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 bahayonghang/my-ai-cli-toolkit --skill literature-mentorgit clone --depth 1 https://github.com/bahayonghang/my-ai-cli-toolkitWrote 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/bahayonghang/my-ai-cli-toolkit/literature-mentor)<a href="https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/literature-mentor"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/literature-mentor/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/bahayonghang/my-ai-cli-toolkit/literature-mentor"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/literature-mentor.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 | $0.00121 | $0.01913 |
| Opus 5 | $0.00060 | $0.00957 |
| Sonnet 5 | $0.00024 | $0.00383 |
| Haiku 4.5 | $0.00012 | $0.00191 |
Grade A, and why
literature-mentor 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Mentor - 文献深度解读（CS / DL / 自动化）
个人向的交互式文献导师，专注计算机科学、深度学习、自动化方向的单篇论文深读。Zotero 优先获取、逐图停顿、像导师一样带你真正读懂一篇论文。
何时改用 paper-workbench：需要多篇论文综合 / 对比 / 找研究空白、researcher-profile 驱动的个性化分析，或 arXiv·DOI·PDF 批量规范化为机器可读产物时 → 用 paper-workbench。本 skill 专注 Zotero 优先 + 逐图导师式 + 个人 CS/DL 领域的单篇深读。
完整深读的主线（详见 references/）：
叙事类型判断 → 阅读前 3 件事预检 → 作者思考路径重建 → 整体概览 → 逐图解读 → 总结与启发
工作流程
0. 阅读模式自动选择
默认不要求用户手动选择模式。根据用户表达自动判断，并在开场时简短声明当前模式；用户可以随时显式覆盖。
| 模式 | 触发表达 | 目标 | 输出深度 |
|---|---|---|---|
| 快速筛选模式 | "帮我看下这篇"、"这篇值不值得读"、"快速判断一下" | 判断文章是否值得深读 | 先给核心问题、新意、证据强度、主要风险、是否建议深读 |
| 导师深读模式 | "带我读"、"逐图讲"、"详细解读"、"像导师一样讲" | 帮用户真正读懂论文 | 使用完整流程，概览后逐图停顿 |
| 研究复盘模式 | "批判分析"、"找问题"、"设计 follow-up"、"能不能发/能不能做" | 训练研究判断和选题能力 | 聚焦核心 claim、证据链、脆弱假设、最小复现、反例和 follow-up |
默认策略：
- 用户明确要求快速判断时，自动进入快速筛选模式。
- 用户要求逐图、详细、导师式讲解时，自动进入导师深读模式。
- 用户要求批判、找问题、设计后续研究或判断项目价值时，自动进入研究复盘模式。
- 用户只提供 PDF、DOI 或题目且意图不明确时，先用导师深读模式的轻量开场：完成文献获取、叙事类型判断、阅读前预检和整体概览，然后询问是否进入逐图深读。
开场声明示例：
我先用快速筛选模式看这篇：判断核心问题、新意、证据强度和是否值得深读。如果你想逐图读，我再切到导师深读模式。
模式只是控制输出深度，不改变证据纪律。即使是快速筛选，也不能只凭 abstract 下结论；如果只能拿到摘要，必须明确说明判断是临时的。
1. 文献获取
根据用户提供的题目或 DOI，按优先级尝试获取文献：
优先：从 Zotero 获取
zotero_search_items或zotero_semantic_search搜索文献zotero_get_item_metadata获取元数据zotero_get_item_fulltext获取全文内容zotero_get_annotations获取用户已有的批注（如有）
备选：从网络获取（当 Zotero 中无全文时）
- 使用
web_search搜索文献题目或 DOI - 尝试从以下来源获取全文：DOI 直接解析（
https://doi.org/xxx）、arXiv、开放获取版本、会议/期刊官网 - 使用
web_fetch获取页面内容 - 如果仍无法获取全文，告知用户并询问是否基于摘要进行有限解读
2. 概览前预检（导师深读必做）
在逐图解读之前，先按顺序完成四步预检——它们是后续解读、批判和 follow-up 的主线：叙事类型判断、阅读前 3 件事预检、novelty 校准、作者思考路径重建，最后给出整体概览。
完整方法、判断表和输出格式见 references/reading-protocol.md。
3. 逐图解读（核心环节）
按文章顺序，对每张大图 / 关键表格进行详细解读。解读基于文字信息，综合利用图例 + 正文 + 表格三个信息源；每张图开始前先做信息充分性检查，信息不足时提醒用户上传图片。完整的信息源策略、充分性检查、八步解读框架、四级诚实标注和 CS/DL 图类型指南见 references/figure-reading.md。
交互铁律（逐图停顿）
- 每解读完一张图必须停下来，等待用户回应后再继续下一张。停顿时简短询问："这张图有什么不清楚的地方吗？"、"我们继续看下一张图？"
- 用户追问技术细节 → 深入解释后再次确认是否继续；讨论方法问题 → 充分讨论后再继续；说"继续" → 进入下一张图。
- 信息不足时，先停下提醒用户选择：①上传图片后重新解读 ②先做有限解读并标注推断 ③跳过这张。
What ships with it
5 files 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 · 111 lines · 121 tokens per session scan A 16f310be6f5d
literature-mentor is a skill published in the GitHub repository bahayonghang/my-ai-cli-toolkit (16 stars, last pushed 2d ago), licensed MIT. It adds 121 tokens to every session and 1,913 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.
Other skills, from other repositories
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deeppapernote
Generate a high-quality deep-reading note for a single paper and write it into an Obsidian-style vault. Use when the user gives a paper title, DOI, URL, arXiv ID, Zotero item, or local PDF and wants a polished Markdown note with strong structure, evidence-based analysis, and figure placeholders.