# Academic Search > Search academic paper repositories (arXiv, Semantic Scholar) for scholarly articles in physics, mathematics, computer science, quantitative biology, AI/ML, and related fields Use when this capability is needed. - Skill: `tomevault-io/academic-search` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/academic-search` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/academic-search/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/academic-search --- # Academic Search Skill This skill provides access to academic paper repositories, primarily arXiv, for searching scholarly articles. arXiv is a free distribution service and open-access archive for preprints in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, systems science, and economics. ## When to Use This Skill Use this skill when you need to: - **Find cutting-edge research**: Access preprints and recent papers before formal journal publication - **Search AI/ML papers**: Find machine learning, deep learning, and artificial intelligence research - **Explore computational methods**: Search for algorithms, theoretical frameworks, and mathematical foundations - **Research interdisciplinary topics**: Find papers spanning computer science, biology, physics, and mathematics - **Gather literature reviews**: Collect relevant papers for comprehensive topic overviews - **Track state-of-the-art**: Find the latest advances in rapidly evolving fields ### Ideal Use Cases | Scenario | Example Query | |----------|---------------| | Understanding new architectures | "transformer attention mechanism" | | Exploring applications | "large language models code generation" | | Finding benchmarks | "image classification benchmark ImageNet" | | Surveying methods | "reinforcement learning robotics" | | Technical deep-dives | "backpropagation neural networks" | ## How to Use The skill provides a Python script that searches arXiv and returns formatted results with titles and abstracts. ### Basic Usage **Note:** Always use the absolute path from your skills directory. If running from a virtual environment: ```bash .venv/bin/python [YOUR_SKILLS_DIR]/academic-search/arxiv_search.py "your search query" ``` Or for system Python: ```bash python3 [YOUR_SKILLS_DIR]/academic-search/arxiv_search.py "your search query" ``` Replace `[YOUR_SKILLS_DIR]` with the absolute skills directory path from your system prompt. ### Command-Line Arguments | Argument | Required | Default | Description | |----------|----------|---------|-------------| | `query` | Yes | - | The search query string | | `--max-papers` | No | 10 | Maximum number of papers to retrieve | | `--output-format` | No | text | Output format: `text`, `json`, or `markdown` | ### Examples **Search for transformer architecture papers:** ```bash python3 arxiv_search.py "attention is all you need transformer" --max-papers 5 ``` **Search for reinforcement learning papers:** ```bash python3 arxiv_search.py "deep reinforcement learning continuous control" --max-papers 10 ``` **Search for LLM papers with JSON output:** ```bash python3 arxiv_search.py "large language model reasoning" --output-format json ``` **Search for specific author or topic:** ```bash python3 arxiv_search.py "author:Hinton deep learning" ``` **Search in specific arXiv categories:** ```bash python3 arxiv_search.py "cat:cs.LG neural network pruning" ``` ## Step-by-Step Workflow ### 1. Formulate Your Query - Use specific, technical terms (e.g., "convolutional neural network image segmentation" not "AI for pictures") - Include key authors if known: `author:Bengio` - Specify arXiv categories for focused results: `cat:cs.CL` (Computation and Language) - Combine terms for intersection: `"graph neural network" AND "molecular property"` ### 2. Execute the Search ```bash python3 [SKILLS_DIR]/academic-search/arxiv_search.py "your refined query" --max-papers 10 ``` ### 3. Review Results The output includes: - **Title**: Full paper title - **Authors**: List of paper authors - **Published**: Publication date - **arXiv ID**: Unique identifier (useful for citing) - **URL**: Direct link to the paper - **Summary**: Abstract text ### 4. Iterate if Needed - Too many irrelevant results? Add more specific terms or use category filters - Too few results? Broaden the query or remove restrictive terms - Looking for recent work? arXiv sorts by relevance by default ### 5. Save and Synthesize Save relevant findings to your research workspace for later synthesis: ``` research_workspace/ papers/ topic_findings.md ``` ## Output Formats ### Text Format (Default) ``` ================================================================================ Title: Attention Is All You Need Authors: Ashish Vaswani, Noam Shazeer, Niki Parmar, ... Published: 2017-06-12 arXiv ID: 1706.03762 URL: https://arxiv.org/abs/1706.03762 -------------------------------------------------------------------------------- Summary: The dominant sequence transduction models are based on complex recurrent or convolutional neural networks... ================================================================================ ``` ### JSON Format ```json { "query": "transformer attention", "total_results": 5, "papers": [ { "title": "Attention Is All You Need", "authors": ["Ashish Vaswani", "Noam Shazeer", ...], "published": "2017-06-12", "arxiv_id": "1706.03762", "url": "https://arxiv.org/abs/1706.03762", "summary": "The dominant sequence transduction models..." } ] } ``` ### Markdown Format ```markdown ## Attention Is All You Need **Authors:** Ashish Vaswani, Noam Shazeer, ... **Published:** 2017-06-12 **arXiv ID:** [1706.03762](https://arxiv.org/abs/1706.03762) ### Abstract The dominant sequence transduction models are based on complex... ``` ## arXiv Category Reference Common categories for AI/ML research: | Category | Description | |----------|-------------| | `cs.LG` | Machine Learning | | `cs.AI` | Artificial Intelligence | | `cs.CL` | Computation and Language (NLP) | | `cs.CV` | Computer Vision | | `cs.NE` | Neural and Evolutionary Computing | | `cs.RO` | Robotics | | `stat.ML` | Machine Learning (Statistics) | | `q-bio` | Quantitative Biology | | `math.OC` | Optimization and Control | ## Best Practices ### Query Construction 1. **Be specific**: "graph attention network node classification" > "graph neural network" 2. **Use quotation marks**: For exact phrases: `"self-supervised learning"` 3. **Combine operators**: `cat:cs.CV AND "object detection" AND 2023` 4. **Include variations**: Search for both "LLM" and "large language model" ### Research Workflow Integration 1. **Start broad, then narrow**: Begin with general queries, refine based on initial results 2. **Track paper IDs**: Save arXiv IDs for citing and revisiting 3. **Check references**: Seminal papers often cite foundational work 4. **Note publication dates**: Preprints may be superseded by updated versions ### Limitations to Consider - **Preprint status**: Papers may not be peer-reviewed - **Version updates**: Check for newer versions (v2, v3, etc.) - **Coverage gaps**: Not all fields are well-represented on arXiv - **Rate limiting**: Avoid excessive rapid queries ## Dependencies This skill requires the `arxiv` Python package: ```bash # Virtual environment (recommended) .venv/bin/python -m pip install arxiv # System-wide python3 -m pip install arxiv ``` The script will detect if the package is missing and display installation instructions. ## Troubleshooting ### "Error: arxiv package not installed" Install the arxiv package as shown in Dependencies section. ### No results returned - Try broader search terms - Remove category restrictions - Check for typos in technical terms ### Rate limiting errors - Wait a few seconds between queries - Reduce `--max-papers` value ### Connection errors - Check internet connectivity - arXiv API may have temporary outages ## Integration with Research Workflow This skill works well with the web-research skill for comprehensive research: 1. **Use academic-search** for foundational/theoretical papers 2. **Use web-research** for current implementations, tutorials, and practical guides 3. **Synthesize** findings from both sources in your research report ## Notes - arXiv is particularly strong for: - Computer Science (cs.*) - Physics (physics.*, hep-*, cond-mat.*) - Mathematics (math.*) - Quantitative Biology (q-bio.*) - Statistics (stat.*) - Results are sorted by relevance by default - The arXiv API is free and requires no authentication - Consider checking cited papers for deeper understanding --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/hyunjunjeon) — claim your Tome and manage your conversions.