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在PubScholar公益学术平台自动搜索中文论文、文献或专利，支持智能关键词扩展和结果数量自适应。当用户需要搜索中文学术资源时使用此技能。
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Showing SKILL.md
| name | pubscholar-auto-search |
| description | 在PubScholar公益学术平台自动搜索中文论文、文献或专利，支持智能关键词扩展和结果数量自适应。当用户需要搜索中文学术资源时使用此技能。 |
| version | 1.0.0 |
| author | socienceAI.com |
| license | MIT |
| tags | ["literature-search","pubscholar","chinese-papers","academic-search","automation"] |
| compatibility | Claude 3.5 Sonnet and above |
| metadata | {"domain":"literature-search","methodology":"automated-search","complexity":"intermediate","integration_type":"web-automation","last_updated":"2025-12-28","website":"https://pubscholar.cn","language":"chinese"} |
| allowed-tools | ["python","bash","playwright"] |
在PubScholar公益学术平台（https://pubscholar.cn/）自动搜索中文学术资源，支持智能关键词扩展确保获得足够的文献结果。
Use this skill when the user requests:
When user needs Chinese literature search:
当用户提到以下需求时，使用此技能：
关键词触发:
阶段1: 精准搜索
阶段2: 智能扩展（自动触发）
自动提取每篇文献的：
支持多种格式：
from skills.pubscholar_auto_search.scripts.pubscholar_searcher import SynchronousPubScholarSearcher
# 初始化
searcher = SynchronousPubScholarSearcher(debug=False)
# 执行搜索
results = searcher.search(
keyword="搜索关键词",
auto_expand=True, # 是否智能扩展
min_results=5, # 触发扩展的最小结果数
max_results=50 # 最大返回结果数
)
# 导出结果
searcher.export_to_csv(results, 'output.csv')
参数说明:
keyword: 搜索关键词（必需）auto_expand: 是否启用智能扩展（默认True）min_results: 触发扩展的阈值（默认5）max_results: 最大返回结果数（默认50）{
"search_request": {
"keyword": "搜索关键词（必需）",
"auto_expand": true,
"min_results": 5,
"max_results": 50,
"year_range": {
"start": 2020,
"end": 2024
},
"document_types": ["期刊论文", "学位论文", "会议论文", "专利"]
}
}
{
"search_summary": {
"keyword": "搜索关键词",
"total_results": 25,
"expansion_used": true,
"strategies_applied": ["同义词扩展", "英文翻译"],
"search_time_seconds": 15.3
},
"papers": [
{
"index": 1,
"title": "文献标题",
"authors": ["作者1", "作者2"],
"journal": "期刊名称",
"year": "2024",
"volume": "25",
"issue": "3",
"pages": "45-60",
"abstract": "摘要内容...",
"keywords": ["关键词1", "关键词2"],
"url": "https://pubscholar.cn/...",
"source": "PubScholar"
}
]
}
| 场景 | 原始关键词 | 扩展策略 |
|---|---|---|
| 人工智能 | 人工智能 | AI + 机器学习 + artificial intelligence |
| 数字鸿沟 | 数字鸿沟 | 信息不平等 + digital divide + 数字分化 |
| 社会网络 | 社会网络 | 社交网络 + 关系网络 + social network |
| 深度学习 | 深度学习 | 神经网络 + DL + neural network |
详细文档请查看：
references/USER_GUIDE.md - 完整使用指南references/DEVELOPMENT.md - 开发文档references/API_REFERENCE.md - API参考references/EXTENSION_STRATEGIES.md - 扩展策略详解# 核心依赖
playwright>=1.40.0
beautifulsoup4>=4.12.0
pandas>=2.0.0
# 安装
pip install -r requirements.txt
# 测试
python scripts/test_pubscholar_search.py
# 用户: "在PubScholar搜索关于人工智能的中文论文"
searcher = SynchronousPubScholarSearcher()
results = searcher.search("人工智能")
# 用户: "搜索'社会网络分析 在线社区'，不要扩展"
results = searcher.search("社会网络分析 在线社区", auto_expand=False)
# 用户: "搜索：数字鸿沟、信息不平等、数字不平等"
keywords = ["数字鸿沟", "信息不平等", "数字不平等"]
all_results = [searcher.search(kw) for kw in keywords]
⚠️ 重要声明:
✅ 最佳实践:
版本: 1.0.0 最后更新: 2025-12-28 维护者: SSCI Research Tools