dr-claw
Dr. Claw skill for OpenClaw project discovery, idea intake, waiting-session triage, structured session control, event-driven notifications, and mobile…
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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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.
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.
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.
Use this skill when:
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
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
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
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"
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")Filter searches by bioRxiv subject categories:
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": ""
}
]
}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']}")A Super AI Lab with massive AI Doctors as Assistants. Best IDE for Research via AI Power.
Repo: OpenLAIR/dr-claw
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