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/biorxiv-database

Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

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Install
$ npx -y skills add OpenLAIR/dr-claw --skill biorxiv-database --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/biorxiv-database

Context preview

The summary Claude sees to decide when to auto-load this skill.

Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

SKILL.md

biorxiv-database.SKILL.md
name: biorxiv-database
description: Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

bioRxiv Database

Overview

This skill provides efficient Python-based tools for searching and retrieving preprints from the bioRxiv database. It enables comprehensive searches by keywords, authors, date ranges, and categories, returning structured JSON metadata that includes titles, abstracts, DOIs, and citation information. The skill also supports PDF downloads for full-text analysis.

When to Use This Skill

Use this skill when:

  • Searching for recent preprints in specific research areas
  • Tracking publications by particular authors
  • Conducting systematic literature reviews
  • Analyzing research trends over time periods
  • Retrieving metadata for citation management
  • Downloading preprint PDFs for analysis
  • Filtering papers by bioRxiv subject categories

Core Search Capabilities

1. Keyword Search

Search for preprints containing specific keywords in titles, abstracts, or author lists.

**Basic Usage:**

python scripts/biorxiv_search.py \
  --keywords "CRISPR" "gene editing" \
  --start-date 2024-01-01 \
  --end-date 2024-12-31 \
  --output results.json

**With Category Filter:**

python scripts/biorxiv_search.py \
  --keywords "neural networks" "deep learning" \
  --days-back 180 \
  --category neuroscience \
  --output recent_neuroscience.json

**Search Fields:** By default, keywords are searched in both title and abstract. Customize with `--search-fields`:

python scripts/biorxiv_search.py \
  --keywords "AlphaFold" \
  --search-fields title \
  --days-back 365

2. Author Search

Find all papers by a specific author within a date range.

**Basic Usage:**

python scripts/biorxiv_search.py \
  --author "Smith" \
  --start-date 2023-01-01 \
  --end-date 2024-12-31 \
  --output smith_papers.json

**Recent Publications:**

# Last year by default if no dates specified
python scripts/biorxiv_search.py \
  --author "Johnson" \
  --output johnson_recent.json

3. Date Range Search

Retrieve all preprints posted within a specific date range.

**Basic Usage:**

python scripts/biorxiv_search.py \
  --start-date 2024-01-01 \
  --end-date 2024-01-31 \
  --output january_2024.json

**With Category Filter:**

python scripts/biorxiv_search.py \
  --start-date 2024-06-01 \
  --end-date 2024-06-30 \
  --category genomics \
  --output genomics_june.json

**Days Back Shortcut:**

# Last 30 days
python scripts/biorxiv_search.py \
  --days-back 30 \
  --output last_month.json

4. Paper Details by DOI

Retrieve detailed metadata for a specific preprint.

**Basic Usage:**

python scripts/biorxiv_search.py \
  --doi "10.1101/2024.01.15.123456" \
  --output paper_details.json

**Full DOI URLs Accepted:**

python scripts/biorxiv_search.py \
  --doi "https://doi.org/10.1101/2024.01.15.123456"

5. PDF Downloads

Download the full-text PDF of any preprint.

**Basic Usage:**

python scripts/biorxiv_search.py \
  --doi "10.1101/2024.01.15.123456" \
  --download-pdf paper.pdf

**Batch Processing:** For multiple PDFs, extract DOIs from a search result JSON and download each paper:

import json
from biorxiv_search import BioRxivSearcher

# Load search results
with open('results.json') as f:
    data = json.load(f)

searcher = BioRxivSearcher(verbose=True)

# Download each paper
for i, paper in enumerate(data['results'][:10]):  # First 10 papers
    doi = paper['doi']
    searcher.download_pdf(doi, f"papers/paper_{i+1}.pdf")

Valid Categories

Filter searches by bioRxiv subject categories:

  • `animal-behavior-and-cognition`
  • `biochemistry`
  • `bioengineering`
  • `bioinformatics`
  • `biophysics`
  • `cancer-biology`
  • `cell-biology`
  • `clinical-trials`
  • `developmental-biology`
  • `ecology`
  • `epidemiology`
  • `evolutionary-biology`
  • `genetics`
  • `genomics`
  • `immunology`
  • `microbiology`
  • `molecular-biology`
  • `neuroscience`
  • `paleontology`
  • `pathology`
  • `pharmacology-and-toxicology`
  • `physiology`
  • `plant-biology`
  • `scientific-communication-and-education`
  • `synthetic-biology`
  • `systems-biology`
  • `zoology`

Output Format

All searches return structured JSON with the following format:

{
  "query": {
    "keywords": ["CRISPR"],
    "start_date": "2024-01-01",
    "end_date": "2024-12-31",
    "category": "genomics"
  },
  "result_count": 42,
  "results": [
    {
      "doi": "10.1101/2024.01.15.123456",
      "title": "Paper Title Here",
      "authors": "Smith J, Doe J, Johnson A",
      "author_corresponding": "Smith J",
      "author_corresponding_institution": "University Example",
      "date": "2024-01-15",
      "version": "1",
      "type": "new results",
      "license": "cc_by",
      "category": "genomics",
      "abstract": "Full abstract text...",
      "pdf_url": "https://www.biorxiv.org/content/10.1101/2024.01.15.123456v1.full.pdf",
      "html_url": "https://www.biorxiv.org/content/10.1101/2024.01.15.123456v1",
      "jatsxml": "https://www.biorxiv.org/content/...",
      "published": ""
    }
  ]
}

Common Usage Patterns

Literature Review Workflow

1. **Broad keyword search:**

python scripts/biorxiv_search.py \
  --keywords "organoids" "tissue engineering" \
  --start-date 2023-01-01 \
  --end-date 2024-12-31 \
  --category bioengineering \
  --output organoid_papers.json

2. **Extract and review results:**

import json

with open('organoid_papers.json') as f:
    data = json.load(f)

print(f"Found {data['result_count']} papers")

for paper in data['results'][:5]:
    print(f"\nTitle: {paper['title']}")
    print(f"Authors: {paper['authors']}")
    print(f"Date: {paper['date']}")
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