academic-research

name	academic-research
description	A tool for rigorous academic research using Semantic Scholar and ArXiv. Focuses on finding highly-cited papers, retrieving abstracts, and following citation trails to understand the provenance of ideas.

Academic Research Skill

This skill allows you to function as an academic researcher, finding and analyzing scholarly papers with a focus on impact and provenance.

Capabilities

1. Search Papers: Find papers by keyword, ensuring relevance.
2. Analyze Impact: Filter by citation count to identify seminal works.
3. Trace Provenance: (Optional) Find papers that cite a target paper to seeing how the field evolved.
4. Get Details: Retrieve abstracts and direct PDF links.

Usage

Run the python script search_papers.py to perform searches.

Arguments

• query (required): The search term.
• --limit (optional): Max results (default 5).
• --year (optional): Year range (e.g., "2023-2025").
• --sort (optional): Sort by "relevance" or "citationCount" (default "relevance").
• --open-access (optional): Only return open access papers.

Example

# Find top 5 seminal papers on "Large Language Models"
python3 search_papers.py "Large Language Models" --sort citationCount --limit 5

# Find recent research on "RAG" from 2024
python3 search_papers.py "Retrieval Augmented Generation" --year 2024-2025

Output Format

The script outputs a JSON object (or JSON-lines) containing:

• title
• authors
• year
• abstract (truncated if too long)
• citationCount
• url
• pdf_url (if available)

Tips for the Agent

• Be Skeptical: High citation count doesn't always mean "correct," but it means "influential."
• Check Recency: For fast-moving fields (AI), prioritize year > citations.
• Contextualize: When summarizing, mention who wrote it (e.g., "DeepMind," "Stanford") and when.