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 yipng05-max/-skills --skill paper-reviewergit clone --depth 1 https://github.com/yipng05-max/-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/yipng05-max/-skills/paper-reviewer)<a href="https://agentmods.dev/skills/yipng05-max/-skills/paper-reviewer"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/paper-reviewer/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/yipng05-max/-skills/paper-reviewer"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/paper-reviewer.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 | $0.00000 | $0.01486 |
| Opus 5 | $0.00000 | $0.00743 |
| Sonnet 5 | $0.00000 | $0.00297 |
| Haiku 4.5 | $0.00000 | $0.00149 |
Grade A, and why
paper-reviewer 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 11d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
学术论文评阅
对 Word(.docx)或 PDF 格式的学术论文进行专业评阅,生成带评阅标注的 Word 文档。支持两种输出模式:
- 可视化评阅(默认推荐):红色删除线标记删除、蓝色下划线标记新增、黄色底纹段落标记审稿意见。兼容所有文字处理软件(Word、WPS、LibreOffice、Pages)。
- 修订痕迹:使用 Word OOXML tracked changes 格式。需要在 Microsoft Word 中开启「审阅→显示标记」查看。WPS 兼容性有限。
触发条件
当用户要求对 Word 或 PDF 文档论文进行评阅、审稿、修改、批注时触发。关键词包括:评阅论文、审稿、论文修改、Word修订、批注论文。支持 .docx 和 .pdf 格式。
脚本位置
所有脚本位于本 SKILL.md 同级的 scripts/ 目录下:
scripts/apply_revisions.py— 评阅标注处理引擎(支持visual和apply两种命令)
工作流程
第 1 步:获取论文文件路径
向用户确认 Word 文档的路径。如果用户只给了文件名,在常见位置搜索:
- ~/Downloads/
- ~/Documents/
- ~/Desktop/
- 当前工作目录
第 2 步:提取论文内容
python3 ${SKILL_DIR}/scripts/apply_revisions.py extract "<论文路径.docx或.pdf>"
这会输出带段落编号的 JSON,包含每段的 index、style、text。如果输入是 PDF,会自动先转为 DOCX 再提取。
第 3 步:逐段评阅论文
以资深社会学期刊审稿人的身份,对论文进行系统评阅。评阅维度包括:
结构层面:
- 标题是否精准反映研究内容
- 摘要是否包含研究问题、方法、核心发现和贡献
- 引言是否清晰建立了研究问题的合法性
- 文献综述是否展现了学术脉络而非简单罗列
- 研究方法部分是否足够透明、可信
- 分析与发现是否有充分的证据支撑
- 讨论与结论是否回应了研究问题
语言层面:
- 概念使用是否一致、精确
- 是否存在空话套话(如"随着XX的发展""具有重要意义"等)
- 论证是否遵循主张-证据-推理结构
- 段落是否有明确主题句
学术规范层面:
- 引用是否规范
- 理论使用是否深入(非贴标签式)
- 研究贡献表述是否具体
第 4 步:生成修订 JSON
重要:必须通过 Python 脚本生成 JSON 文件(不要用 Write 工具直接写 JSON,因为中文引号等特殊字符会导致编码错误)。
将评阅意见组织为 Python dict,用 json.dump(data, f, ensure_ascii=False) 写入临时文件。格式如下:
import json
revisions = {
"revisions": [
{
"type": "replace",
"paragraph_index": 3,
"old_text": "需要修改的原文片段(必须与文档中完全一致)",
"new_text": "修改后的文本",
"comment": "修改理由(中文,简明扼要)"
},
{
"type": "comment",
"paragraph_index": 5,
"comment": "评阅意见(针对该段的问题或建议)"
},
{
"type": "delete",
"paragraph_index": 8,
"old_text": "建议删除的文本",
"comment": "删除理由"
}
]
}
with open('/tmp/revisions.json', 'w', encoding='utf-8') as f:
json.dump(revisions, f, ensure_ascii=False, indent=2)
修订类型说明:
replace:文本替换。可视化模式显示为红色删除线(旧)+ 蓝色下划线(新)comment:仅添加审稿意见段落,不修改正文delete:标记删除。可视化模式显示为红色删除线
What ships with it
1 file 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.
- 11d ago First seen · 149 lines · 0 tokens per session scan A 5468e5a95f47
paper-reviewer is a skill published in the GitHub repository yipng05-max/-skills (285 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,486 tokens. 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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