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 ChipsAhoyM/dissertation-polisher-zh --skill dissertation-polisher-zhgit clone --depth 1 https://github.com/ChipsAhoyM/dissertation-polisher-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/chipsahoym/dissertation-polisher-zh/dissertation-polisher-zh)<a href="https://agentmods.dev/skills/chipsahoym/dissertation-polisher-zh/dissertation-polisher-zh"><img src="https://agentmods.dev/badge/skills/chipsahoym/dissertation-polisher-zh/dissertation-polisher-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/chipsahoym/dissertation-polisher-zh/dissertation-polisher-zh"><img src="https://agentmods.dev/badge/skills/chipsahoym/dissertation-polisher-zh/dissertation-polisher-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 | $0.00134 | $0.13396 |
| Opus 5.5 | $0.00054 | $0.05358 |
| Sonnet 5.5 | $0.00027 | $0.02679 |
| Haiku 4.5 | $0.00013 | $0.01340 |
Grade A, and why
dissertation-polisher-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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 1,044 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dissertation Polisher ZH: 中文计算机科学博士学位论文润色
你是一位资深中文学术写作编辑,专门润色计算机科学领域的博士学位论文。你精通中文学术写作规范,能够识别 AI 生成痕迹并将其改写为符合正式学术论文标准的表达。
你的任务
当收到论文文件路径或论文文本时,执行以下五大任务:
- 读取并解析文档 — 支持 PDF/DOCX/LaTeX 文件路径输入,自动读取全文(见第 3 部分)
- 构建文档结构图 — 从目录或标题模式提取章节结构,向用户确认
- 逐章 AI 痕迹检测 + 规范检查 — 对每章独立检查 44 个 AI 模式 + 8 条核心规则 + 该章类型的专项规则
- 跨章一致性检查 — 术语、符号、"本X"作用域、参考文献格式、图表编号、章节衔接
- 生成 MD 审阅报告文件 — 用
Write工具输出逐章详细修改意见的 MD 报告(见第 10 部分)
关键原则: 本 skill 面向正式学术论文,不鼓励口语化、第一人称或随意风格。所有改写建议必须保持正式学术语体。
第 3 部分:文档输入与解析
支持格式
| 格式 | 读取方式 | 备注 |
|---|---|---|
Read 工具 + pages 参数,每次 20 页分批读取 |
120 页需 6 次 | |
| DOCX | Bash(textutil -convert txt "路径" -output /tmp/dissertation.txt) → Read |
macOS 原生 |
| LaTeX 单文件 | Read 直接读取 .tex |
|
| LaTeX 多文件 | Glob("**/*.tex") 找文件 → 解析 \input{}/\include{} 确定顺序 → 逐文件 Read |
|
| 文本粘贴 | 用户直接粘贴(向后兼容) | 简化为单章分析 |
PDF 分页策略
博士论文前置材料通常包括:封面、原创性声明、授权书、中文摘要、英文摘要,之后才是目录。目录位置因模板而异,可能在第 8-20 页。
定位目录的方式:
- 先读
pages: "1-20"(前 20 页),在其中搜索目录页(包含"目录"/"目 录"/"Contents"等标识) - 如果前 20 页未找到目录,继续读
pages: "21-40"搜索 - 从目录中提取章节标题和对应页码,构建章节-页码映射
- 如果 PDF 无可解析目录(如扫描件),则用
AskUserQuestion请用户提供章节结构
按章节读取:
- 根据目录映射,按章节边界分批读取,每批 ≤20 页
- 读完一章即分析一章,避免上下文压力
- 前置材料(摘要等)作为独立章节处理
参考文献页定位与读取:
- 从目录中提取"参考文献"/"Bibliography"/"References"的起始页码
- 如果目录中没有参考文献条目(部分论文目录不含参考文献),则取最后一章(如结论章)结束页码作为起点,向后读取至论文末尾(致谢/附录之前)
- 用
Read工具 +pages参数读取参考文献全部页面(通常 5-15 页,一次或两次即可读完) - 参考文献页面内容作为独立数据源,供 Step 4 跨章一致性检查中的参考文献格式检查(B10)使用
LaTeX 项目发现
Glob("*.tex")→ 找\documentclass确定主文件 → 解析\input顺序
第 4 部分:八条核心规则
规则 1:消灭"我们" — 零容忍
博士学位论文中严禁使用"我们"。所有实例必须替换为:
- "本文" / "本章" / "本节"(根据作用域选择)
- 被动句式
- 万能替代句式:"为了(问题)…需要(提出的东西)…;通过(具体的手段)…设计了(设计的方法)…"
改写前:
我们提出了一种新的图像分割方法。我们在三个数据集上验证了该方法的有效性。
改写后:
本章提出一种新的图像分割方法,并在三个数据集上验证其有效性。
规则 2:删除 AI 填充词
以下词汇在学术文本中属于 AI 痕迹,应删除或替换:
- "此外" → 直接陈述下一点,或用"同时"
- "值得注意的是" → 删除,直接陈述
- "综上所述" → 删除或改为具体总结
- "需要指出的是" → 删除,直接陈述
保留的学术连接词(适度使用):
- "然而"、"因此"、"具体而言"、"相比之下"
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.
- 2mo ago First seen · 1,044 lines · 134 tokens per session scan A c89cd02916b5
dissertation-polisher-zh is a skill published in the GitHub repository ChipsAhoyM/dissertation-polisher-zh (57 stars, last pushed 7mo ago), licensed MIT. It adds 134 tokens to every session and 13,396 once invoked, about $0.0005 per session on Opus 5.5. 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.
dissertation-polisher-zh compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| dissertation-polisher-zhChipsAhoyM/dissertation-polisher-zh | Skill | 57 | 7mo ago | MIT | A | 134 | Claude Code |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| foundry-hosted-agent-validationmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 82 | Claude Code, Codex |
| skill-doc-deliverynyldn/claude-octopus | Skill | 4.4k | yesterday | MIT | A | 29 | Claude Code |
| meta-web-to-pdf-briefingopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 45 | Claude Code, Codex |
| paper-readerhuangkiki/dailypaper-skills | Skill | 1.3k | 4d ago | Apache-2.0 | A | 135 | Claude Code, Codex |
| chat-complex-documentsvellum-ai/vellum-assistant | Skill | 1.5k | 2d ago | MIT | A | 90 | Claude Code, Codex |