arxiv-papers-search

name	arxiv-papers-search
description	Search, retrieve, and analyze academic papers from arXiv. Use when: (1) searching for specific research papers, (2) retrieving paper details and abstracts, (3) downloading paper PDFs, (4) analyzing research trends, or (5) getting paper metadata.

Permission Setup Review

python scripts/_wildcard_placeholder.py is an optional setup helper for the Arxiv Skill skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.

Arxiv Skill

Overview

This skill enables searching and retrieving academic papers from the arXiv preprint server. It provides functionality to search for papers by keywords, authors, or categories, retrieve paper details and abstracts, download PDF files, and analyze research trends.

Quick Start

Searching for Papers

To search for papers on arXiv, use the search_papers script with relevant keywords:

python scripts/search_papers.py --query "machine learning" --max-results 10

Retrieving Paper Details

To get detailed information about a specific paper:

python scripts/get_paper_details.py --id 2301.00001

Downloading Papers

To download a paper's PDF:

python scripts/download_paper.py --id 2301.00001 --output paper.pdf

Core Functions

Search Papers

Searches arXiv for papers matching specified criteria. Supports keyword search, author search, and category filtering.

Parameters:

• --query: Search query (required)
• --max-results: Maximum number of results to return (default: 10)
• --category: Filter by arXiv category (e.g., cs.AI, stat.ML)
• --sort-by: Sort results by relevance, lastUpdatedDate, or submittedDate
• --start: Start index for paginated results

Example:

python scripts/search_papers.py --query "transformer architecture" --category cs.CL --max-results 5

Get Paper Details

Retrieves detailed information about a specific paper, including title, authors, abstract, categories, and links.

Parameters:

• --id: arXiv paper ID (required, e.g., 2301.00001)

Example:

python scripts/get_paper_details.py --id 2301.00001

Download Paper

Downloads the PDF of a specific paper.

Parameters:

• --id: arXiv paper ID (required)
• --output: Output file path (default: paper.pdf)

Example:

python scripts/download_paper.py --id 2301.00001 --output transformer-paper.pdf

Workflows

Research Literature Review

1. Search for papers on a topic
2. Retrieve details for relevant papers
3. Download PDFs for in-depth analysis
4. Summarize key findings

Example Workflow:

# Search for recent papers on large language models
python scripts/search_papers.py --query "large language models" --max-results 10 --sort-by lastUpdatedDate

# Get details for a promising paper
python scripts/get_paper_details.py --id 2301.00001

# Download the PDF
python scripts/download_paper.py --id 2301.00001 --output llm-paper.pdf

Trend Analysis

1. Search for papers in a specific category over time
2. Analyze publication trends
3. Identify emerging research areas

Example Workflow:

# Search for papers in machine learning category
python scripts/search_papers.py --query "" --category cs.LG --max-results 100 --sort-by submittedDate

Resources

scripts/

• search_papers.py: Search arXiv for papers
• get_paper_details.py: Get detailed information about a paper
• download_paper.py: Download paper PDFs
• analyze_trends.py: Analyze research trends based on arXiv data

references/

• api_reference.md: arXiv API documentation and usage examples
• categories.md: List of arXiv categories and their descriptions

assets/

• templates/: Templates for generating research summaries

API Reference

For detailed information about the arXiv API, see references/api_reference.md.