skills/43-wentorai-research-plugins/skills/writing/polish/chinese-text-humanizer/SKILL.md
Transform AI-generated Chinese text into natural academic writing style
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research chinese-text-humanizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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AI-generated Chinese academic text often exhibits detectable patterns: overly balanced sentence structures, formulaic transitions, predictable hedging, and unnaturally consistent register. This guide provides strategies to transform AI-assisted drafts into natural, human-sounding Chinese academic prose while maintaining scholarly rigor. Applicable to journal manuscripts, thesis chapters, and grant applications written in Chinese.
| Pattern | AI Tendency | Human Academic Style | |---------|-----------|---------------------| | Sentence openings | 重复使用 "本文"、"本研究"、"值得注意的是" | 变换主语:具体名词、被动句式、无主句 | | Transitions | 机械使用 "首先…其次…最后" | 自然承接:因果、转折、递进交替 | | Hedging | 每句都加 "可能"、"一定程度上" | 有选择地使用限定语,关键结论要果断 | | Paragraph structure | 总-分-总,每段等长 | 段落长短不一,论证节奏有变化 | | Vocabulary | 偏好"关键""重要""显著" | 用词精确:分辨"关键/核心/至关重要"的语境差异 | | 列举 | 大量并列三项 ("X、Y和Z") | 有时二项,有时四项,避免刻板的三项并列 |
AI 风格(机械均匀):
"深度学习在自然语言处理中取得了显著进展。研究者提出了多种模型来解决文本分类问题。
这些方法在标准数据集上取得了良好效果。然而,实际应用中仍面临诸多挑战。"
修改后(节奏变化):
"深度学习正深刻改变自然语言处理的面貌——从文本分类到机器翻译,预训练模型已成为
事实上的标准范式。不过,标准数据集上的高分并不总能转化为实际场景中的可靠表现。
部署环境中的分布偏移、标注噪声以及计算资源限制,都使得从实验室到生产环境的过渡
远非一帆风顺。"
改进点:
✓ 长短句交替
✓ 破折号引入补充说明
✓ 具体化 "诸多挑战"
✓ "远非一帆风顺" 比 "仍面临挑战" 更生动
| AI 公式化 | 替代方案 | |----------|---------| | 首先…其次…最后… | 删除序号词,用逻辑关系自然承接 | | 值得注意的是 | 直接陈述,或用 "尤其是"、"特别是" | | 综上所述 | "以上分析表明" 或直接给出结论 | | 总的来说 | "总体而言" 或省略,直接表述 | | 研究表明 | 具体引用:"Li et al. (2024) 发现…" | | 具有重要意义 | 说清楚重要在哪里:"这为X提供了Y" |
AI(泛化的学术腔):
"本研究采用混合方法研究设计,结合定量和定性数据分析,
以期全面了解该现象。"
经济学风格:
"我们构建了一个双重差分模型,利用2016年政策冲击作为外生变量,
识别市场准入放宽对中小企业融资成本的因果效应。"
社会学风格:
"通过对15位流动务工人员的深度访谈,本文试图理解制度性排斥如何
在日常生活实践中被体验和回应。"
改进点:
✓ 具体的方法名称(不是 "混合方法")
✓ 具体的研究对象(不是 "该现象")
✓ 学科特有术语(因果效应、外生变量、制度性排斥)
中文学术写作的特有习惯(AI 常遗漏):
1. 四字格的适当使用(但不过度):
✓ "方兴未艾""不容忽视""有待商榷"
✗ 不要每句都塞入四字格
2. 引述惯例:
✓ "正如张三 (2023) 所指出的,…"
✓ "有学者认为…(李四,2024;王五,2023)"
✗ AI 常写:"研究表明…" 但不给出具体引用
3. 数据呈现:
✓ "回归结果(表3第(2)列)显示,处理组均值提高了12.3个百分点(p<0.01)"
✗ AI 常写:"结果显示变量之间存在显著正相关关系"(太模糊)
4. 论文基金致谢:
✓ 放在首页脚注,格式:"本研究受国家自然科学基金项目(No. XXXXXXX)资助"
AI 通常生成 "总-分-总" 结构的等长段落。修改策略:
1. 合并过短的段落(少于3句的段落考虑合并)
2. 拆分过长的段落(超过8句时寻找分割点)
3. 删除重复表述(AI 喜欢在段首和段尾重复相同观点)
4. 添加段间逻辑标记("与此形成对照的是""这一发现的理论含义在于")
5. 允许段落长短不一(3句段和7句段交替出现更自然)
## 逐段检查清单
□ 删除了所有 "本文"/"本研究" 的过度使用(每页不超过2次)
□ 替换了公式化过渡词
□ 检查了每个 "重要/显著/关键" 是否有具体说明
□ 确保引用了具体文献(不是泛泛的 "研究表明")
□ 段落长度有变化(不是每段都5-6句)
□ 句式有变化(长短句交替,主动被动穿插)
□ 四字格使用适度(每段不超过1-2个)
□ 数据引用精确(有表格编号、列号、数值)
□ 读起来像你自己写的(而不是任何人都能写的通用文本)
development
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data-ai
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