oh-story-claudecode is a skill package for planning, analyzing, and writing Chinese web fiction, covering both short and long novels. It is intended for writers using Claude Code, Codex, OpenClaw, and other supported AI-agent environments, with workflows for market research, story breakdowns, drafting, editing, and cover creation. The catalogue entries are the package's skills, commands, agents, and plugin.
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-claudecode --skill story-short-scangit clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecodeWrote 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-claudecode/story-short-scan)<a href="https://agentmods.dev/skills/zenstory-ai/oh-story-claudecode/story-short-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-claudecode/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/zenstory-ai/oh-story-claudecode/story-short-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-claudecode/story-short-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- 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 | $0.02654 |
| Opus 5.5 | $0.00026 | $0.01062 |
| Sonnet 5.5 | $0.00013 | $0.00531 |
| Haiku 4.5 | $0.00006 | $0.00265 |
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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- story-short-scan — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 166 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
基于真实榜单样本分析短篇市场，给作者可写的情绪方向、题材候选和验证办法。
核心哲学
原则 1：短篇市场是情绪市场
扫榜从题材和简介中判断读者读完的感受、触发场景与情绪爆发点，说明这些内容如何吸引读者。仅凭题材名无法判断具体情绪体验。
原则 2：热度只按各平台自己的口径比
榜单给的收藏、赞同、在读、评分各有口径，只在同一口径内比较。排名和互动量只说明样本受到的关注，不能据此断定故事质量或情绪拉扯效果。
原则 3：短篇风口来得快去得快
报告写明样本日期、覆盖范围、结论可信度和复扫日期。题材信号可能在数周内失效，过期后只作候选参考。
扫榜流程
Phase 1：确认平台和方向
用户已给出平台或方向时直接采用，只问缺项：「想看哪个平台、男频还是女频、哪类短篇？点众可直接采集；黑岩要有黑岩后台账号、先登录；知乎盐言、番茄和七猫短篇请发榜单截图、文字或链接。手里有编辑的征稿要求也可以一起发来。」
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
| 优先级 | 模式 | 说明 | 何时用 |
|---|---|---|---|
| 1 | 脚本采集 | 点众、黑岩：抓取平台页面，产出结构化文件 | 有 Chrome 环境时（优先） |
| 2 | 作者提供 | 没有脚本的平台，或作者已有榜单 | 知乎盐言/番茄短篇/七猫短篇等 |
| 3 | 内置知识 | 用历史资料提出待验证的选题 | 无法联网、作者也没有数据时 |
命令中的 scripts/ 相对本 skill 根目录。
- 只读所选平台那一份：点众 / 黑岩 / 没有脚本的平台。其中有网址、命令、字段、故障排查、平台分析维度和作者榜单的整理格式。
- 每次扫榜新建输出目录
扫榜/{YYYYMMDD}/（同日再扫加-2）存本次榜单，不往旧目录追加（聚合会混进旧榜）。脚本自动命名文件，作者榜单按平台参考命名；某平台失败就跳过。对比时读上个日期目录的扫榜聚合.md。 - 聚合：
node scripts/aggregate-rank.js {输出目录} --out {输出目录}/扫榜聚合.md --sparse 10 --scale short。主会话只读这份聚合，需要原始简介与人设信息时再抽样：node scripts/aggregate-rank.js {输出目录} --sample {题材/标签/书名词} --n 5。 - 看聚合的「采集情况」：标了问题（书名没解出来、没采到、详情没取到）的榜单按平台参考排查重采；重采不了就在报告里说明结论不含它。
- 作者发来征稿要求：原文存进输出目录的
征稿要求.md，题材、字数、截止日期当硬条件。
内置知识： 跳过聚合，加载 references/real-market-data.md，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。
Phase 3：数据分析
有真实样本时，以聚合结果和平台参考的「分析维度」为准。趋势需对比同口径的多期样本；仅用内置知识时只给待验证候选，不填写当前数量、占比或涨跌。
- 情绪排行：按本节末的情绪表把题材、标签归入六种写作情绪，按样本数量比较。每本书根据简介判断读者读完的感受，只归一类；标签只是线索，无法判断的计「待定」。悬疑题材按简介落点分：最后揭开真相的归反转震撼，留下寒意的归细思极恐
- 题材热点：聚合的题材表和标签热词里反复出现的设定、场景
- 篇幅分布：聚合的字数分布与各题材字数中位
- 简介与书名写法：抽样简介怎么前置冲突、留悬念，书名常见词与代表作标题；可对照 real-market-data 的历史写法
- 结尾类型：HE（好结局）/BE（坏结局）/开放式，只在作者提供的内容看得出结局时统计
- 人设模型：抽样简介里反复出现的主角类型
What ships with it
9 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/manual-rank-input.md 1.9 KB
- references/platform-dianzhong.md 1.2 KB
- references/platform-heiyan.md 1.7 KB
- references/real-market-data.md 3.6 KB
- references/topic-match.md 2.7 KB
- scripts/aggregate-rank.js 31 KB runs code
- scripts/cdp-utils.js 8.4 KB runs code
- scripts/dz-browse-scraper.js 8.4 KB runs code
- scripts/heiyan-booklist-scraper.js 13 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.
- 4d ago Changed 9b0e18ed6bf2
- 10d ago Changed · -10 lines 00192d708a9f
- 12d ago Changed · -7 lines 21868d466a09
- 1mo ago Changed · -34 lines 0c8314c6c62b
- 1mo ago Changed · +4 lines 10a656d50c02
- 1mo ago First seen · 213 lines · 65 tokens per session scan A def39be0868b
story-short-scan is a skill published in the GitHub repository zenstory-ai/oh-story-claudecode (8,063 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 2,654 once invoked, about $0.0003 per session on Opus 5.5. 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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