據 AlphaMoat 統計,截至 2026-09,PubMed Search 累計下載 4,459 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,171 位,在「知識管理」分類(442 個)中排名第 207 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 61 | 1973 | - | - |
| SkillHub ↗ | 414 | 4459 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
支援關鍵詞及作者、期刊、日期篩選、摘要審讀、論文分析和嘗試獲取開放獲取 PDF。基礎檢索使用 PubMed E-utilities,無強制認證要求;可選 API 配置影響訪問,分析結果應對照原始論文核實。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 4459 | — | 2 |
| 2026-08 | 3098 | +73.6% | 2 |
| 2026-07 | 1785 | — | - |
| 2026-05 | 1493 | — | 2 |
| 2026-03 | 892 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: PubMed-Search description: AI-powered tool for searching and analyzing PubMed biomedical literature --- You are a professional biomedical literature search assistant, helping users search, access, and analyze PubMed articles. ## Core Features ### Article Search
- Search PubMed articles using keywords
- Advanced search with multiple filters (title, author, journal, date range)
- Fast access to comprehensive paper metadata
### Metadata Retrieval
- Fetch detailed metadata for specific papers using PMID
- Extract title, authors, abstract, journal, publication date
- Support for batch retrieval
### Paper Analysis
- Deep analysis of PubMed articles
- Research background and significance
- Methodology overview and key findings
- Limitations and future research directions
### Full-Text Access
- Attempt to download full-text PDF content
- Check open access availability via PubMed Central (PMC)
- Provide direct links to articles
## Installation
### Prerequisites
- Python 3.8+
- pip package manager
### Setup Steps
1. **Install Python dependencies** (choose one method):
**Method 1: Using uv (Recommended - Fastest)**
```bash
# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh
# Create virtual environment and install dependencies
cd /path/to/pubmed-search-skill
uv venv
source .venv/bin/activate # Linux/macOS
# or .venv\Scripts\activate # Windows
uv pip install -r requirements.txt
```
**Method 2: Using conda (Best for scientific/research users)**
```bash
cd /path/to/pubmed-search-skill
conda create -n pubmed-search python=3.11 -y
conda activate pubmed-search
pip install -r requirements.txt
```
**Method 3: Using pip directly (Built-in, no extra installation)**
```bash
cd /path/to/pubmed-search-skill
pip install -r requirements.txt
```
2. **Configure API credentials** (optional for basic search, required for PDF download):
```bash
# Copy example configuration
cp .env.example .env
# Edit .env and configure optional settings
# Most features work without API keys - uses free PubMed E-utilities API
```
### Verify Installation
```bash
python pubmed_search.py --help
```
## How to Use
When users request literature search or analysis:
1. **Understand requirements**: Ask what research topic or papers to search for
2. **Choose method**:
- Simple keyword search for quick results
- Advanced search with specific filters
- Deep analysis for comprehensive understanding
3. **Execute search**:
```bash
python pubmed_search.py search --keywords "CRISPR gene editing" --results 10
```
4. **Present results**: Display article metadata and ask if further analysis needed
## Usage Examples
### Basic Keyword Search
```bash
# Search for articles by keywords
python pubmed_search.py search --keywords "COVID-19 vaccine efficacy" --results 10
```
### Advanced Search
```bash
# Search with multiple filters
python pubmed_search.py search --term "cancer" --author "Smith" --journal "Nature" --start-date "2020" --end-date "2023" --results 20
```
### Get Article Metadata
```bash
# Fetch detailed metadata for a specific paper
python pubmed_search.py metadata --pmid "12345678"
```
### Deep Paper Analysis
```bash
# Perform comprehensive analysis of a paper
python pubmed_search.py analyze --pmid "12345678" --output analysis.md
```
### Download Full-Text PDF
```bash
# Attempt to download open access PDF
python pubmed_search.py download --pmid "12345678" --output ./papers/
```
### Batch Search
```bash
# Search and save results to file
python pubmed_search.py search --keywords "Alzheimer disease" --results 50 --output results.json
```
## Configuration Requirements
### Environment Variables (Optional)
The skill uses the free PubMed E-utilities API, which doesn't require authentication for basic usage. However, you can configure these optional settings:
- `PUBMED_API_KEY`: PubMed API key for higher rate limits (get from: https://www.ncbi.nlm.nih.gov/account/)
- `PUBMED_EMAIL`: Email for API requests (required when using API key)
- `PUBMED_TOOL`: Tool name for API identification (default: pubmed-search-skill)
### Rate Limits
- **Without API key**: 3 requests per second
- **With API key**: Up to 10 requests per second
Get your free API key at: https://www.ncbi.nlm.nih.gov/account/
## Best Practices
1. Use specific keywords for better results
2. Apply filters (author, journal, date) to narrow down searches
3. Review abstracts before requesting full analysis
4. Check open access availability before downloading PDFs
5. Cite original papers when using retrieved information
## Output Formats
### Console Output
Human-readable format with key article information
### JSON Format
Machine-readable format for further processing:
```json
[
{
"PMID": "12345678",
"Title": "Article Title",
"Authors": "Author1, Author2",
"Journal": "Journal Name",
"Publication Date": "2023",
"Abstract": "Abstract text..."
}
]
```
### Markdown Format
Formatted output for documentation:
```markdown
# Article Title
**Authors**: Author1, Author2
**Journal**: Journal Name (2023)
**PMID**: 12345678
## Abstract
Abstract text...
```
## Notes
- This tool uses the free PubMed E-utilities API
- PDF downloads are only available for open access articles
- Always verify information from original sources
- Respect copyright when using downloaded articles
- Rate limits apply - consider getting an API key for heavy usage
把長文字、文件與網頁內容壓縮成要點和關鍵詞的摘要工具。
透過 IMA OpenAPI 管理筆記與知識庫內容。
規定如何為網頁請求選擇合適工具的必讀指引。
呼叫百度 AI 搜尋介面做網頁檢索的技能。
用 uvx 直接呼叫 markitdown,把各類檔案轉成 Markdown。
面向 OpenClaw 的預設網頁搜尋,即時檢索多個引擎。
用 DuckDuckGo 介面做網頁、新聞、圖片與影片檢索的技能。
檢索並發現可用 OpenClaw 技能的技能。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。