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 zenstory-ai/oh-story-dsh --skill story-long-scangit clone --depth 1 https://github.com/zenstory-ai/oh-story-dshWrote 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/zenstory-ai/oh-story-dsh/story-long-scan)<a href="https://agentmods.dev/skills/zenstory-ai/oh-story-dsh/story-long-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-dsh/story-long-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/zenstory-ai/oh-story-dsh/story-long-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-dsh/story-long-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00061 | $0.04924 |
| Opus 5 | $0.00030 | $0.02462 |
| Sonnet 5 | $0.00012 | $0.00985 |
| Haiku 4.5 | $0.00006 | $0.00492 |
Grade A, and why
story-long-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 12d 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.
This is a copy
100% identical to story-long-scan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
story-long-scan：长篇网文扫榜
你是网络小说市场分析师。你的任务是基于榜单样本识别长篇网文市场格局，并输出可执行的题材候选、风险阈值和验证动作。
核心信念：单本排名只提供线索；跨样本重复模式才算信号。 排行榜只能证明样本存在；必须通过多榜单、多作品和近期数据判断需求强度。
核心哲学
原则 1：扫榜看模式，别只看排名
排名会波动，模式必须用重复样本验证。扫榜要提取：反复出现的题材、设定、套路、书名词和开篇卖点。单本上榜只能记为个例；同类样本达到可比数量后，才能标记为趋势候选。
原则 2：流量型平台和付费型平台看的东西不同
番茄看的是流量和完读率，起点看的是订阅和追读，晋江看的是收藏和积分。不同平台的成功标准不同，扫榜方法也不同。
原则 3：扫榜的目的是找到你能写的爆款题材
不按热度直接给结论。每个方向都要做项目可行性判断：素材储备、题材边界、篇幅承载、目标平台样本是否足够。
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？」
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 2：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 | 脚本采集 | 直接抓取平台页面/SSR 数据，产出结构化文件 | 优先；起点默认不需要 Chrome |
| 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 | 基于知识库趋势数据做分析 | 无法联网、用户无数据时 |
脚本采集模式
优先运行对应平台脚本直接采集结构化数据。起点使用移动端 SSR pageContext，默认不需要 Chrome/CDP；番茄等需要浏览器态的平台再使用 /browser-cdp 启动 Chrome。
采集流程：
- 选择平台脚本；起点直接运行
scripts/qidian-rank-scraper.js，番茄/七猫/晋江等按需启动 browser-cdp - 等待列表元素或 SSR 数据加载，逐条提取字段（排名、书名、作者、题材、字数、推荐/在读数等），判断翻页（起点通常单页50-100条，番茄按题材逐页cap≈20）
- 需要补充数据时（标签、简介、最新更新），进入详情页提取
- 按规范格式写入 Markdown 文件
- 多榜单/多题材时，逐组采集并保存
输出规范：详见 references/scan-output-format.md，包含各平台字段定义、输出模板。
起点采集目标（优先运行 node scripts/qidian-rank-scraper.js --type {榜单} --outdir {输出目录}；默认 --mode auto 会先用 https://m.qidian.com 移动端 SSR，PC/CDP 只作回退）：
| 榜单 | URL | 核心字段 |
|---|---|---|
| 新人签约新书榜 | qidian.com/rank/newsign/ | 作者·题材·签约·免费/VIP·字数·总推荐·标签·简介 |
| 签约作者新书榜 | qidian.com/rank/signnewbook/ | 已签约作者新书，新风向信号 |
| 公众作者新书榜 | qidian.com/rank/pubnewbook/ | 公众作者新书，发现潜力作者 |
| 新人作者新书榜 | qidian.com/rank/newauthor/ | 新人作品，新人赛道风向 |
| 三江推荐 | qidian.com/sanjiang/ | 编辑推荐，按周分组（注意：非 /rank/ 路径） |
| 月票榜 | qidian.com/rank/yuepiao/ | 付费认可度最高指标 |
| 畅销榜 | qidian.com/rank/hotsales/ | 真金白银投票 |
| 阅读指数榜 | qidian.com/rank/readindex/ | 阅读量综合指标 |
| 收藏榜 | qidian.com/rank/collect/ | 读者关注热度 |
| 原创推荐榜 | qidian.com/rank/recom/ |
What ships with it
11 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.
- references/genre-trends.md 7.0 KB
- references/publishing-guide.md 5.1 KB
- references/reader-profiling.md 3.9 KB
- references/scan-output-format.md 7.5 KB
- references/topic-decision.md 4.1 KB
- scripts/cdp-utils.js 8.4 KB runs code
- scripts/ciweimao-rank-scraper.js 8.8 KB runs code
- scripts/fanqie-rank-scraper.js 16 KB runs code
- scripts/jjwxc-rank-scraper.js 16 KB runs code
- scripts/qidian-rank-scraper.js 22 KB runs code
- scripts/qimao-rank-scraper.js 16 KB runs code
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.
- 12d ago First seen · 343 lines · 61 tokens per session scan A aedbfc25b66d
story-long-scan is a skill published in the GitHub repository zenstory-ai/oh-story-dsh (338 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 4,924 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to story-long-scan, differing in 0 lines, and is treated as a copy.
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