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 guyumengyue/zotero-obsidian-codex-workflow --skill literature-processorgit clone --depth 1 https://github.com/guyumengyue/zotero-obsidian-codex-workflowWrote 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/guyumengyue/zotero-obsidian-codex-workflow/literature-processor)<a href="https://agentmods.dev/skills/guyumengyue/zotero-obsidian-codex-workflow/literature-processor"><img src="https://agentmods.dev/badge/skills/guyumengyue/zotero-obsidian-codex-workflow/literature-processor/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/guyumengyue/zotero-obsidian-codex-workflow/literature-processor"><img src="https://agentmods.dev/badge/skills/guyumengyue/zotero-obsidian-codex-workflow/literature-processor.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 | $0.00045 | $0.01212 |
| Opus 5.5 | $0.00018 | $0.00485 |
| Sonnet 5.5 | $0.00009 | $0.00242 |
| Haiku 4.5 | $0.00005 | $0.00121 |
Grade A, and why
literature-processor 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 1mo 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Processor
在 Research vault/ 里工作时，使用这个 skill 处理文献 PDF、补全文献笔记、重算相关文献网络，并基于已有笔记继续做综述写作与研究设计。
Scope
- 工作目录固定为
Research vault/ - PDF 固定放在
literature/pdf/ - 文献笔记固定放在
literature/notes/ - 引用库默认是
references.bib/library.bib - 模板固定使用
_templates/论文笔记模版.md
不要在仓库根目录使用这个 skill 做初始化；仓库初始化应交给 repo-root 的 $zotero-obsidian-codex-setup。
Triggers
处理 literature/pdf/ 里的新文献处理 literature/pdf/某篇论文.pdf刷新 literature/notes/ 里所有笔记的相关文献区块先读文献索引，再找和某个主题最相关的文献基于现有笔记写文献综述/引言/实验设计
Primary Workflow
1. 找到目标 PDF 或目标笔记
- 新文献默认来自
literature/pdf/ - 单篇处理时优先使用用户给出的具体文件
- 批量处理时优先处理尚未形成高质量成品笔记的 PDF
- 如遇扫描版、受密码保护、或文本抽取质量过低的 PDF，要明确告诉用户卡点
2. 复用或补全文献笔记
- 读取
_templates/论文笔记模版.md - 如果已存在英文骨架笔记，优先在原笔记上补全
- 如果已存在中文成品笔记，继续补写该成品笔记
- 不要为同一篇文献反复创建重复笔记
3. 提取结构化内容
严格依据论文原文，不编造：
核心问题摘要创新点前言与文献综述实验数据与方法核心结论方法局限性引用的开创性、高被引文献与我研究的关联下一步实验建议我的想法/问题
如果某部分原文没有足够信息，明确写出“无相关内容”或说明证据不足，不要留空装作已经读到。
4. 规范命名与引用
- 成品笔记文件名统一收口到
期刊-中文标题.md YAML title、journal、citekey保留原始学术元数据- 正文引用统一使用
[@citekey] - 提到 vault 里已有文献时，优先使用
[[期刊-中文标题]] - 英文文献如果没有合适的
shortTitle，可以在处理时生成准确、简洁、适合作为文件名的中文短标题 - 不强制修改 PDF 原文件名
5. 刷新相关文献区块
- 每次处理完新文献后，都要重算
literature/notes/下全部笔记的## 相关文献（自动更新） - 使用脚本：
python .agents/skills/literature-processor/scripts/refresh_related_notes.py .
- 关联计算优先看这些章节：
核心问题摘要实验数据与方法核心结论与我研究的关联
- 相关文献区块应输出“带理由列表”，理由来自：
同研究问题同变量/对象/情境同理论框架同方法设计结论互补/冲突
- 如果配置了 embedding API，则在本地候选召回后做语义重排
- 如果 embedding API 不可用、超时或失败，必须自动退回本地增强版，不能中断整库刷新
Writing Tasks
处理完笔记后，还可以继续承担这些任务：
- 先读
文献索引.md再找主题相关文献 - 基于已有笔记写英文文献综述或 Introduction
- 做批判性阅读，从实验设计、样本、数据支撑和库内一致性几个角度审查
- 结合已有文献给出最小可验证实验方案
- 整理
inbox/中的材料并给出归档建议
Constraints
- 严格遵循原文，不编造数据或结论
- 遇到扫描件、加密 PDF、或明显损坏的 PDF，直接说明无法可靠处理
- 发现重复笔记时，不覆盖已有高质量成品
- 如果旧文件名已被其他笔记引用，优先保留别名或兼容链接，避免断链
- 不要把初始化工作、插件安装工作、或仓库结构调整混到这个 skill 里
- 不确定时直接说明不确定，不要用想象补齐
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.
- 1mo ago First seen · 115 lines · 45 tokens per session scan A 00dc0d6b4869
literature-processor is a skill published in the GitHub repository guyumengyue/zotero-obsidian-codex-workflow (13 stars, last pushed 5mo ago), licensed MIT. It adds 45 tokens to every session and 1,212 once invoked, about $0.0002 per session on Opus 5.5. 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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