Agent skill
academic-research
This skill should be used for academic paper search, literature reviews, and research synthesis. Combines Exa MCP (research_paper category, arxiv.org filtering) with arxiv-mcp-server for paper discovery, download, and deep analysis. Use when searching for papers, conducting literature reviews, analyzing research trends, or synthesizing findings across multiple papers.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/skills/other/academic-research
SKILL.md
Academic Research
This skill provides comprehensive guidance for academic paper search, literature reviews, and research synthesis using Exa MCP and arxiv-mcp-server.
When to Use This Skill
- Searching for academic papers on a topic
- Conducting literature reviews
- Finding papers by specific authors
- Discovering recent research in a field
- Downloading and analyzing arXiv papers
- Synthesizing findings across multiple papers
- Tracking citation networks and influential papers
- Researching state-of-the-art methods in AI/ML
Available Tools
Exa MCP Server (Web Search with Academic Filtering)
Tools: mcp__exa__web_search_exa, mcp__exa__get_code_context_exa, mcp__exa__deep_search_exa
Key Parameters for Academic Search:
category: "research_paper"- Filter results to academic papersincludeDomains: ["arxiv.org"]- Restrict to arXivstartPublishedDate/endPublishedDate- Filter by publication date
ArXiv MCP Server (Paper Search, Download, Analysis)
Tools: search_papers, download_paper, list_papers, read_paper
Capabilities:
- Search arXiv by keyword, author, or category
- Download papers locally (~/.arxiv-papers)
- Read paper content directly
- Deep paper analysis with built-in prompts
Core Workflows
Workflow 1: Quick Paper Discovery
Use case: Find papers on a specific topic quickly
Step 1: Use Exa with research_paper category
mcp__exa__web_search_exa({
query: "transformer attention mechanisms survey",
category: "research_paper",
numResults: 10
})
Step 2: Review titles and abstracts
Step 3: Note arXiv IDs for deeper analysis
Workflow 2: ArXiv-Focused Search
Use case: Search specifically within arXiv
Step 1: Use arxiv MCP search_papers
search_papers({
query: "large language models reasoning",
max_results: 20,
sort_by: "relevance"
})
Step 2: Download papers
download_paper({ arxiv_id: "2301.00234" })
Step 3: Read and analyze
read_paper({ arxiv_id: "2301.00234" })
Workflow 3: Comprehensive Literature Review
Step 1: Broad discovery with Exa (category: "research_paper")
Step 2: Identify key papers and authors
Step 3: Deep dive with arXiv MCP (download + read_paper)
Step 4: Synthesize findings by methodology/approach
Workflow 4: Recent Developments Tracking
Step 1: Time-filtered Exa search
mcp__exa__web_search_exa({
query: "multimodal large language models",
category: "research_paper",
startPublishedDate: "2024-01-01"
})
Step 2: Sort arXiv by submitted_date
search_papers({ query: "multimodal LLM", sort_by: "submitted_date" })
ArXiv Categories Reference
| Category | Description |
|---|---|
| cs.AI | Artificial Intelligence |
| cs.CL | Computation and Language (NLP) |
| cs.CV | Computer Vision |
| cs.LG | Machine Learning |
| cs.NE | Neural and Evolutionary Computing |
| stat.ML | Statistics - Machine Learning |
| cs.RO | Robotics |
Academic Domain Filtering
For Exa searches, restrict to academic sources:
includeDomains: [
"arxiv.org",
"aclanthology.org",
"openreview.net",
"proceedings.mlr.press",
"papers.nips.cc",
"openaccess.thecvf.com"
]
Tool Selection Guide
| Task | Primary Tool | Alternative |
|---|---|---|
| Broad topic search | Exa (research_paper) | arXiv search_papers |
| ArXiv-specific | arXiv search_papers | Exa with includeDomains |
| Download paper | arXiv download_paper | - |
| Full paper content | arXiv read_paper | - |
| Code implementations | Exa get_code_context | - |
| Very recent papers | arXiv (submitted_date) | Exa with date filter |
Best Practices
- Start broad with Exa's research_paper category, then narrow
- Use date filtering for recent developments
- Download key papers via arXiv MCP for persistent access
- Cross-reference multiple search approaches
- Use technical terms in queries for better results
Reference Documentation
For detailed parameters and advanced usage:
references/exa-academic-search.md- Exa parameters for academic searchreferences/arxiv-mcp-tools.md- ArXiv MCP server tool reference
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