Webnovel Scan

Community

ricky-theseus

webnovel-scan

网文扫榜。按模式分为长篇扫榜和短篇扫榜，覆盖起点/番茄/晋江/七猫/知乎盐言/黑岩/点众等平台。分析排行榜数据，提炼市场趋势与热门题材。

Overview

Publisher	ricky-theseus
Repository	`DaisyWriter`
Skill name	`webnovel-scan`
Stars	77
Forks	5
Bundled files	Instructions only
License	GPL-3.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ricky-theseus on GitHub. Read the source before you install it.

Installation

Install the Webnovel Scan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/ricky-theseus/DaisyWriter/tree/master/skills/webnovel/scan
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ricky-theseus/DaisyWriter.git /tmp/DaisyWriter
mkdir -p .claude/skills
cp -r /tmp/DaisyWriter/skills/webnovel/scan .claude/skills/webnovel-scan

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Webnovel Scan in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Webnovel Scan on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Webnovel Scan is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

网文扫榜 · webnovel-scan

合并自 story-long-scan（长篇市场分析）+ story-short-scan（短篇市场分析）。根据 模式选择 路由。

核心信念：

长篇：单本排名只提供线索；跨样本重复模式才算信号。
短篇：短篇市场变化快，题材信号有效期短。扫榜报告必须标注样本日期和趋势可信度。

模式选择

模式	命令	适用
长篇	`/webnovel-scan long`	起点/番茄/晋江/七猫等长篇排行榜
短篇	`/webnovel-scan short`	知乎盐言/七猫短篇/黑岩/点众短篇

长篇扫榜流程

Phase 1：确认平台和方向

问用户：「你想看哪个平台？（起点/番茄/晋江/其他）有没有关注的题材方向？」

Phase 1.5：确定数据来源

优先级	模式	说明
1	脚本采集	直接抓取平台页面/SSR 数据产出结构化文件
2	用户提供	用户粘贴榜单截图/文字/链接
3	内置知识	基于知识库趋势数据做分析

起点采集目标： 新人签约新书榜、签约作者新书榜、月票榜、畅销榜、阅读指数榜、收藏榜、三江推荐。使用 scripts/qidian-rank-scraper.js，默认移动端 SSR 模式，不需 Chrome。

番茄采集目标： 男频阅读榜、女频阅读榜、新书榜。使用 scripts/fanqie-rank-scraper.js，配合 browser-cdp。

晋江采集目标： 收入金榜，使用 scripts/jjwxc-rank-scraper.js。

七猫采集目标： 排行榜总入口，大热榜/新书榜/完结榜。

Phase 2：数据分析

起点分析维度： 月票榜/畅销榜/签约作者新书榜/公众作者新书榜/三江推荐/追读率。

番茄分析维度： 阅读榜在读数/新书榜/题材分布/标签热词。

晋江分析维度： 金榜综合热度/季度榜中期趋势/收藏与营养液。

通用分析维度： 题材分布、新题材信号、经典题材变化、字数与更新、书名模式、开头卖点、新元素对比。

Phase 3：输出扫榜报告


# 长篇网文扫榜报告：{平台名称}

## 市场概况
- 扫榜时间：{日期}
- 核心发现：{一句话总结}

## 题材热度排行
| 排名 | 题材 | 榜上数量 | 趋势 | 代表作 |
|------|------|----------|------|--------|

## 新题材信号/经典题材动态/新元素提取
...

## 值得关注的方向
1. {方向 + 为什么值得关注 + 可行性评估}

Phase 4：选题决策

把扫榜结果变成能直接用的选题建议，产出 选题决策.md。选题四步：能爆的原因 → 市场验证 → 差异化定位 → 可行性+失败风险+验证动作。

输出到 {outdir}/选题决策.md。

短篇扫榜流程

Phase 1：确认平台和方向

问用户：「你想看哪个平台？（知乎盐言/番茄短篇/七猫短篇/其他）有没有想写的类型方向？」

Phase 1.5：确定数据来源

优先级	模式	说明
1	browser-cdp 采集	直接抓取平台页面，产出结构化文件
2	用户提供	用户粘贴榜单截图/文字/链接
3	内置知识	基于知识库趋势数据和方法论做分析

点众采集目标： 男频短篇/女频短篇，使用 scripts/dz-browse-scraper.js。 黑岩采集目标： 书库列表，使用 scripts/heiyan-booklist-scraper.js（需要登录）。

Phase 2：数据分析

知乎盐言分析维度： 热门榜单、高赞故事、新作者上榜、付费转化率、标签分布。

通用分析维度： 情绪类型分布、题材热点、篇幅分布、开头模式、结尾类型、标题模式、人设模型。

Phase 3：输出短篇扫榜报告


# 短篇网文扫榜报告：{平台名称}

## 市场概况
- 扫榜时间：{日期}
- 核心发现：{一句话总结}

## 情绪热度排行
| 排名 | 情绪类型 | 榜上数量 | 趋势 |
|------|----------|----------|------|

## 风口预警
- 🔥 正在爆发：{题材}
- ⚡ 即将起风：{题材}
- ⚠️ 即将饱和：{题材}

Phase 4：选题匹配

关键判断：情绪拉扯力 > 题材创新力。开头 3 句话是留存高风险区。

平台特性速查

平台	调性	核心指标	主力读者	适合类型
起点中文网	男频为主，硬核爽文	追读率、月票	18-35 男性	玄幻、都市、科幻
番茄小说	下沉市场，免费阅读	在读数	大众读者	脑洞、快节奏、强爽感
晋江文学城	女频为主，精品路线	收藏、营养液	16-30 女性	言情、纯爱、衍生
七猫小说	下沉市场，免费阅读	热度	大众读者	快节奏爽文
知乎盐言	精品短篇，情绪深度	付费转化	20-35 都市人群	虐恋、反转、悬疑
黑岩短篇	极端情绪，快节奏	完读率	混合	虐恋、复仇、反转
点众短篇	精品快节奏	完读率	混合	家庭复仇、假千金

参考资料

文件	何时加载
references/topic-decision.md	长篇 Phase 4 选题决策
references/real-market-data.md	短篇跨平台写作差异对照
references/genre-trends.md	题材趋势候选
references/publishing-guide.md	平台适配+推荐机制
references/scan-output-format.md	采集字段定义+输出模板

Frequently asked questions

What does the Webnovel Scan AI skill do?

网文扫榜。按模式分为长篇扫榜和短篇扫榜，覆盖起点/番茄/晋江/七猫/知乎盐言/黑岩/点众等平台。分析排行榜数据，提炼市场趋势与热门题材。

Why use Webnovel Scan on TypingMind?

Because you install it once and use it with any model. Webnovel Scan is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Webnovel Scan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ricky-theseus/DaisyWriter/tree/master/skills/webnovel/scan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Webnovel Scan?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Webnovel Scan?

As many as you like. As long as a model supports skills, you can use Webnovel Scan with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Webnovel Scan AI skill free?

Yes. It is published on GitHub by ricky-theseus under the GPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

网文扫榜 · webnovel-scan

模式选择

长篇扫榜流程

Phase 1：确认平台和方向

Phase 1.5：确定数据来源

Phase 2：数据分析

Phase 3：输出扫榜报告

Phase 4：选题决策

短篇扫榜流程

Phase 1：确认平台和方向

Phase 1.5：确定数据来源

Phase 2：数据分析

Phase 3：输出短篇扫榜报告

Phase 4：选题匹配

平台特性速查

参考资料

Frequently asked questions

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