Academic Paper Fetcher

Fetch academic papers from Sci-Hub given a DOI. Automatically downloads PDFs and saves them to research/papers/ with clean filenames. Use when the user provides a DOI or requests a paper from PubMed.

This skill mostly does what it says (downloads PDFs from a hard-coded Sci‑Hub domain). Before installing, consider: 1) Legal/ethical: Sci‑Hub distributes copyrighted material in many jurisdictions — ensure you are comfortable with that risk. 2) Undeclared runtime dependency: the Python script calls curl via subprocess but the skill metadata does not list curl as required; ensure curl and network access are available and acceptable. 3) Mismatched claims: SKILL.md mentions browser navigation and Obsidian/automation integrations that are not implemented in the script — don’t assume those features exist. 4) Safety: downloaded PDFs can contain exploits (rare) and files are written to your workspace path; run the script in a sandboxed environment if you are unsure. 5) If you want more confidence, ask the author to (a) declare required binaries (curl), (b) remove or implement claimed integrations, and (c) optionally allow selecting an alternative, lawful source (publisher APIs, institutional access) instead of Sci‑Hub.

Type: OpenClaw Skill Name: paper-fetcher Version: 1.0.0 The skill is classified as suspicious due to its interaction with `sci-hub.su`, a domain known for copyright infringement, which introduces inherent supply chain risks (e.g., potential for serving compromised content, though the script only downloads PDFs). Additionally, the `scripts/fetch_paper.py` script allows writing downloaded files to an arbitrary `output_dir` specified via command-line arguments, which could lead to path traversal vulnerabilities if the agent passes untrusted input, despite the `SKILL.md` suggesting a contained path. There is no clear evidence of intentional malicious behavior like data exfiltration or persistence.