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 feishu-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/feishu-paper-reviewer)<a href="https://agentmods.dev/skills/yipng05-max/-skills/feishu-paper-reviewer"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/feishu-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/feishu-paper-reviewer"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/feishu-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 | $0.00126 | $0.02997 |
| Opus 5 | $0.00063 | $0.01499 |
| Sonnet 5 | $0.00025 | $0.00599 |
| Haiku 4.5 | $0.00013 | $0.00300 |
Grade A, and why
feishu-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 12d 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
飞书文档论文审阅
对飞书云文档（docx）中的学术论文进行专业审阅，直接在文档正文中标注修订（高亮、删除线、变色、替换建议），并通过飞书评论系统添加划词批注和全文总评。审阅完成后，作者在飞书中打开文档即可看到所有修订标记和评论。
前置依赖
lark-cli（已安装）- 需要先阅读 lark-shared 了解认证和权限
- 操作依赖：lark-doc（docs +fetch / +update）、lark-drive（drive +add-comment）
工作流程
第 1 步：确认文档并获取内容
向用户确认待审阅的飞书文档 URL 或 doc_id。支持 /docx/ 和 /wiki/ 链接。
lark-cli docs +fetch --doc "<文档URL或ID>"
获取返回的 Markdown 全文。如果文档较长，可使用 --offset 和 --limit 分页获取。
如果用户给出的是 /wiki/ 链接，先查询真实文档类型：
lark-cli wiki spaces get_node --params '{"token":"<wiki_token>"}'
确认 obj_type 为 docx 后，使用 obj_token 进行后续操作。
第 2 步：系统评阅论文
以资深学术期刊审稿人身份，对论文进行全面、系统的评阅。评阅必须严格、专业、建设性。
评阅维度
结构层面：
- 标题是否精准反映研究内容，副标题是否必要
- 摘要是否完整涵盖研究问题、方法、核心发现与贡献
- 引言是否清晰建立了研究问题的学术合法性
- 文献综述是否展现学术脉络与对话关系（而非简单罗列）
- 研究方法是否透明、可信，认识论与方法论是否一致
- 分析与发现是否有充分的证据支撑，论证链条是否完整
- 讨论与结论是否回应了研究问题，理论贡献是否具体
语言层面：
- 概念使用是否一致、精确（一个概念一个术语，全文统一）
- 是否存在空话套话（"随着XX的发展""具有重要意义""丰富了XX研究"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
- 衔接是否自然，逻辑推进是否清晰
学术规范层面：
- 引用是否规范，是否回到原始文献
- 理论使用是否深入（非贴标签式），是否说明边界条件
- 研究贡献表述是否具体而非泛泛
- 方法论反思性是否充分（定性研究尤其重要）
第 3 步：生成修订计划
将评阅结果整理为结构化的修订列表。每条修订必须包含明确的类型、定位信息和理由。
修订总量控制在 15-30 条为宜：太少则审阅不够深入，太多则让作者无所适从。优先处理影响论文核心质量的问题。
修订类型（5 种）
详细语法参见 references/revision-marks.md。
| type | 何时使用 | 正文操作 | 评论操作 |
|---|---|---|---|
highlight |
标注需要作者注意的问题文本 | 黄色高亮 | 划词评论说明问题 |
suggest_delete |
建议删除冗余/不当内容 | 红色删除线 | 划词评论说明理由 |
suggest_replace |
建议用更好的表述替换 | 删除线 + 蓝色新文本 | 划词评论说明理由 |
comment_only |
宏观建议，不直接改正文 | 无 | 划词评论 |
callout_insert |
章节级审阅意见 | 插入 callout 块 | 无 |
颜色约定
| 颜色 | 含义 | Markdown 写法 |
|---|---|---|
| 黄色高亮 | 需注意的问题 | <text background-color="yellow">文本</text> |
| 红色文字 | 严重问题 / 建议删除 | <text color="red">~~文本~~</text> |
| 蓝色粗体 | 建议替换的新文本 | <text color="blue">**新文本**</text> |
| 绿色 callout | 值得肯定之处 | <callout emoji="✅" background-color="light-green"> |
| 黄色 callout | 审阅意见 / 修改建议 | <callout emoji="📝" background-color="light-yellow"> |
| 红色 callout | 严重问题说明 | <callout emoji="⚠️" background-color="light-red"> |
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.
- 12d ago First seen · 225 lines · 126 tokens per session scan A c035226e7152
feishu-paper-reviewer is a skill published in the GitHub repository yipng05-max/-skills (286 stars, last pushed 4mo ago), licensed MIT. It adds 126 tokens to every session and 2,997 once invoked, about $0.0006 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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