026
One-click install
npx skills add https://github.com/cwjdong-design/novel --skill novel-editing-patterns-cwjdong-design
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: novel-editing-patterns
Source: https://github.com/cwjdong-design/novel/tree/main/novel-editing-patterns
Command: npx skills add https://github.com/cwjdong-design/novel --skill novel-editing-patterns-cwjdong-design

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Web novel chapters often suffer from pacing deserts, hollow character arcs, word count misses, cross-chapter inconsistencies, and unreliable AI drafting output. This Skill provides a field-tested playbook of repair patterns to diagnose and fix these quality problems systematically. ## Core Features & Use Cases - Pacing & Satisfaction Repair: Diagnose zero-payoff chapters and inject data comparisons, internal monologues, external viewpoints, or end hooks with minimal disruption to the main plot. - Word Count Discipline: Enforce the 2200-2400 character standard with effective-content density gates, oscillation stop-loss ladders, and rules against padding with scenery or repetition. - Consistency & Audit Workflows: Run cross-chapter entity/location scans, timeline arithmetic checks, dialect standardization audits, and five-evidence verification of Claude Code drafting output. - Use Case: A 2200-word chapter comes back at 1800 words after over-compression. Use the stop-loss ladder to patch in valid plot beats (character reactions, financial details) via targeted edits instead of re-dispatching a full rewrite. ## Quick Start Ask the AI to diagnose and repair the pacing and word count problems in chapter 34 using the editing patterns playbook.

Frequently Asked Questions about novel-editing-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix a web novel chapter with no satisfying payoff moments?

Diagnose the chapter against five payoff checks (money landing, shock reactions, face-slapping, income comparison, system mystery). Then inject low-disruption fixes like a system data comparison, an internal resource-counting monologue, or an external observer's viewpoint, limited to two injection points per chapter.

How to enforce a 2200 word count target in AI-generated chapters?

Use the dual-gate standard: 2200-2400 characters plus content density of at least one plot change per 500 characters. Never pad with scenery or repetition; instead add valid plot beats like conflict escalation, character decisions, or financial specifics, verified with review_scan.py.

What should I do when Claude Code output is too short or times out?

After two consecutive Claude Code failures, the main agent takes over drafting directly. For over-compressed output below 2200 characters, apply targeted patches with valid plot content rather than re-dispatching full rewrites, following the word count oscillation stop-loss ladder.

How do I check cross-chapter consistency for locations and timelines?

When one error is found, search all chapters for the same keyword pattern and related entities before fixing. Verify geographic feasibility against each character's current position, and compute timeline windows explicitly from anchor dates before allowing result-type events.

Can this skill handle dialect overuse in novel dialogue?

Yes, it includes a dialect audit workflow: scan chapters for dialect characters, classify each line as keep-or-replace based on character identity, batch-patch with backups, then update the book configuration so future chapters follow the quantified dialect limits.