biorxiv-database

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill biorxiv-database
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summary

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.

skill.md

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
  1. 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
how to use biorxiv-database

How to use biorxiv-database on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add biorxiv-database
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill biorxiv-database

The skills CLI fetches biorxiv-database from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/biorxiv-database

Reload or restart Cursor to activate biorxiv-database. Access the skill through slash commands (e.g., /biorxiv-database) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.673 reviews
  • Maya Jackson· Dec 28, 2024

    biorxiv-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Fatima Khan· Dec 24, 2024

    Solid pick for teams standardizing on skills: biorxiv-database is focused, and the summary matches what you get after install.

  • Yusuf Mensah· Dec 20, 2024

    biorxiv-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ren Ramirez· Dec 12, 2024

    We added biorxiv-database from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Dec 4, 2024

    Useful defaults in biorxiv-database — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sakura Nasser· Dec 4, 2024

    Useful defaults in biorxiv-database — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amina Gupta· Dec 4, 2024

    Keeps context tight: biorxiv-database is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Rahul Santra· Nov 23, 2024

    biorxiv-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Fatima Farah· Nov 23, 2024

    biorxiv-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Amina Jackson· Nov 23, 2024

    Registry listing for biorxiv-database matched our evaluation — installs cleanly and behaves as described in the markdown.

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