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paper-fetch

Skill Documents & Content Usable

Legal open-access PDF downloader by DOI — Unpaywall, arXiv, PMC, bioRxiv. Multi-platform Agent Skill.

97 starsMIT (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Reduces manual paper retrieval overhead by automatically sourcing open-access PDFs across multiple repositories. Eliminates paywalls and broken links for research-heavy workflows.

Research teams, legal analysts, and compliance officers who need rapid access to academic and legal documents without subscription costs.

Claude Code Claude Cowork Claude Chat

https://github.com/Agents365-ai/paper-fetch

By Agents365-ai

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install Agents365-ai/paper-fetch

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars97Last updated2026-05-19LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-05-21 · scanner v1

Community Pulse Active

Discussed on Hacker News, Reddit

12 mentions across 2 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 97 GitHub stars; contributors unknown; last commit 2d ago; license MIT.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 UsableEvaluatedMay 2026
Scored from trust signals (evidence-eval-v1): 97 GitHub stars; contributors unknown; last commit 2d ago; license MIT.

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