Menu
AI-powered tool for searching and analyzing PubMed biomedical literature
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
Generates beautiful, consistent Preline Theme CSS files. Agent interprets user request, runs build script, delivers complete CSS.
Extract clinical trial data from pharmaceutical conference websites or PDF documents. Use when user provides a URL or PDF file containing innovative drug clinical trial data and needs structured extraction of: drug name, manufacturer, indication, clinical phase, trial name, conference, efficacy and safety data (presented as tables), and markdown output to "药品名称@适应症.md" file.
Use this skill when a clinician, practice manager, or healthcare developer needs to draft, structure, or retrieve clinical documentation — including SOAP notes, referral letters, prior authorization forms, discharge summaries, and care plan narratives. Connects to FHIR R4-compliant APIs (Epic, Cerner, Azure Health Data Services, HAPI FHIR) to pull structured patient data and generate documentation drafts. Also supports manual input when no EHR connection is available. DO NOT use for direct diagnosis, prescribing decisions, or any task requiring a licensed clinical judgment — this skill assists with documentation only.
Search clinical trial databases similar to ClinicalTrials.gov. Use this skill whenever the user asks about clinical trials, drug trials, indications, targets, drug names, trial phases, NCT IDs, enrollment, or recruitment. Automatically parses natural language questions into structured query parameters and calls the backend API to return matching trial records. Trigger words include: clinical trial, NCT, drug development, indication, target, phase, enrollment, recruitment, sponsor, cohort, arm, endpoint, efficacy, safety data.
Analyze ECG signals via heartvoice (心之声) API — single-lead and 12-lead. Automatically selects endpoint based on user intent and responds in the user's language. Use when user mentions ECG, 心电图, 心电分析, 单导联, 十二导联, 1-lead, 12-lead, heart rhythm, arrhythmia, QRS, QT interval, signal quality, or asks to analyze an ECG JSON file.
醫療文檔處理技能 - 病歷摘要、報告分析、醫學文獻整理。適用於醫生、醫療專業人員。觸發詞：病歷、醫療報告、醫學文獻、clinical notes、medical document、病歷摘要、出院小結、門診記錄。
| 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.
Install Python dependencies (choose one method):
Method 1: Using uv (Recommended - Fastest)
# 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)
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)
cd /path/to/pubmed-search-skill
pip install -r requirements.txt
Configure API credentials (optional for basic search, required for PDF download):
# 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
python pubmed_search.py --help
When users request literature search or analysis:
python pubmed_search.py search --keywords "CRISPR gene editing" --results 10
# Search for articles by keywords
python pubmed_search.py search --keywords "COVID-19 vaccine efficacy" --results 10
# Search with multiple filters
python pubmed_search.py search --term "cancer" --author "Smith" --journal "Nature" --start-date "2020" --end-date "2023" --results 20
# Fetch detailed metadata for a specific paper
python pubmed_search.py metadata --pmid "12345678"
# Perform comprehensive analysis of a paper
python pubmed_search.py analyze --pmid "12345678" --output analysis.md
# Attempt to download open access PDF
python pubmed_search.py download --pmid "12345678" --output ./papers/
# Search and save results to file
python pubmed_search.py search --keywords "Alzheimer disease" --results 50 --output results.json
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)Get your free API key at: https://www.ncbi.nlm.nih.gov/account/
Human-readable format with key article information
Machine-readable format for further processing:
[
{
"PMID": "12345678",
"Title": "Article Title",
"Authors": "Author1, Author2",
"Journal": "Journal Name",
"Publication Date": "2023",
"Abstract": "Abstract text..."
}
]
Formatted output for documentation:
# Article Title
**Authors**: Author1, Author2
**Journal**: Journal Name (2023)
**PMID**: 12345678
## Abstract
Abstract text...