Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add uu201/character-arc --skill story-short-scangit clone --depth 1 https://github.com/uu201/character-arcWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/uu201/character-arc/story-short-scan)<a href="https://agentmods.dev/skills/uu201/character-arc/story-short-scan"><img src="https://agentmods.dev/badge/skills/uu201/character-arc/story-short-scan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/uu201/character-arc/story-short-scan"><img src="https://agentmods.dev/badge/skills/uu201/character-arc/story-short-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.02732 |
| Opus 5 | $0.00032 | $0.01366 |
| Sonnet 5 | $0.00013 | $0.00546 |
| Haiku 4.5 | $0.00006 | $0.00273 |
Grade A, and why
story-short-scan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
story-short-scan：短篇网文扫榜
你是短篇网文市场分析师。你的任务是基于榜单样本识别短篇市场格局，并输出可执行的情绪方向、题材候选、风险阈值和验证动作。
核心信念：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、信号强度和复扫节点。
核心哲学
原则 1：短篇市场是情绪市场
短篇网文的核心是情绪交付。读者在短时间内完成一次情绪体验；扫榜要提取高频情绪、触发场景、释放节奏和传播点，而不是只记录题材名。
原则 2：短篇的生命力在传播
短篇不像长篇靠追读赚钱。短篇靠的是单篇完读率和传播（分享、收藏、点赞）。完读率高 = 情绪拉扯到位；传播率高 = 有共鸣或反转让人想转发。
原则 3：短篇风口来得快去得快
短篇题材信号可能在数周内失效。输出风口候选时必须给出有效期、饱和风险和下次复扫时间；未复扫前不得当作长期趋势。
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？」
关键判断：
- 用户已有方向 → 针对该方向做深度扫榜
- 用户没有方向 → 做全榜概览 + 找趋势
- 用户想跨平台比较 → 做平台对比分析
Phase 1.5：确定数据来源
扫榜需要真实数据支撑。 根据当前环境选择数据来源：
| 优先级 | 模式 | 说明 | 何时用 |
|---|---|---|---|
| 1 | browser-cdp 采集 | 直接抓取平台页面，产出结构化文件 | 有 Chrome 环境时（优先） |
| 2 | 用户提供 | 用户粘贴榜单截图/文字/链接 | 用户已有数据时 |
| 3 | 内置知识 | 基于知识库中的趋势数据和方法论做分析 | 无法联网、用户无数据时 |
browser-cdp 采集模式
使用 /browser-cdp 启动 Chrome，直接抓取平台页面的结构化数据。
点众采集目标：
| 页面 | URL | 核心字段 |
|---|---|---|
| 男频短篇 | ishugui.com/browse | 书名·作者·标签·状态·字数·评分·最新章节 |
| 女频短篇 | ishugui.com/browse/on3 | 书名·作者·标签·状态·字数·评分·最新章节 |
黑岩采集目标：
| 页面 | URL | 核心字段 |
|---|---|---|
| 书库列表 | manage.zhangwenpindu.cn/books/booklist | 书名·作者·字数·分类·类型·价格·创建/更新时间·标签（详情模式） |
黑岩需要登录！ 必须先在 Chrome 中手动登录
manage.zhangwenpindu.cn，脚本才能从 Cookie 中提取 Bearer token 调用后端 API。未登录会报错提示。黑岩采集失败时标记为 SKIP，继续其他平台采集，不中断整个 Phase 1。
- 黑岩专用：
--pages N（每页 20 条）、--detail（逐本详情，含标签/简介，速度较慢）、--channel male/female - 点众专用：
--channel male/female/all
文件命名：{平台}{类型}_{YYYYMMDD}.md，例：点众男频短篇_20260501.md
用户提供操作指引：
- 请用户截图或复制粘贴榜单内容
- 如果用户提供链接，用 WebFetch 抓取页面内容
- 如果用户只提供故事名列表，直接进入分析
内置知识操作指引：
- 加载
references/real-market-data.md（跨平台写作差异对照） - 明确标注：「以下分析基于历史趋势数据；未完成实时榜单校验前只能作为候选假设。」并列出需要复扫的平台页面。
浏览器操控（高级模式）：
- 如果可用 agent-browser CLI，通过 CDP 连接 Chrome 获取平台数据
- 示例：
agent-browser --cdp 9222 open "https://www.ishugui.com/browse" - 可复用用户已登录的 Chrome session，获取完整榜单数据
- 适用于需要登录才能看到的数据（知乎个人中心、番茄书架等）
Phase 2：数据分析
知乎盐言故事分析维度
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 224 lines · 65 tokens per session scan A ddf7239daf19
story-short-scan is a skill published in the GitHub repository uu201/character-arc (560 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session and 2,732 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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