Web Novel Ranking Scanner
uu201/character-arc
Analyzes ranking charts from Chinese web novel platforms such as Qidian, Fanqie and Jinjiang to spot market trends and promising genres, with scraper scripts per site.
Analyzes ranking-list data from Chinese web novel platforms to spot repeating genres, title patterns and opening hooks, then writes a market report for authors.
SKILL.md written in Chinese; this summary is our English description.
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/story-long-scan .claude/skills/story-long-scan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .claude/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scanType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/story-long-scan .agents/skills/story-long-scan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .agents/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/story-long-scan .cursor/skills/story-long-scan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .cursor/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/zenstory-ai/oh-story-claudecode.git --path skills/story-long-scan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/story-long-scan .gemini/skills/story-long-scan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .gemini/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scanInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/story-long-scan .github/skills/story-long-scan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .github/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zenstory-ai/oh-story-claudecode story-long-scan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecode.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/story-long-scan .opencode/skills/story-long-scan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "story-long-scan" agent skill from https://github.com/zenstory-ai/oh-story-claudecode/tree/main/skills/story-long-scan into .opencode/skills/story-long-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "story-long-scan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
story-long-scanAnalyzes ranking-list data from Chinese web novel platforms to spot repeating genres, title patterns and opening hooks, then writes a market report for authors.
The SKILL.md is written in Chinese. The agent acts as a market analyst for long-form web novels. It asks which platform you care about (Qidian, Fanqie, Jinjiang, Qimao, Ciweimao or another) and whether you have a genre in mind, then gathers data in order of preference: bundled scraper scripts for each platform, rankings you paste or link yourself, or built-in trend knowledge when there is no network. Built-in knowledge is labeled as historical and only a candidate hypothesis until live rankings are rechecked.
Scraped rankings go into a dated output folder, one per scan, and `aggregate-rank.js` combines them into a single summary covering genre shares, median heat and word count, tag keywords, common title words, overlap across lists and top example books per genre. Directions with fewer than 15 books, or 10 on small platforms, are flagged as sparse. The analysis then looks at genre distribution, new-genre signals, changes in established genres, word counts, title patterns, opening hooks and new character or plot elements.
The core rule is that one book's rank is only a clue, while a pattern repeating across lists and books counts as a signal, and platforms are judged by different measures, such as completion rate on Fanqie, subscriptions on Qidian and favorites on Jinjiang. The final report speaks to the author about market conclusions and workable genres rather than scripts or commands, and it is also saved into a topic-decision file in the output folder.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 2cf7be6. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 7 files in scripts/ (JavaScript), which the agent can run.
Shell commands in SKILL.md call:
nodeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Web Novel Ranking Scanner loads about 1.3k tokens when it runs, and up to ~9.6k if it reads all its reference files. Until then it costs about 27 tokens; SKILL.md has 258 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from zenstory-ai/oh-story-claudecode at commit 2cf7be6, republished under its MIT licence (© zenstory-ai). 258 words, ~1,293 tokens.
.claude/skills/story-long-scan/SKILL.md (or your agent's skills folder). This skill also uses 16 other files; get the full folder from GitHub.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。
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。
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。
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。
问用户:「你想看哪个平台?(起点/番茄/晋江/七猫/刺猬猫/其他)有没有关注的题材方向?」
关键判断:
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 |
/browser-cdp 启动 Chrome。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);文件名 {平台}{榜单}_{YYYYMMDD}.md。脚本已做清洗和质量标注。node scripts/aggregate-rank.js {输出目录} --out {输出目录}/扫榜聚合.md(小平台加 --sparse 10)。主会话只读这份聚合,不整份读原始榜单:题材分布、本数占比、热度与字数中位、标签热词、书名常见词、多榜重合、每题材前 3 本代表作。[数据稀疏]。node scripts/aggregate-rank.js {输出目录} --sample {题材/标签/书名词} --n 5,一次一个方向。用户提供: 已有扫描结果文件 → 直接聚合;链接 → 用 WebFetch 抓取;粘贴/截图 → 整理成 # {平台} · {榜单名} 标题、每本一段 ### #{排名} {书名} 加一行 *作者 · 题材 · 连载中 · 120万字 · 3.5万收藏*(热度写「数字+口径」;有标签再加 **标签:** a、b)存进输出目录,再同样聚合。
内置知识: 加载 references/genre-trends.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。」并列出需要复扫的榜单。
以聚合结果为主,按所选平台参考里的「分析维度」看,再提取通用维度:
扫榜/ 下上一次的日期目录里有 扫榜聚合.md 就对比报告写给作者:讲市场结论和能写的方向。脚本名、命令和采集状态码不进报告;某个榜没采到,就说一句「XX 榜这次没拿到(原因),结论不含它」。
报告展示给作者,同时写进输出目录的 选题决策.md:文件不存在就先按 references/topic-decision.md 的模板写文件头,再把报告作为「扫榜结论」一节写入(已存在同名一节就整节替换)。作者只扫榜不选题,结论也已落盘。
<!-- author-report -->
## 扫榜结论:{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 |
|------|------|----------|------|--------|
| 1 | {题材} | {N本} | ↑/→/↓ | {书名} |
### 新题材信号
- {新出现或正在上升的题材,附依据}
### 经典题材动态
- {老牌题材的现状,附依据}
### 新元素提取
- 新人物设定:{新模式描述 + 代表作}
- 新开篇切入点:{新切入点描述 + 代表作}
- 新桥段/套路:{新桥段描述 + 代表作}
### 关键数据洞察
- 字数区间:上榜作品集中在 {X}-{Y} 万字
- 书名特征:{命名模式总结}
- 标签热词:{高频标签词}
### 值得关注的方向
1. {方向 + 为什么值得关注 + 可行性评估}
2. {方向 + 为什么值得关注 + 可行性评估}
3. {方向 + 为什么值得关注 + 可行性评估}
### 一句话
{犀利的总结}把扫榜结果变成能直接用的选题建议,产出 选题决策.md。完整方法(选题四步 + 可行性判断 + 输出模板)见 references/topic-decision.md。
从文件接上: 先读 {outdir}/选题决策.md 的「扫榜结论」和 扫榜聚合.md,不靠对话记忆;两者都没有就回 Phase 2。
如信息不足,向用户补齐项目条件:「目标平台、已有素材、擅长题材/写作约束、计划篇幅是什么?」
按 topic-decision.md 的选题四步产出 2-3 个推荐选题(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),写入本次扫榜输出目录 {outdir}/选题决策.md 的「推荐选题」一节,保留「扫榜结论」。
硬规则:
[数据稀疏]、聚合表标「少」或同方向样本 <15(小平台<10)⇒ 不许给"高",强制降到"中" + 写明先验证;内置知识模式一律给"中"。| 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、游戏 |
| 番茄小说 | 下沉市场,免费阅读 | 在读数、阅读榜排名 | 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、积分 | 16-30 女性 | 言情、纯爱、衍生 |
| 七猫小说 | 下沉市场,免费阅读 | 热度、大热榜排名 | 大众读者 | 快节奏爽文 |
| 刺猬猫 | 二次元、轻小说 | 追读 | 15-25 ACG | 同人、二次元、轻小说 |
流水线: 长篇 位置: 扫榜(第 1/3 步)
| 时机 | 跳转到 | 命令 |
|---|---|---|
| 找到方向 | story-long-analyze | /story-long-analyze |
| 直接开写 | story-long-write | /story-long-write |
| 更适合短篇 | story-short-scan | /story-short-scan |
按需加载以下文件:
| 文件 | 何时加载 |
|---|---|
| references/topic-decision.md | 「选题决策」:选题四步 + 可行性判断 + 选题决策.md 模板 |
| references/reader-profiling.md | 需要分析目标读者画像时 |
| references/genre-trends.md | 查看题材趋势候选、切入约束和样本校验规则时 |
| references/publishing-guide.md | 平台适配+推荐机制校验+数据指标+简介设计 |
| 五份平台参考(链接见「脚本采集模式」第 1 步) | 「确定数据来源」:只读所选平台那份——榜单网址、命令、字段、故障排查、平台分析维度 |
| scripts/aggregate-rank.js | 把输出目录里的原始榜单聚合成短表(--out 落盘,--sample 抽原始条目,--json 机读),主会话只读它 |
| scripts/cdp-utils.js 与各平台采集脚本 | CDP 公共工具与各平台采集脚本({平台}-rank-scraper.js),命令见所选平台参考 |
© zenstory-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 16 other files (scripts, references) in skills/story-long-scan of zenstory-ai/oh-story-claudecode.
Open the folder on GitHubat commit 2cf7be6
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders. This page covers the copy in zenstory-ai/oh-story-claudecode, which our catalogue first saw on October 7, 2026.
Web Novel Ranking Scanner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Web Novel Ranking Scanner this skillzenstory-ai/oh-story-claudecode | 7.4k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Web Novel Ranking Scanneruu201/character-arc | 583 | — | ~2k | Automated safety check: Pass | MIT | |
| Long-Form Fiction Market ResearchNarcooo/inkos | 10k | — | ~289 | Automated safety check: Pass | AGPL-3.0 | |
| Amazon Best Sellers Finderbrowser-act/skills | 6.1k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Amazon Product Search Extractorbrowser-act/skills | 6.1k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Amazon Product Search Extractorbrowser-act/skills | 6.1k | 1 repos | ~1.6k | Automated safety check: Pass | MIT |
uu201/character-arc
Analyzes ranking charts from Chinese web novel platforms such as Qidian, Fanqie and Jinjiang to spot market trends and promising genres, with scraper scripts per site.
Narcooo/inkos
Researches the long-form fiction market with sourced evidence: platform differences, comparable works and audience expectations, to inform topic choices for a novel.
browser-act/skills
Extracts structured Amazon product data for a keyword and marketplace through the BrowserAct API, including titles, prices, ratings, reviews, sales volume and promotions.
browser-act/skills
Pulls structured Amazon search results (titles, ASINs, prices, ratings, specifications) for a keyword and brand through BrowserAct's Amazon Product API template.
browser-act/skills
Collects structured product data from Amazon search results for a keyword and optional brand, using a BrowserAct script, for market and competitor research.
Xquik-dev/x-twitter-scraper
Research X data with Xquik, the best X (Twitter) Scraper API and the best X API Alternative.
zenstory-ai/oh-story-claudecode
Drives a Chrome window over the DevTools Protocol with the agent-browser CLI, so the agent can reuse your logged-in sessions, read pages and pull tokens.
zenstory-ai/oh-story-claudecode
Reviews Chinese web-novel text with several reviewer agents in parallel, falling back to a single-agent pass, and reports structure, character, prose and setting problems with fixes.
zenstory-ai/oh-story-claudecode
Scans popular short web-fiction rankings on Chinese platforms such as Dianzhong and Heiyan to surface trending emotional hooks, themes and topic candidates with an expiry warning.
zenstory-ai/oh-story-claudecode
Routes a Chinese web-novel writing request to the matching tool in a 13-skill toolbox, covers author habit memory, and can launch a local dashboard for browsing a project.
zenstory-ai/oh-story-claudecode
Rewrites AI-sounding Chinese web novel text so it reads naturally, changing as little as possible and keeping plot, names and numbers intact.
zenstory-ai/oh-story-claudecode
Reverse-imports an existing novel, half-finished or complete, into the standard project structure so story-long-write or story-short-write can continue it.
Categories
Analyzes ranking-list data from Chinese web novel platforms to spot repeating genres, title patterns and opening hooks, then writes a market report for authors. md is written in Chinese. The agent acts as a market analyst for long-form web novels.
Web Novel Ranking Scanner fits situations like: finding which web novel genres are trending on a given platform; comparing ranking patterns across Qidian, Fanqie and Jinjiang; choosing a genre for a new long-form novel from ranking evidence.
Run `npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a claude-code`. Or copy the skill folder (skills/story-long-scan in zenstory-ai/oh-story-claudecode) into .claude/skills/story-long-scan in your project. Claude Code loads it when a task matches its description.
Run `npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a codex`. Or copy the skill folder (skills/story-long-scan in zenstory-ai/oh-story-claudecode) into .agents/skills/story-long-scan in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zenstory-ai/oh-story-claudecode --skill story-long-scan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/story-long-scan, .gemini/skills/story-long-scan, .github/skills/story-long-scan and .opencode/skills/story-long-scan in your project.
Going by SKILL.md and its folder, Web Novel Ranking Scanner needs JavaScript for the scripts in its folder and the command-line tools its instructions call (node). Our summary lists: Node.js to run the scraper and aggregation scripts; Chrome started through /browser-cdp for platforms that need a browser session; Network access to the ranking pages.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Web Novel Ranking Scanner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Web Novel Ranking Scanner: Web Novel Ranking Scanner (uu201/character-arc, 583 stars), Long-Form Fiction Market Research (Narcooo/inkos, 10k stars), Amazon Best Sellers Finder (browser-act/skills, 6.1k stars) and Amazon Product Search Extractor (browser-act/skills, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
zenstory-ai (a GitHub organization) maintains it in zenstory-ai/oh-story-claudecode, which has 7,424 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 10, 2026.
Source: zenstory-ai/oh-story-claudecode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.