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thu-thesis

作者 Chao1208 · GitHub ↗ · v1.5.6 · MIT-0
cross-platform ⚠ suspicious
581
总下载
0
收藏
2
当前安装
38
版本数
在 OpenClaw 中安装
/install thu-thesis
功能描述
自动将清华毕业论文 Word (.docx) 转换为符合 thuthesis 官方模板规范的完整高质量 PDF,支持章节、摘要、图表、参考文献等处理。
安全使用建议
What to consider before installing or running this skill: - Review scripts first: open scripts/setup.sh, scripts/convert.py, scripts/render.py, build_parsed.py and extract_raw.py. Confirm there are no unexpected network endpoints, telemetry, or obfuscated code paths. Do not run setup.sh until you inspect it. - Inspect setup.sh: it will git-clone https://github.com/tuna/thuthesis into /tmp and overwrite assets/databk/ (rm -rf && cp -r). If you rely on a local assets/databk/, back it up. Only run setup.sh in a controlled environment (container, VM, or sandbox). - Sandbox execution: run the tool inside an isolated container/VM with no access to sensitive host data, and with network access restricted if you want to avoid fetching remote repos. - Back up user documents: the tool creates a <stem>-latex/ folder next to the input .docx and modifies files in that directory; keep backups of your original .docx and any existing LaTeX projects before running. - Inspect included sample data: the skill archive contains many parsed/output JSON and .md files with real-looking student names, birth dates and other PII. Remove or treat these files as sensitive; they do not need to be uploaded anywhere. - Prompt-injection warning: the SKILL.md contained unicode control characters (scanner flagged). These can be used to try to influence LLM behavior. Manually inspect SKILL.md for hidden characters and remove them before allowing autonomous model steps (AI-generated struct.json or auto-repair). - Restrict agent write/network privileges: if your environment allows, restrict the agent skill's file-write scope to only a safe temp directory and disallow outbound network unless explicitly needed. Consider running the AI 'struct.json' generation step manually if you do not trust automatic writes. - Validate external sources: confirm the thuthesis repository URL and contents are legitimate (check commit history / tags). If you must update the template, prefer cloning a verified release and verifying checksums. If you are not comfortable with these manual reviews or sandboxing, do not install or run the skill. If you proceed, perform the first runs on non-sensitive sample documents.
功能分析
Type: OpenClaw Skill Name: thu-thesis Version: 1.5.6 The skill bundle is a legitimate utility designed to convert Word (.docx) Tsinghua University theses into standardized LaTeX/PDF format. The scripts (extract_raw.py, build_parsed.py, render.py) use standard libraries like python-docx and jinja2 to process document content, while setup.sh fetches the official thuthesis template from the reputable TUNA (Tsinghua University TUNA Association) GitHub repository. The AI-specific instructions in SKILL.md are strictly task-oriented, directing the agent to analyze document structure and evaluate output quality without any evidence of prompt injection, data exfiltration, or malicious execution.
能力评估
Purpose & Capability
Name/description match what the package delivers: Python scripts to extract .docx, build JSON, render thuthesis LaTeX, and run xelatex/bibtex. Example outputs and templates are included which are consistent with a conversion tool. Unexpected: the bundle contains many example/parsed output files (real thesis content, names, birth dates, etc.) — presence of PII inside the skill archive is surprising and should be considered before installing.
Instruction Scope
SKILL.md gives the agent explicit permission to read conversion artefacts (raw/parsed/struct JSON, .tex, .bib, thesis.log, thesis.pdf) and to write struct.json and directly modify .tex files during 'automatic repair' (up to 3 compile cycles). That capability is within converter scope but grants the agent write/modify permissions over the user's LaTeX project; combined with instruction-level prompt-injection indicators (unicode control chars), this is a notable scope risk and should be audited.
Install Mechanism
No formal install spec, lowering disk-install risk. However scripts/setup.sh will git-clone the thuthesis repo from GitHub into /tmp/thuthesis-latest, build thuthesis.cls, and overwrite assets/databk/ via rm -rf && cp -r data/. Pulling and building remote code is expected for keeping the template up-to-date but does execute network fetch + local filesystem changes — review setup.sh before running and prefer running in a sandbox/container.
Credentials
The skill requests no environment variables or credentials, and only lists typical Python/TeX dependencies. That is proportional. Note: it assumes the agent (or runtime) can write files (Write tool / filesystem) and invoke xelatex/bibtex; ensure those permissions are intended.
Persistence & Privilege
always:false and no special persistent privileges. The skill does however take actions that modify local files (creating <stem>-latex/, writing/rewriting .tex, copying databk from a freshly cloned repo). Autonomous invocation is allowed (default) — this is the platform norm, but combined with file-write and remote-clone behavior it increases the impact if misused.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install thu-thesis
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /thu-thesis 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.5.6
新增手工修复强制检查流程:写章节正文前必须先列出原文所有表格/图片清单并逐章核对,防止表格数据丢失
v1.5.5
文档:Rubric 由 AI 执行细则;图片/表格全链路说明。流程:extract 即创建 latex 目录。渲染:numeric 引用、关键词转义、致谢/简历模板字段。移除 evaluate/llm_parse/parse_docx 废弃脚本。
v1.5.4
参考文献默认改为 numeric 样式([1][2]序号);main.tex.j2 加 PassOptionsToPackage{numbers}{natbib};解决 author-year 模式下作者名重复显示问题;移除 \nocite{}(正文已有 \cite{} 覆盖)
v1.5.3
Rubric C3精化:必须同时检查refs.bib和.bbl,检查佚名/截断/空字段;C4精化:检查.bbl每条内容是否合理;C5精化:严格区分\cite和\nocite(正文引用vs仅进入参考文献列表);修复render.py机构名APA引用格式解析bug(德勤/高力国际/美国旅游协会/英文大学名等不再显示为佚名)
v1.5.2
移除 SKILL.md 中的硬编码绝对路径,改为通用占位路径 /path/to/skills/thu-thesis;修复 ClawHub 安全扫描告警
v1.5.1
AI Rubric 评测(替换 Python evaluate.py);图表处理全链路重写含失败原因排查;修复 resume/acknowledgements 模板变量名 bug;修复 keywords 特殊字符未转义;.doc 转换工具警告;convert.py extract 即创建 LaTeX 目录并打印图表位置;删除废弃脚本
v1.6.1
Remove shell=True from subprocess calls to fix suspicious flag
v1.6.0
Add output path spec, fix suspicious flags
v1.5.0
修复英文关键词逐词拆散、中文日期解析(十一月等复合月份)、封面日期为空兜底、插图/附表清单精确检测、评测报告增加执行摘要、参考文献作者匹配优化
v1.4.0
新增 D4 插图清单检查、E4 附表清单检查(38项/满分90分);修复 listoffigures 未生成 bug;修复表格列数推断、keywords tojson、title* 冒号、chapter 模板字段名等多项 render bug;H2 过滤 SimSun/xeCJK non-fatal noise
v1.3.1
新增手工转换 Phase 1-6 完整流程指南;新增 convert-rubric.md(35项/95分 Word→LaTeX 转换质量 Rubric)
v1.3.0
重构为 AI-native 三层架构:Python 脚本不再调用 LLM;AI 负责阅读骨架生成 struct.json;新增 build_parsed.py 纯 Python 组装器;convert.py 改为 extract/build 两步命令;修复表格提取(正确过滤封面表,正文表格完整保留);API key 安全性修复
v1.2.6
Version 1.2.6 introduces automatic post-evaluation repair, improving conversion reliability and user experience. - 增加 Step 5「评测后自动修复」:对可自动修复的问题(如元信息误识别、BibTeX 空字段、author-year引用丢失)立即修正并重跑流程,无需用户操作 - 修复循环机制:每发现问题后自动修复,最多循环3次并汇报修复结果 - 修改 README (SKILL.md) 补充「自动修复」相关文档说明,列出可/不可自动修复项与流程 - 保留不可自动修复问题为 WARN,报告中明确指出原始 Word 内容限制
v1.2.5
- Improved error reporting in evaluation_report.md, now including full error context for LaTeX compilation failures. - Enhanced LaTeX log parsing to extract and display the first actual error line, making debugging easier.
v1.2.4
SKILL.md: add scoring rubric doc + deduction annotation requirement; format_report: full message in detail table (no truncation)
v1.2.3
C6 cite relevance: random sample audit (10 cites with context+bib written to report for human review); machine proxy = bib author/title both empty → deduct 1pt each, max 10
v1.2.2
Rubric engine: real scoring (PASS=full, WARN=half, FAIL=0, DEDUCT=-N); per-dimension scores; 百分制总分+评级; NA items excluded from denominator
v1.2.1
Add C6 cite content relevance check (deduction scoring: -1 per orphan cite, max -10); C7 for author-year compliance; DEDUCT status in rubric engine; expanded WEIGHT_LABEL
v1.2.0
Major: author-year citation detection now covers all authors in multi-author refs; CamelCase pinyin name lookup (BiyuTang→tang/biyu); expanded pinyin map (刘/欧/肖 etc); C6 rubric: 202→2 uncited refs on Wang Yaling thesis
v1.1.9
Add author-year citation detection: auto-insert \cite for narrative citations (曹玉(2025)→ \cite{...}); support CamelCase pinyin names; add rubric C6 critical check for uncited author-year references
元数据
Slug thu-thesis
版本 1.5.6
许可证 MIT-0
累计安装 2
当前安装数 2
历史版本数 38
常见问题

thu-thesis 是什么?

自动将清华毕业论文 Word (.docx) 转换为符合 thuthesis 官方模板规范的完整高质量 PDF,支持章节、摘要、图表、参考文献等处理。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 581 次。

如何安装 thu-thesis?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install thu-thesis」即可一键安装,无需额外配置。

thu-thesis 是免费的吗?

是的,thu-thesis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

thu-thesis 支持哪些平台?

thu-thesis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 thu-thesis?

由 Chao1208(@chao1208)开发并维护,当前版本 v1.5.6。

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