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 tance-mang/chinese-webnovel-skills --skill ideagit clone --depth 1 https://github.com/tance-mang/chinese-webnovel-skillsWrote 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/tance-mang/chinese-webnovel-skills/idea)<a href="https://agentmods.dev/skills/tance-mang/chinese-webnovel-skills/idea"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/idea/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/tance-mang/chinese-webnovel-skills/idea"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/idea.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 | $0.00074 | $0.00970 |
| Opus 5 | $0.00037 | $0.00485 |
| Sonnet 5 | $0.00015 | $0.00194 |
| Haiku 4.5 | $0.00007 | $0.00097 |
Grade A, and why
idea 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.
What it actually says
选题立意（idea）
帮作者把"想写小说"变成"一个能开写、有市场的具体选题"。
何时用
- 用户说"我想写小说但不知道写什么"
- 用户有个模糊想法，需要打磨成爆款选题
- 用户要一句话卖点 / 标签 / 黄金三章方案
- 开新书前的立项
工作流
第 1 步：定位四连问
先明确（缺哪个就问用户，或给推荐）：
- 频道：男频 / 女频？→ 参考
references/channel-guide.md - 平台：番茄 / 晋江 / 起点 / UC / 知乎盐选 / Webnovel？→ 参考
references/platform-profiles.md - 题材偏好：用户想写什么大类 → 从
references/genre-library.md九大板块选型（悬疑/心理/都市/系统流/玄幻仙侠/女频/历史古代架空/灵异/年代乡土/小众） - 篇幅：短篇 / 中篇 / 长篇？→ 定签约门槛和目标总字数（参考
references/length-standards.md，如番茄短故事冲爆款瞄 1万–1.8万、长篇先冲 ≥8万进分发）
可带参数直接定位，如
/webnovel:idea 番茄 男频 系统都市、/webnovel:idea 晋江 女频 古言宅斗。
第 2 步：生成 3 个差异化选题
每个选题给出：
- 一句话核心创意（卖点钩子，能当宣传语）
- 频道 + 类型 + 平台适配
- 金手指/核心设定（参考
references/goldfinger-types.md） - 核心爽点链（参考
references/trope-library.md） - 目标读者画像
- 同质化风险评估（这个点子市场上多不多，怎么差异化）
第 3 步：黄金三章策略
为用户选中的选题设计：
- 第 1 章：开篇钩（3 句立危机/反差）+ 金手指上线时机 → 调
references/hook-library.md - 第 2 章：扩大冲突 + 第一次小爽点
- 第 3 章：第一个小高潮 + 主线悬念落地（决定收藏率）
第 4 步：输出"开书卡"
【书名候选】3 个
【一句话卖点】
【频道/类型/平台/篇幅】（篇幅给档位+目标总字数）
【金手指】
【主角设定】一句话
【核心矛盾】
【爽点链】打脸X → 升级Y → 翻盘Z
【黄金三章】逐章一句话
【差异化】与市面同类的区别
原则
- 先有"爽点和卖点"，再有"故事"——网文是商品，立意先想清楚卖给谁、爽在哪。
- 不要泛泛而谈，每个选题都要具体到能直接写第一章。
- 主动指出同质化风险，给差异化建议。
起名提示
开书卡里的【书名候选】必须带题材关键词+爽点+钩子，避免抽象文艺/烂大街/AI 味（调 references/title-library.md）。要专门打磨书名 → 用 title 技能。
下一步
选题定了 → 用 title 起名，outline 出大纲，hook 打磨开篇，goldfinger 细化金手指。
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 · 65 lines · 74 tokens per session scan A dab5a2a36820
idea is a skill published in the GitHub repository tance-mang/chinese-webnovel-skills (58 stars, last pushed 3mo ago), licensed MIT. It adds 74 tokens to every session and 970 once invoked, about $0.0004 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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