What is the BioRxiv Database skill?

It is a specialized tool for Claude Code that allows users to programmatically search, filter, and download preprints from the bioRxiv server using Python scripts.

How does the skill handle bioRxiv API limits?

The tool includes automatic delays between requests and provides tools for batch processing to ensure compliance with server rate limits.

Is the search data easy to use for further analysis?

All search results are returned as structured JSON, making it easy to convert into pandas DataFrames or integrate into downstream software pipelines.

Does it support filtering by specific biological fields?

Yes, you can filter results by 27 distinct categories including genomics, neuroscience, biochemistry, and bioengineering.

Can I download full-text papers with this skill?

Yes, the skill supports downloading full-text PDFs using a paper's DOI, facilitating deep-text analysis or offline reading.

BioRxiv Database Research Tool

Name: BioRxiv Database Research Tool
Author: Microck

byMicrock

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Web Scraping & Data Collection

Enables efficient searching and retrieval of life sciences preprints from the bioRxiv server for research and analysis.

About

This skill provides a specialized Python-based interface for interacting with the bioRxiv preprint server, allowing researchers and developers to conduct systematic literature reviews and track scientific trends within Claude. Users can perform comprehensive searches using keywords, specific authors, date ranges, and 27 distinct biological subject categories to retrieve structured JSON metadata or download full-text PDFs. It is an essential tool for automating the discovery of recent biological research, managing citations, and integrating real-time preprint data into data science or academic workflows.

Key Features

89 GitHub stars
Structured JSON output containing full metadata and abstracts
Full-text PDF download capabilities for automated analysis
Built-in rate limiting and batch processing for large datasets
Multi-parameter search by keywords, authors, categories, and dates
Support for 27 specialized biological subject categories

Use Cases

Monitoring recent publications and preprints from specific authors or labs
Generating research trend datasets for data science and analysis pipelines
Conducting automated systematic literature reviews for research areas

About

Key Features

89 GitHub stars
Structured JSON output containing full metadata and abstracts
Full-text PDF download capabilities for automated analysis
Built-in rate limiting and batch processing for large datasets
Multi-parameter search by keywords, authors, categories, and dates
Support for 27 specialized biological subject categories

Use Cases

Monitoring recent publications and preprints from specific authors or labs
Generating research trend datasets for data science and analysis pipelines
Conducting automated systematic literature reviews for research areas