semantic-scholar-database

name	semantic-scholar-database
description	Access the Semantic Scholar Graph API to search papers and retrieve paper/author/citation data when you need literature discovery or citation graph exploration.
license	MIT
author	AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

• You need to find relevant papers by keyword, title, or known identifiers (e.g., Semantic Scholar Paper ID).
• You want to fetch detailed metadata for a paper (abstract, venue, year, fields of study, etc.).
• You need author-centric information such as an author profile and their publications.
• You want to explore a citation network by traversing references or citations for a given paper.
• You are building a literature review workflow that requires programmatic access to scholarly graph data.

Key Features

• Paper search via the Semantic Scholar Graph API.
• Paper details retrieval (e.g., abstract, venue, citations-related fields depending on requested fields).
• Author details retrieval (author profile and associated papers depending on requested fields).
• Citation graph traversal:
  • Fetch papers that cite a target paper (citations)
  • Fetch papers referenced by a target paper (references)
• Optional API key support for higher rate limits via environment variable.

Dependencies

• Python >=3.9
• requests >=2.25.0

Example Usage

import os
from scripts.client import (
    search_papers,
    get_paper_details,
    get_author_details,
    get_citations,
)

# Optional: set for higher rate limits
# os.environ["S2_API_KEY"] = "YOUR_API_KEY"

def main():
    # 1) Search papers
    results = search_papers(query="Attention Is All You Need", limit=5)
    print("Search results (top 5):")
    for i, p in enumerate(results, 1):
        # The exact keys depend on the fields requested by the client implementation.
        print(f"{i}. {p.get('title')} ({p.get('year')}) - paperId={p.get('paperId')}")

    # 2) Get paper details
    paper_id = "649def34f8be52c8b66281af98ae884c09aef38b"
    paper = get_paper_details(paper_id=paper_id)
    print("\nPaper details:")
    print("Title:", paper.get("title"))
    print("Venue:", paper.get("venue"))
    print("Year:", paper.get("year"))
    print("Abstract:", (paper.get("abstract") or "")[:300], "...")

    # 3) Get author details
    author_id = 
    author = get_author_details(author_id=author_id)
    ()
    (, author.get())
    (, author.get())

    
    citing = get_citations(paper_id=paper_id, method=)
    refs = get_citations(paper_id=paper_id, method=)
    ()
    (, (citing)  (citing, )  )
    (, (refs)  (refs, )  )

 __name__ == :
    main()

Implementation Details

• API Endpoint: The skill communicates with the Semantic Scholar Graph API:
  • Base URL: https://api.semanticscholar.org/graph/v1/
• HTTP Client: Uses requests to perform REST calls.
• Authentication / Rate Limits:
  • If S2_API_KEY is set in the environment, requests should include it (typically via an x-api-key header) to obtain higher rate limits.
  • Without an API key, the API may enforce stricter rate limiting.
• Core Operations (as implemented in scripts/client.py):
  • search_papers(query, limit=...): queries the search endpoint and returns a list of matching papers.
  • get_paper_details(paper_id): fetches metadata for a specific paper ID.
  • get_author_details(author_id): fetches metadata for a specific author ID.
  • get_citations(paper_id, method="citations"|"references"): traverses the citation graph by selecting either inbound citations or outbound references.
• Parameters:
  • limit: controls the maximum number of results returned by search.
  • method: must be either "citations" or "references" to select traversal direction.