story-long-scan

Analyze ranking data from Qidian, Fanqie, Jinjiang, and Qimao to identify recurring genres and story hooks.

482|72|Updated May 24, 2026
One-click install
npx skills add https://github.com/uu201/character-arc --skill story-long-scan-uu201
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: story-long-scan
Source: https://github.com/uu201/character-arc/tree/main/resources/skills/oh-story-claudecode/story-long-scan
Command: npx skills add https://github.com/uu201/character-arc --skill story-long-scan-uu201

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Long-form web fiction topic selection is time-consuming and uncertain; this Skill automates cross-platform scanning to reveal market signals and guide topic decisions.

Core Features & Use Cases

  • Cross-platform Trend Discovery: Analyze ranking data from major platforms to surface recurring genres, motifs, and opening hooks.
  • Feasible Topic Validation: Provide actionable candidate ideas with initial feasibility signals and risk notes.
  • Phase-aligned Outputs: Generate a Phase 2 report and a Phase 4 topic-decision draft for project planning.

Quick Start

Trigger with /story-long-scan to run a full cross-platform scan and generate a Phase 2 report with topic recommendations.

Frequently Asked Questions about story-long-scan

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

FAQPage Schema
How do I identify trending web fiction genres across multiple platforms?▼

Cross-platform scanning analyzes ranking data from Qidian, Fanqie, Jinjiang, and Qimao to surface trending genres, recurring motifs, and opening hooks for web fiction topic selection. It enforces data-quality checks to ensure signal reliability.

What is the best way to validate long-form web fiction topics before writing?▼

Validating long-form web fiction topics requires analyzing market signals from ranking data to generate a Phase 4 topic-decision draft. This draft provides actionable candidate ideas with initial feasibility signals and risk notes for project planning.

Can I use ranking data to find recurring story hooks for web novels?▼

Ranking data analysis extracts repeatable market signals to identify recurring story hooks across major web fiction platforms. The generated Phase 2 report structures these findings to guide your topic selection process.

Does cross-platform market analysis work for both Qidian and Jinjiang rankings?▼

Cross-platform market analysis supports Qidian, Fanqie, Jinjiang, and Qimao rankings simultaneously. It surfaces recurring genres and trending themes across these platforms to produce structured reports for topic validation.

How do I generate a topic-decision draft for web fiction project planning?▼

Generating a topic-decision draft involves running a cross-platform scan to process ranking data and extract market signals. The Skill outputs a Phase 2 report and a Phase 4 topic-decision draft containing feasible candidate ideas and risk notes.

What limitations exist when scanning web fiction rankings for genre trends?▼

Scanning web fiction rankings relies on available platform data and enforces data-quality checks to filter noise. Topic validation outputs provide initial feasibility signals and risk notes, but final decisions require manual review of the generated Phase 4 draft.