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.
5. Velocity Metrics: See citations per year to identify “trending” papers.
6. BibTeX Export: Generate citations for your references.

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”, “citationCount”, or “velocity” (new!).
• --open-access (optional): Only return open access papers.
• --format (optional): Output “json” (default) or “bibtex”.

Example

# Find "hot" papers on LLMs (high velocity)
python3 search_papers.py "Large Language Models" --sort velocity

# Get BibTeX for a specific search
python3 search_papers.py "Attention is All You Need" --format bibtex

Output Format

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

• title
• authors
• year
• citationCount
• citationsPerYear: Velocity metric.
• tldr: Semantic Scholar’s generated summary (if available).
• url
• pdf_url (if available)

Tips for the Agent

• TLDR vs Abstract: The tldr field is often shorter and easier to digest for quick summaries.
• Velocity: A paper from 2024 with 100 citations is often more relevant than a 2010 paper with 500 citations. Use sort=”velocity”.