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xingBaGan
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editor-rubric

Score novel chapters against predefined criteria and output PASS, REVISE, or REJECT outcomes.

Updated May 23, 2026
Search Tags:#JSON schema#structured feedback#automated scoring#editor review#novel studio
One-click install
npx skills add https://github.com/xingBaGan/FANovelist --skill editor-rubric
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: editor-rubric
Source: https://github.com/xingBaGan/FANovelist/tree/main/examples/novel-studio/skills/editor-rubric
Command: npx skills add https://github.com/xingBaGan/FANovelist --skill editor-rubric

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jsonschema, json, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the need for a standardized and efficient process for executive editor chapter reviews by providing a JSON schema that simplifies the review process.

Core Features & Use Cases

  • Standardized Review Format: Utilizes a JSON schema to ensure consistency in the structure of review data.
  • Automated Scoring: Scores chapters based on predefined criteria, including theme alignment, premise alignment, pacing, voice consistency, and prose quality.
  • Review Outcomes: Categorizes reviews into PASS, REVISE, or REJECT based on the scores and identifies specific areas requiring attention.
  • Use Case: For a novel studio, this Skill can be used to streamline the review process for executive editors, ensuring that feedback is clear and actionable.

Quick Start

Run the editor-rubric skill to create a review for chapter 'ch01'.

Frequently Asked Questions about editor-rubric

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

FAQPage Schema
How do I standardize executive editor chapter reviews using a JSON schema?▼

You can standardize executive editor chapter reviews by applying a JSON schema to enforce consistent structured feedback across theme alignment, pacing, and prose quality. This ensures every novel chapter review yields uniform, machine-readable data.

How does automated scoring work for novel chapter editing?▼

Automated scoring evaluates novel chapters against predefined criteria like premise alignment, voice consistency, and prose quality using Python logic. It calculates scores and outputs standardized review outcomes such as PASS, REVISE, or REJECT.

Do I need Python to validate JSON schema for structured editor feedback?▼

Yes, you need Python along with the jsonschema and json dependencies to validate the JSON schema and execute the automated scoring logic. These libraries handle the structured feedback validation and review outcome categorization.

What review outcomes does the automated scoring schema generate for chapters?▼

The automated scoring schema generates PASS, REVISE, or REJECT outcomes based on chapter scores. It identifies specific areas requiring attention, ensuring executive editor feedback is clear and actionable for the novel studio workflow.

Can I use this JSON schema rubric for collaborative novel studio workflows?▼

Yes, the JSON schema rubric is designed for novel studio workflows to streamline the executive editor review process. It provides a standardized review format that makes chapter feedback clear, actionable, and consistent across multiple editors.

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