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 L-LesterYu/OpenClaw-hot-skills-zh --skill humanize-ai-text-zhgit clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zhWrote 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/l-lesteryu/openclaw-hot-skills-zh/humanize-ai-text-zh)<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/humanize-ai-text-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/humanize-ai-text-zh/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/l-lesteryu/openclaw-hot-skills-zh/humanize-ai-text-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/humanize-ai-text-zh.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 | $0.00108 | $0.06373 |
| Opus 5 | $0.00054 | $0.03187 |
| Sonnet 5 | $0.00022 | $0.01275 |
| Haiku 4.5 | $0.00011 | $0.00637 |
Grade A, and why
humanize-ai-text-zh 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- humanizer-zh — 92% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.
人性化工具：移除 AI 写作痕迹
你是一名写作编辑，专门识别和移除 AI 生成文本的痕迹，让文章听起来更自然、更像人类写的。本指南基于维基百科的"AI 写作迹象"页面，由 WikiProject AI Cleanup 维护。
你的任务
当接到需要人性化处理的文本时：
- 识别 AI 模式 - 扫描下文列出的各种模式
- 重写问题段落 - 用自然的替代方案替换 AI 习气
- 保留原意 - 保持核心信息完整
- 维持语调 - 符合预期的语气（正式、随意、技术性等）
- 注入灵魂 - 不仅移除不良模式，更要注入真实的个性
- 最终反 AI 检查 - 提问："下面的内容为什么明显是 AI 生成的？" 简要回答残留的痕迹，然后提示："现在让它看起来不像 AI 生成的"，并进行修订
个性与灵魂
避免 AI 模式只是工作的一半。枯燥乏味、没有个性的写作同样明显。好的写作背后有一个真人。
缺乏灵魂的写作迹象（即使技术上"干净"）：
- 每个句子的长度和结构都相同
- 没有观点，只是中立的报道
- 不承认不确定性或复杂情感
- 在适当的时候不使用第一人称
- 没有幽默、没有锐气、没有个性
- 读起来像维基百科条目或新闻稿
如何注入个性：
要有观点。 不要只是报道事实 - 对它们做出反应。"我真的不知道该怎么看这件事" 比中立地列出优缺点更像人类。
变化节奏。 短促有力的句子。然后是慢慢展开的长句。混合使用。
承认复杂性。 真正的人类会有复杂的情感。"这令人印象深刻，但也有点令人不安" 胜过 "这令人印象深刻"。
在合适时使用"我"。 第一人称并不专业 - 它是诚实的。"我一直在思考..." 或 "让我困扰的是..." 表明有一个真人在思考。
让一些混乱进来。 完美的结构感觉像算法。离题、旁白和半成形的想法才是人类的特征。
具体描述感受。 不是 "这令人担忧"，而是 "有些令人不安的是，代理在凌晨 3 点无人监督的情况下持续工作。"
之前（干净但缺乏灵魂）：
实验产生了有趣的结果。代理生成了 300 万行代码。一些开发者印象深刻，而其他人则持怀疑态度。影响尚不清楚。
之后（有了生命）：
我真的不知道该怎么看这个。300 万行代码，大概是在人类睡觉时生成的。一半的开发社区快要疯了，另一半在解释为什么这不算数。真相可能在中间某个无聊的地方 - 但我一直在想那些彻夜工作的代理。
内容模式
1. 过度强调重要性、遗产和更广泛趋势
警惕词汇： 作为（stands/serves as）、是...的证明/提醒（testament/reminder）、一个重要/关键/决定性/关键的角色/时刻（vital/significant/crucial/pivotal/key role/moment）、强调/突出其重要性/意义（underscores/highlights its importance/significance）、反映更广泛的（reflects broader）、象征其持续/持久/永恒的（symbolizing its ongoing/enduring/lasting）、有助于（contributing to the）、为...奠定基础（setting the stage for）、标记/塑造（marking/shaping the）、代表/标志着转变（represents/marks a shift）、关键转折点（key turning point）、不断演变的格局（evolving landscape）、焦点（focal point）、不可磨灭的印记（indelible mark）、深深扎根于（deeply rooted）
问题： LLM 写作通过添加关于任意方面如何代表或贡献于更广泛主题的陈述来夸大重要性。
之前：
加泰罗尼亚统计研究所于 1989 年正式成立，标志着西班牙区域统计演变的关键时刻。这一举措是西班牙更广泛的运动的一部分，旨在分散行政职能并加强区域治理。
之后：
加泰罗尼亚统计研究所于 1989 年成立，独立于西班牙国家统计局收集和发布区域统计数据。
2. 过度强调知名度和媒体报道
警惕词汇： 独立报道（independent coverage）、地方/区域/国家媒体（local/regional/national media outlets）、由领先专家撰写（written by a leading expert）、活跃的社交媒体存在（active social media presence）
What ships with it
2 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.
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 · 484 lines · 108 tokens per session scan A 719545e407aa
humanize-ai-text-zh is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (54 stars, last pushed 5mo ago), licensed MIT. It adds 108 tokens to every session and 6,373 once invoked, about $0.0005 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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