literature-downloader-skill: A Chinese Codex skill for academic literature search, lawful full-text downloading, readable reports

by Lucaswangzcx · Codex Skill · ★ 239

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install literature-downloader-skill

git clone https://github.com/Lucaswangzcx/literature-downloader-skill.git $env:USERPROFILE\.codex\skills\literature-downloader

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 64/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars239
Forks12
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score64/100
Open Issues1
Last Updated2026-04-27
Created2026-04-27
Platformscodex, python
Est. Tokens~4k

About literature-downloader-skill

Literature Downloader Skill 面向中国大学生、研究生、博士和老师的中文文献检索与合法全文获取 Codex Skill。 它不是盗版下载器,也不会绕过付费墙。它的目标是把“找文献、筛文献、查期刊质量、尝试获取开放全文、整理下载结果”做成一套清楚、可复现、适合学生使用的流程。 适合谁 需要快速入门一个研究主题的本科生、研究生、博士生 正在写综述、开题报告、论文引言的同学 需要批量整理 DOI、PDF、期刊指标和阅读清单的研究者 想把文献检索流程交给 AI agent 辅助完成的老师或课题组 能做什么 根据主题生成关键词、同义词和 Boolean 检索式 生成 Google Scholar、PubMed、Crossref、OpenAlex、Semantic Scholar、PMC、arXiv 等检索入口 批量维护候选文献表 按相关性分出高、中、低优先级文献...

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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