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awesome-paper-skill
End-to-end pipeline for topic-driven literature research: collect papers from multiple sources, generate an Awesome-style README, and update/push to user GitHub repo.
Legitimate academic paper aggregation pipeline with no malicious behavior; all shell/network operations are documented, necessary, and use standard APIs and GitHub CLI tools.
技能名称awesome-paper-skill
分析耗时40.9s
引擎pi
可以安装
This skill can be used safely. The shell:WRITE permission is required for git/gh CLI operations which are fully documented in SKILL.md.
资源类型声明权限推断权限状态证据
文件系统 READ READ ✓ 一致 build_awesome_readme.py reads JSON, writes README; fetch_papers.py writes JSON
网络访问 READ READ ✓ 一致 fetch_papers.py: HTTP GET to arXiv/Crossref/Semantic Scholar APIs (lines 16-26, …
命令执行 WRITE WRITE ✓ 一致 publish_repo.py: subprocess.run() for git/gh commands (lines 18-40)
环境变量 NONE NONE No os.environ access detected
技能调用 NONE NONE No nested skill invocations
剪贴板 NONE NONE No clipboard access
浏览器 NONE NONE No browser automation
数据库 NONE NONE No database access
8 项发现
🔗
中危 外部 URL 外部 URL
https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg
scripts/build_awesome_readme.py:9
🔗
中危 外部 URL 外部 URL
https://img.shields.io/badge/
scripts/build_awesome_readme.py:28
🔗
中危 外部 URL 外部 URL
https://export.arxiv.org/api/query?search_query=all:
scripts/fetch_papers.py:20
🔗
中危 外部 URL 外部 URL
http://www.w3.org/2005/Atom
scripts/fetch_papers.py:25
🔗
中危 外部 URL 外部 URL
https://api.crossref.org/works?query=
scripts/fetch_papers.py:55
🔗
中危 外部 URL 外部 URL
https://doi.org/
scripts/fetch_papers.py:80
🔗
中危 外部 URL 外部 URL
https://api.semanticscholar.org/graph/v1/paper/search?query=
scripts/fetch_papers.py:101
🔗
中危 外部 URL 外部 URL
https://arxiv.org/abs/
scripts/fetch_papers.py:116

目录结构

5 文件 · 13.7 KB · 443 行
Python 3f · 351L Markdown 1f · 87L JSON 1f · 5L
├─ 📁 scripts
│ ├─ 🐍 build_awesome_readme.py Python 117L · 3.6 KB
│ ├─ 🐍 fetch_papers.py Python 186L · 6.0 KB
│ └─ 🐍 publish_repo.py Python 48L · 1.8 KB
├─ 📋 _meta.json JSON 5L · 138 B
└─ 📝 SKILL.md Markdown 87L · 2.2 KB

依赖分析 1 项

包名版本来源已知漏洞备注
urllib stdlib Python 3 Standard library only; no external dependencies

安全亮点

✓ All capabilities declared in SKILL.md match actual implementation
✓ No credential harvesting or exfiltration detected
✓ No obfuscation, base64 execution, or anti-analysis techniques
✓ Network requests target legitimate academic APIs (arXiv, Crossref, Semantic Scholar)
✓ Shell commands limited to documented git/gh CLI operations
✓ No sensitive file paths (~/.ssh, ~/.aws, .env) accessed
✓ No reverse shell, C2, or data theft mechanisms
✓ User-Agent header identifies tool properly (openclaw-awesome-research-tracker/1.0)