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.
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---
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
```bash
# 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*.