Google Scholar Search

Academic paper search using Semantic Scholar API. Free API - no key required. Search research papers, get citations, abstracts, authors, and download PDFs. U...

Security Scan

The skill's code and instructions match its stated purpose of querying the Semantic Scholar Graph API; it makes ordinary outbound API requests, requests no credentials, and does not perform unexpected file or credential access.

Purpose & Capability

The name/description say 'Semantic Scholar' search and the included Python script calls api.semanticscholar.org with fields consistent with that API. No unrelated services, binaries, or credentials are requested.

Instruction Scope

SKILL.md simply instructs running the provided script with query and filter flags. The script only constructs HTTP requests to the Semantic Scholar API and formats results; it does not read unrelated files, access system credentials, or exfiltrate data to unknown endpoints.

Install Mechanism

There is no install spec; this is instruction+source-only. All code is present in the bundle and there are no downloads, package installs, or extraction from external URLs.

Credentials

The skill requires no environment variables or credentials. It only performs outbound HTTPS requests to api.semanticscholar.org and returns metadata and PDF links; it does not attempt to use or store secrets.

Persistence & Privilege

always is false and the skill does not modify other skills or system configuration. It has no special persistence or elevated privileges.

Assessment

This skill appears coherent and low-risk: it queries the official Semantic Scholar API, needs no API keys, and only returns metadata and PDF links. Before running, quickly review the included Python script yourself (or run it in an isolated environment) to confirm inbound/outbound network policies are acceptable. Note that openAccessPdf values are links to external hosts—treat downloaded PDFs like any external file (scan before opening). Also be aware the package has no listed homepage/maintainer; if you require stronger provenance, ask the publisher for origin or prefer a signed/official distribution.

Search academic papers using the free Semantic Scholar API. No API key required.

Quick Start

Basic search:

python3 {baseDir}/scripts/search_papers.py "machine learning transformers"

Search with filters:

python3 {baseDir}/scripts/search_papers.py "deep learning" --limit 5 --year 2020-2023 --min-citations 10

Search Options

• --limit N: Number of results (default: 10, max: 100)
• --year YYYY-YYYY: Filter by year range (e.g., "2020-2023" or "2023")
• --min-citations N: Minimum citation count
• --json: Output in JSON format for machine processing

Get Paper Details

Retrieve detailed information about a specific paper:

python3 {baseDir}/scripts/search_papers.py --details <paper-id>

Returned Data

Each paper includes:

• title: Paper title
• authors: List of authors with names
• year: Publication year
• venue: Journal or conference name
• citationCount: Number of citations
• abstract: Paper abstract
• url: Link to Semantic Scholar page
• openAccessPdf: Direct PDF link if available
• paperId: Unique Semantic Scholar ID (for details lookup)

Examples

Search for recent AI papers:

python3 {baseDir}/scripts/search_papers.py "large language models" --year 2022-2024 --limit 10

Find highly cited papers on a topic:

python3 {baseDir}/scripts/search_papers.py "quantum computing" --min-citations 50 --limit 10

Get JSON output for integration:

python3 {baseDir}/scripts/search_papers.py "neural networks" --json --limit 20

Tips

• Use specific keywords for better results
• Filter by year to get recent research
• Use --min-citations to find influential papers
• The API is free and requires no authentication
• For complex queries, try multiple related terms