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 humangit 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/human)<a href="https://agentmods.dev/skills/tance-mang/chinese-webnovel-skills/human"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/human/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/human"><img src="https://agentmods.dev/badge/skills/tance-mang/chinese-webnovel-skills/human.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 | $0.00117 | $0.00958 |
| Opus 5 | $0.00059 | $0.00479 |
| Sonnet 5 | $0.00023 | $0.00192 |
| Haiku 4.5 | $0.00012 | $0.00096 |
Grade A, and why
human 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
人味 / 失控感（human）
最高级的一层去 AI 味。"AI 味"的本质是缺少人类失控感——AI 写得像说明书（都解释、都合理、都闭环、都中立），人写得像情绪记录（有失控、有偏执、有省略、有偏心）。
何时用
- 稿子"读着像 AI / 像说明书 / 太顺太工整 / 情绪太平均 / 人物太正常 / 没人味"
- 表面修辞都改干净了（
deslop过了），但还是"差点意思" - 想让文字更像真人写的——不是改字，是加失控感
和
deslop的分工：deslop 治表面（修辞/标点/符号/重复/极端词）；本技能治深层（情绪/冲突/人物/不闭环/私货）。两个一起用最彻底。
工作流
A. 诊断（按 5 种感受找"太 AI"处）
扫稿子，指到段标出（调 references/human-texture.md）：
- 情绪太平均：都在合理反应，没有真正失控/极端/偏执的爆点。
- 冲突太干净：误会→解释→解决，缺"越滚越脏"的链条。
- 句子太顺：没有长短变化、断句、停顿、不完整表达 → 句长不均+停顿标点，详见
references/sentence-rhythm.md。 - 人物太正常：动机合理但不极端，没有"明知错还做"的不理性。
- 太中立：没有偏见、情绪判断、私货感。
B. 注入人味（3 个手法，关键处加）
- 非理性行为：让角色做"逻辑上不该、情绪上必须"的事（明知会输还赌、当场翻脸不解释、突然极端选择）。
- 情绪不完整表达：留没说出口的缺口（"他没说完那句话。""她突然不想解释了。""那一刻他有点后悔，但没停。"）。
- 逻辑不完全闭环：次要的事不解释尽、次要的关系不收干净。 给"原句/原段 → 改后"对照，说明加了哪种。
原则
- 点睛不发疯：关键处放 1–2 个失控点，不是通篇不理性。
- 不牺牲爽和钩：番茄仍要节奏；失控感是让爽更可信、人物更立得住。
- 不闭环 ≠ 烂尾：主线大坑必须回收，留白只留情绪性/关系性的小东西。
- 自检一句话：这段像说明书，还是像一个人在记录情绪？
反例对照
- ❌（太干净）“她误会了他，他解释清楚，两人和好。”
- ✅（越滚越脏）“她没等他说完就挂了电话。他想再打，手指悬在屏幕上，又放下了——算了，解释什么呢。第二天，闺蜜把那张照片发到了群里。”
下一步
加完人味 → deslop 收表面、review 复诊、emotion 强化关键情绪。
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 · 45 lines · 117 tokens per session scan A 73b8718af203
human is a skill published in the GitHub repository tance-mang/chinese-webnovel-skills (58 stars, last pushed 3mo ago), licensed MIT. It adds 117 tokens to every session and 958 once invoked, about $0.0006 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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