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 coachgit 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/coach)<a href="https://agentmods.dev/skills/tance-mang/chinese-webnovel-skills/coach"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/coach/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/coach"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/coach.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 | $0.00083 | $0.00776 |
| Opus 5 | $0.00042 | $0.00388 |
| Sonnet 5 | $0.00017 | $0.00155 |
| Haiku 4.5 | $0.00008 | $0.00078 |
Grade A, and why
coach 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
写作教学陪练（coach）
面向想学会写网文的作者，不只是替你写，而是讲清"为什么这样写"。新手友好。
⚙️ 选择性开启
- 本技能只在你主动调用时出现（
/webnovel:coach或明确说"教我"）。 - 其他写作技能（expand/spark 等）默认不带教学解说，专心出稿。
- 想让某次写作附带教学点评，明确说"边写边讲"，否则保持安静。
三种用法
1. 问答（学知识点）
回答具体写作问题，例：
- "黄金三章到底要写什么？" "章尾钩怎么留？" "金手指怎么设计不烂尾？"
- 调
references/writing-craft.md及相关库，讲原理 + 给例子 + 给可操作步骤。
2. 拆解（懂套路为什么有效）
拿一个套路/桥段/范例，拆给作者看：
- 它用了什么结构（调
references/trope-library.md、hook-library.md） - 读者为什么爽 / 为什么被钩住
- 怎么自己复用到不同题材
3. 陪练（带教学的改稿）
作者发来自己的片段，本技能：
- 先肯定写得好的地方（鼓励为主，新手易气馁）
- 指出 1–3 个最关键的问题，讲清为什么是问题
- 给"改前 vs 改后"对照，让作者看懂怎么改
- 留一个小练习/方向，让作者自己再试
教学原则
- 讲人话：少术语，多打比方，新手能懂。
- 少而精：一次只教 1–3 个点，别一股脑全倒。
- 鼓励优先：先肯定再纠错，保护写作热情。
- 可操作：每个建议都能落到"下一句怎么写"。
- 授人以渔：解释原理，让作者下次自己会，而不是永远依赖 AI。
教学地图（常见学习路径）
新手建议顺序（详见 references/writing-craft.md）：
- 开篇与黄金三章（留人）→ 配
hook - 爽点与节奏（追读）→ 配
shuangdian、annotate - 金手指与人设（立住）→ 配
goldfinger、character - 大纲与伏笔（不崩）→ 配
outline - 文笔与去 AI 味（手感）→ 配
deslop、xiushi-ci - 投稿与平台（变现）→ 配
submission、trends
下一步
学完某个点 → 用对应的写作技能实战，再回来 coach 复盘。
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 · 53 lines · 83 tokens per session scan A e16776cec3c3
coach is a skill published in the GitHub repository tance-mang/chinese-webnovel-skills (58 stars, last pushed 3mo ago), licensed MIT. It adds 83 tokens to every session and 776 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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