Borrowing it
Nothing to install: this file belongs to ZimoLiao/scholaraio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZimoLiao/scholaraio/main/.claude/skills/review-response/SKILL.mdgit clone --depth 1 https://github.com/ZimoLiao/scholaraioWrote 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/zimoliao/scholaraio/review-response)<a href="https://agentmods.dev/skills/zimoliao/scholaraio/review-response"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/review-response/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/zimoliao/scholaraio/review-response"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/review-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.01027 |
| Opus 5 | $0.00015 | $0.00513 |
| Sonnet 5 | $0.00006 | $0.00205 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
review-response 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.
What it actually says
审稿回复
逐条回复审稿人意见,从工作区文献和原稿中定位支撑证据。
前提
用户需提供:
- 审稿意见:粘贴或文件路径
- 原稿:workspace 中的论文草稿或文件路径
- workspace:关联的文献工作区(用于检索支撑证据)
- 语言:中文 / English(回复信通常与原稿语言一致)
执行逻辑
1. 解析审稿意见
将审稿意见拆分为独立的 comment,分类标注:
- MAJOR:需要实质性修改(补实验、改方法、加分析)
- MINOR:表述修改、格式调整、补充说明
- POSITIVE:正面评价(致谢即可)
- QUESTION:需要回答的问题
2. 逐条分析
对每条意见:
- 理解审稿人的核心诉求
- 在原稿中定位相关段落
- 用
scholaraio show查看论文(已有notes.md笔记会自动展示),复用已有发现 - 在工作区文献中搜索支撑证据:
scholaraio ws search <name> "<审稿人关注的关键词>" scholaraio show <paper-id> --layer 3 # 读结论找证据 scholaraio show <paper-id> --layer 4 # 必要时读全文 - 从引用图谱中找额外支撑:
scholaraio refs "<id>" # 相关论文的参考文献 scholaraio usearch "<补充关键词>" # 全库搜索(工作区外)
3. 撰写回复
每条回复的结构:
> **Reviewer X, Comment N:** [原文引用]
**Response:** [回复正文]
[如有修改] **Revision:** We have revised Section X.X as follows: "..." (Page X, Line X)
回复策略:
- 同意并修改:明确说明做了什么修改、在哪里
- 部分同意:承认合理之处,解释为什么不完全采纳,提供证据
- 礼貌反驳:用数据和文献支撑,语气尊重但立场坚定
- 补充实验/分析:描述新增的内容和结果
多模态辅助:
- 审稿人质疑图表时,读取论文中的原始图(
images/)重新分析 - 审稿人质疑数值时,编写 Python 代码独立复现计算,用代码输出作为回复证据
- 审稿人质疑推导时,读取论文中的公式逐步验证
4. 输出
- 保存回复信到
workspace/<name>/response-letter.md - 必须通过 CLI 将深度分析的论文关键发现写入笔记:
scholaraio show "<paper-id>" --append-notes "## YYYY-MM-DD | <workspace> | review-response - 关键发现" - 如需补充引用新论文到工作区:
scholaraio ws add <name> <paper-id>
写作原则
- 逐条回复,不遗漏:每条意见都必须有明确回应
- 证据优先:能用数据和文献回答的,不用空话
- 语气专业:感谢审稿人的建设性意见,即使不同意也保持尊重
- 修改可追踪:明确标注修改位置(Section、Page、Line)
- 引用核验:提交前用
/citation-check检查回复信中新增或改动过的 author-year 引用 - 不回避弱点:如果审稿人指出的确是问题,坦诚承认并说明改进措施
示例
用户说:"审稿意见回来了,帮我写 response letter" → 解析意见,分类标注,逐条在工作区中找证据,撰写回复
用户说:"Reviewer 2 说我的方法跟 Smith (2023) 没区别,怎么回" → 在工作区中找到 Smith (2023),对比方法差异,起草有理有据的反驳
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 · 97 lines · 31 tokens per session scan A c87d1d6474ed
review-response is a skill published in the GitHub repository ZimoLiao/scholaraio (570 stars, last pushed 11d ago), licensed MIT. It adds 31 tokens to every session and 1,027 once invoked, about $0.0002 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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