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oh-story-short-scan

Analyzes short-form web fiction platform samples to identify emotional trends and topic opportunities.

677|112|Updated Mar 3, 2026
Search Tags:#creative writing#trend analysis#short story#topic selection#web fiction#Market Research#ranking scan
One-click install
npx skills add https://github.com/LiPu-jpg/Openwrite_skill --skill oh-story-short-scan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oh-story-short-scan
Source: https://github.com/LiPu-jpg/Openwrite_skill/tree/main/tools/runtime_skills/oh-story-short-scan
Command: npx skills add https://github.com/LiPu-jpg/Openwrite_skill --skill oh-story-short-scan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Short-form web fiction markets shift quickly, and authors struggle to judge which emotional hooks, title promises, and plot mechanisms are actually trending versus one-off noise. This Skill structures the research of platform rankings and sample stories so topic decisions rest on dated, sourced evidence instead of guesswork.

Core Features & Use Cases

  • Market Sample Collection: Gathers public samples with links and dates, recording platform, ranking criteria, length, genre, title promises, opening hooks, core emotions, and resolution patterns.
  • Trend Analysis: Compares packaging against actual story delivery using a reference methodology, separating stable patterns, recent signals, and one-time noise while flagging overheated trends.
  • Topic Candidate Generation: Produces multiple short-story candidates with target readers, single core emotion, opening tests, differentiation, submission fit, and risk notes for discussion with the Goethe planning agent.
  • Use Case: An author deciding what to write next for a short-fiction platform can run a scan of current rankings, receive sourced analysis of which emotional hooks are saturated, and get several validated topic candidates with submission risk assessments.

Quick Start

Use the oh-story-short-scan skill to research current short-form web fiction rankings and propose three topic candidates with sources and dates.

Frequently Asked Questions about oh-story-short-scan

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

FAQPage Schema
How do I research short-form web fiction market trends?▼

Collect public samples with links and dates from platform rankings, then record each story's length, genre, title promise, opening hook, core emotion, and resolution type. Compare packaging against actual delivery to separate stable patterns from short-lived noise.

How to validate a short story topic before writing?▼

Define a single core emotion and target reader, then test the title and opening against real market samples. Check whether the emotion can resolve within limited scenes, whether the twist needs excessive explanation, and how saturated the niche already is.

What data should I record when scanning fiction rankings?▼

Record the work, platform, ranking criteria, sampling date, visible performance, length, main and sub genres, core emotion, character relationships, title and blurb promises, opening anomaly, key turns, twist type, resolution, and distribution tags. Leave fields empty when data is not visible.

Does this skill scrape ranking platforms automatically?▼

No. It does not run CDP, browser automation, or scraping scripts, and it does not bypass logins, paywalls, or access restrictions. Without live sources it states that limitation and provides a sampling plan and checklist instead.

What are the limitations of small-sample trend analysis?▼

Small samples cannot support trend claims, so results must distinguish stable patterns, recent signals, and one-time noise. Recommendation slots,影视 tie-ins, author influence, free preview ranges, and platform campaigns all introduce bias that must be noted.

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