scholar-paper-downloader

学术文献PDF批量下载工具,支持从多个学术网站(arXiv、PubMed、PMC、Semantic Scholar等)搜索和下载论文, 自动提取元数据、生成索引列表。优先从官方免费渠道下载,付费文献提供手动下载指引。

What to consider before installing or running this skill: - Coherence: The code matches the described purpose (searching and downloading open academic PDFs). It does not request secrets or system privileges. - Legal/ethical: The skill generates manual download guides that explicitly list Sci‑Hub mirror URLs and step‑by‑step instructions. If you must comply with your institution or local law, remove or edit those guide templates before use. - Code quality: One bundled script (enhanced_downloader.py) appears truncated/buggy near the end — this could cause crashes or unexpected behavior. Inspect that file (and run tests) before using at scale. - Installation: There is no automatic installer; you should create an isolated Python environment and pip install scripts/requirements.txt before running. Run first with a small query and a disposable output directory to observe behavior. - Network & file safety: The tool makes outgoing HTTP requests to public academic sites and writes PDF and Markdown files locally. Run it on a machine or container where network access and file writes are acceptable. - Audit: If you plan to use it regularly, review the code for any logging/network endpoints you don't expect, remove Sci‑Hub references if you don't want to see them, and fix the truncated script. If you want, I can point to the exact lines that reference Sci‑Hub, show the truncated portion of enhanced_downloader.py, or create a sanitized version of the manual download template that omits Sci‑Hub links.

Type: OpenClaw Skill Name: scholar-paper-downloader Version: 1.0.3 The scholar-paper-downloader skill is a legitimate tool designed to search and download academic papers from open-access repositories like arXiv and PubMed Central. The code uses standard libraries (requests, arxiv, PyMuPDF) and implements proper filename sanitization in file_manager.py to prevent path traversal. While enhanced_downloader.py and manual_download_guide.md provide instructions for manually using Sci-Hub to access paid content, the skill does not automate unauthorized access, nor does it exhibit any malicious behaviors such as data exfiltration, persistence, or remote code execution.