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-long-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-long-scan)<a href="https://agentmods.dev/skills/zenstory-ai/oh-story-claudecode/story-long-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-claudecode/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-claudecode/story-long-scan"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-claudecode/story-long-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 | $0.00061 | $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 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- story-long-scan — 100% identical, 0 lines differ
- story-long-scan — 92% identical, 73 lines differ
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.
- 13d 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-claudecode (6,780 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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novel-sync
A Chinese-language workflow for updating a novel's continuity notes after a chapter is written or changed. It records events, character changes, unresolved clues, and notable lines in the project's reference files.
novel-chapter-write
A long-form novel writing workflow that turns an approved chapter plan into chapter prose. It supports drafting, targeted revision, and final approval while keeping style and story details consistent across chapters.
bestseller-novel-outline
A planning workflow for designing a very long commercial novel before chapters are written. It creates the world, characters, overall plot, volume outlines, planted clues, and chapter paths for later writing tools.
outline-refinement
A planning tool for long-form novels that breaks each chapter into a detailed sequence of scenes, information, required events, forbidden events, clues, and an ending hook.