Google Scholar Search

👤 zhoujc11 📦 v1.0.0 ⭐ 4.5 ⬇️ 1.8K 下载
📚 知识管理 免费

📖 技能介绍


name: google-scholar-search description: Academic paper search using Semantic Scholar API. Free API - no key required. Search research papers, get citations, abstracts, authors, and download PDFs. Use when searching academic literature, finding research papers on specific topics, finding citation counts and paper metadata, getting paper abstracts and author information, or looking for papers from specific years or with minimum citations.


Google Scholar Search

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

🤖 AI 评测

这个工具用起来还不错,能快速搜索学术论文,结果来自可靠的学术数据库,不需要注册就能用,还支持按年份、引用数等条件筛选。但它是通过命令行操作的,对普通用户来说不够直观,参数设置有点复杂。另外,它叫"Google Scholar Search"但实际用的是另一个数据库的名字,容易让人混淆。搜索结果只给摘要,没有全文预览,评估论文时不够方便。总体适合有学术需求的用户使用,但界面设计还有改进空间。

📊 多维度评分

适应性4.3
规范性4.5
有效性4.5
可靠性4.5
可信度4.3

📁 包含文件 (6 个)

📄 README.md 3.9 KB
📄 SKILL.md 2.2 KB
📄 _meta.json 140 B
📄 references/API.md 2.1 KB
📄 scripts/search_papers.py 6 KB
📄 test.sh 586 B

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