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biorxiv-database

Search bioRxiv preprints by keywords, authors, dates, or categories.

94|11|Updated Mar 26, 2026
Search Tags:#pdf#search#metadata#preprints#biorxiv#doi
One-click install
npx skills add https://github.com/swaruplab/operon --skill biorxiv-database-swaruplab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: biorxiv-database
Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/biorxiv-database
Command: npx skills add https://github.com/swaruplab/operon --skill biorxiv-database-swaruplab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Researchers need a fast, reliable way to locate relevant bioRxiv preprints and retrieve metadata and PDFs for downstream analysis without manual searching.

Core Features & Use Cases

  • Keyword and author-based search across bioRxiv with category filtering
  • Retrieve structured metadata (title, authors, date, DOI, category) and download PDFs
  • Programmatic usage via a Python API or CLI for literature reviews or trend analysis

Quick Start

Provide keywords and optional date ranges to fetch preprint metadata and PDFs for review.

Frequently Asked Questions about biorxiv-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search bioRxiv preprints by keyword, author, and date range?▼

Search bioRxiv preprints by providing keywords, authors, and optional date ranges to fetch matching metadata. The client handles category filters and returns structured JSON output containing titles, authors, dates, and DOIs for your queries.

Can I download bioRxiv PDFs programmatically using a Python requests client?▼

Yes, you can download bioRxiv PDFs programmatically. The Python requests-based client retrieves preprint metadata and handles PDF downloads, returning structured JSON output so you can automate literature reviews and trend analysis.

What is the best way to get structured metadata for bioRxiv preprints across biology categories?▼

Getting structured bioRxiv metadata involves filtering by biology categories and date ranges to retrieve titles, authors, dates, DOIs, and categories. The client outputs this data as structured JSON, making it ready for citation management.

Do I need Python and the requests library to retrieve bioRxiv DOIs and metadata?▼

Yes, you need Python and the requests library to use this Skill. The requests-based client queries bioRxiv to retrieve DOIs and metadata, requiring a basic Python environment setup to execute the scripts and process the JSON output.

Does this bioRxiv search tool support category filtering for literature reviews?▼

Yes, the bioRxiv search tool supports category filtering. You can apply category filters alongside keyword and date parameters to narrow preprint results, making it efficient for targeted literature reviews across specific biology domains.

What are the limitations of using a requests-based client for bioRxiv preprint searches?▼

A limitation of using a requests-based client for bioRxiv searches is dependency on the requests library and API availability. Complex queries may require multiple calls, and PDF downloads depend on bioRxiv server response times and rate limits.

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