pubmed-database

davila7/claude-code-templates · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/davila7/claude-code-templates --skill pubmed-database
0 commentsdiscussion
summary

PubMed is the U.S. National Library of Medicine's comprehensive database providing free access to MEDLINE and life sciences literature. Construct advanced queries with Boolean operators, MeSH terms, and field tags, access data programmatically via E-utilities API for systematic reviews and literature analysis.

skill.md

PubMed Database

Overview

PubMed is the U.S. National Library of Medicine's comprehensive database providing free access to MEDLINE and life sciences literature. Construct advanced queries with Boolean operators, MeSH terms, and field tags, access data programmatically via E-utilities API for systematic reviews and literature analysis.

When to Use This Skill

This skill should be used when:

  • Searching for biomedical or life sciences research articles
  • Constructing complex search queries with Boolean operators, field tags, or MeSH terms
  • Conducting systematic literature reviews or meta-analyses
  • Accessing PubMed data programmatically via the E-utilities API
  • Finding articles by specific criteria (author, journal, publication date, article type)
  • Retrieving citation information, abstracts, or full-text articles
  • Working with PMIDs (PubMed IDs) or DOIs
  • Creating automated workflows for literature monitoring or data extraction

Core Capabilities

1. Advanced Search Query Construction

Construct sophisticated PubMed queries using Boolean operators, field tags, and specialized syntax.

Basic Search Strategies:

  • Combine concepts with Boolean operators (AND, OR, NOT)
  • Use field tags to limit searches to specific record parts
  • Employ phrase searching with double quotes for exact matches
  • Apply wildcards for term variations
  • Use proximity searching for terms within specified distances

Example Queries:

# Recent systematic reviews on diabetes treatment
diabetes mellitus[mh] AND treatment[tiab] AND systematic review[pt] AND 2023:2024[dp]

# Clinical trials comparing two drugs
(metformin[nm] OR insulin[nm]) AND diabetes mellitus, type 2[mh] AND randomized controlled trial[pt]

# Author-specific research
smith ja[au] AND cancer[tiab] AND 2023[dp] AND english[la]

When to consult search_syntax.md:

  • Need comprehensive list of available field tags
  • Require detailed explanation of search operators
  • Constructing complex proximity searches
  • Understanding automatic term mapping behavior
  • Need specific syntax for date ranges, wildcards, or special characters

Grep pattern for field tags: \[au\]|\[ti\]|\[ab\]|\[mh\]|\[pt\]|\[dp\]

2. MeSH Terms and Controlled Vocabulary

Use Medical Subject Headings (MeSH) for precise, consistent searching across the biomedical literature.

MeSH Searching:

  • [mh] tag searches MeSH terms with automatic inclusion of narrower terms
  • [majr] tag limits to articles where the topic is the main focus
  • Combine MeSH terms with subheadings for specificity (e.g., diabetes mellitus/therapy[mh])

Common MeSH Subheadings:

  • /diagnosis - Diagnostic methods
  • /drug therapy - Pharmaceutical treatment
  • /epidemiology - Disease patterns and prevalence
  • /etiology - Disease causes
  • /prevention & control - Preventive measures
  • /therapy - Treatment approaches

Example:

# Diabetes therapy with specific focus
diabetes mellitus, type 2[mh]/drug therapy AND cardiovascular diseases[mh]/prevention & control

3. Article Type and Publication Filtering

Filter results by publication type, date, text availability, and other attributes.

Publication Types (use [pt] field tag):

  • Clinical Trial
  • Meta-Analysis
  • Randomized Controlled Trial
  • Review
  • Systematic Review
  • Case Reports
  • Guideline

Date Filtering:

  • Single year: 2024[dp]
  • Date range: 2020:2024[dp]
  • Specific date: 2024/03/15[dp]

Text Availability:

  • Free full text: Add AND free full text[sb] to query
  • Has abstract: Add AND hasabstract[text] to query

Example:

# Recent free full-text RCTs on hypertension
hypertension[mh] AND randomized controlled trial[pt] AND 2023:2024[dp] AND free full text[sb]

4. Programmatic Access via E-utilities API

Access PubMed data programmatically using the NCBI E-utilities REST API for automation and bulk operations.

Core API Endpoints:

  1. ESearch - Search database and retrieve PMIDs
  2. EFetch - Download full records in various formats
  3. ESummary - Get document summaries
  4. EPost - Upload UIDs for batch processing
  5. ELink - Find related articles and linked data

Basic Workflow:

import requests

# Step 1: Search for articles
base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/"
search_url = f"{base_url}esearch.fcgi"
params = {
    "db": "pubmed",
    "term": "diabetes[tiab] AND 2024[dp]",
    "retmax": 100,
    "retmode": "json",
    "api_key": "YOUR_API_KEY"  # Optional but recommended
}
response = requests.get(search_url, params=params)
pmids = response.json()["esearchresult"]["idlist"]

# Step 2: Fetch article details
fetch_url = f"{base_url}efetch.fcgi"
params = {
    "db": "pubmed",
    "id": ",".join(pmids),
    "rettype": "abstract",
    "retmode": "text",
    "api_key": "YOUR_API_KEY"
}
response = requests.get(fetch_url, params=params)
abstracts = response.text

Rate Limits:

  • Without API key: 3 requests/second
  • With API key: 10 requests/second
  • Always include User-Agent header

Best Practices:

  • Use history server (usehistory=y) for large result sets
  • Implement batch operations via EPost for multiple UIDs
  • Cache results locally to minimize redundant calls
  • Respect rate limits to avoid service disruption

When to consult api_reference.md:

  • Need detailed endpoint documentation
  • Require parameter specifications for each E-utility
  • Constructing batch operations or history server workflows
  • Understanding response formats (XML, JSON, text)
  • Troubleshooting API errors or rate limit issues

Grep pattern for API endpoints: esearch|efetch|esummary|epost|elink|einfo

5. Citation Matching and Article Retrieval

Find articles using partial citation information or specific identifiers.

By Identifier:

# By PMID
12345678[pmid]

# By DOI
10.1056/NEJMoa123456[doi]

# By PMC ID
PMC123456[pmc]

Citation Matching (via ECitMatch API): Use journal name, year, volume, page, and author to find PMIDs:

Format: journal|year|volume|page|author|key|
Example: Science|2008|320|5880|1185|key1|

By Author and Metadata:

# First author with year and topic
smith ja[1au] AND 2023[dp] AND cancer[tiab]

# Journal, volume, and page
nature[ta] AND 2024[dp] AND 456[vi] AND 123-130[pg]

6. Systematic Literature Reviews

Conduct comprehensive literature searches for systematic reviews and meta-analyses.

PICO Framework (Population, Intervention, Comparison, Outcome): Structure clinical research questions systematically:

# Example: Diabetes treatment effectiveness
# P: diabetes mellitus, type 2[mh]
# I: metformin[nm]
# C: lifestyle modification[tiab]
# O: glycemic control[tiab]

diabetes mellitus, type 2[mh] AND
(metformin[nm] OR lifestyle modification[tiab]) AND
glycemic control[tiab] AND
randomized controlled trial[pt]

Comprehensive Search Strategy:

# Include multiple synonyms and MeSH terms
(disease name[tiab] OR disease name[mh] OR synonym[tiab]) AND
(treatment[tiab] OR therapy[tiab] OR intervention[tiab]) AND
(systematic review[pt] OR meta-analysis[pt] OR randomized controlled trial[pt]) AND
2020:2024[dp] AND
english[la]

Search Refinement:

  1. Start broad, review results
  2. Add specificity with field tags
  3. Apply date and publication type filters
  4. Use Advanced Search to view query translation
  5. Combine search history for complex queries

When to consult common_queries.md:

  • Need example queries for specific disease types or research areas
  • Require templates for different study designs
  • Looking for population-specific query patterns (pediatric, geriatric, etc.)
  • Constructing methodology-specific searches
  • Need quality filters or best practice patterns

Grep pattern for query examples: diabetes|cancer|cardiovascular|clinical trial|systematic review

7. Search History and Saved Searches

Use PubMed's search history and My NCBI features for efficient research workflows.

Search History (via Advanced Search):

  • Maintains up to 100 searches
  • Expires after 8 hours of inactivity
  • Combine previous searches using # references
  • Preview result counts before executing

Example:

#1: diabetes mellitus[mh]
#2: cardiovascular diseases[mh]
#3: #1 AND #2 AND risk factors[tiab]

My NCBI Features:

  • Save searches indefinitely
  • Set up email alerts for new matching articles
  • Create collections of saved articles
  • Organize research by project or topic

RSS Feeds: Create RSS feeds for any search to monitor new publications in your area of interest.

8. Related Articles and Citation Discovery

Find related research and explore citation networks.

Similar Articles Feature: Every PubMed article includes pre-calculated related articles based on:

  • Title and abstract similarity
  • MeSH term overlap
  • Weighted algorithmic matching

ELink for Related Data:

# Find related articles programmatically
elink.fcgi?dbfrom=pubmed&db=pubmed&id=PMID&cmd=neighbor

Citation Links:

  • LinkOut to full text from publishers
  • Links to PubMed Central free articles
  • Connections to related NCBI databases (GenBank, ClinicalTrials.gov, etc.)

9. Export and Citation Management

Export search results in various formats for citation management and further analysis.

Export Formats:

  • .nbib files for reference managers (Zotero, Mendeley, EndNote)
  • AMA, MLA, APA, NLM citation styles
  • CSV for data analysis
  • XML for programmatic processing

Clipboard and Collections:

  • Clipboard: Temporary storage for up to 500 items (8-hour expiration)
  • Collections: Permanent storage via My NCBI account

Batch Export via API:

# Export citations in MEDLINE format
efetch.fcgi?db=pubmed&id=PMID1,PMID2&rettype=medline&retmode=text

Working with Reference Files

This skill includes three comprehensive reference files in the references/ directory:

references/api_reference.md

Complete E-utilities API documentation including all nine endpoints, parameters, response formats, and best practices. Consult when:

  • Implementing programmatic PubMed access
  • Constructing API requests
  • Understanding rate limits and authentication
  • Working with large datasets via history server
  • Troubleshooting API errors

references/search_syntax.md

Detailed guide to PubMed search syntax including field tags, Boolean operators, wildcards, and special characters. Consult when:

  • Constructing complex search queries
  • Understanding automatic term mapping
  • Using advanced search features (proximity, wildcards)
  • Applying filters and limits
  • Troubleshooting unexpected search results

references/common_queries.md

Extensive collection of example queries for various research scenarios, disease types, and methodologies. Consult when:

  • Starting a new literature search
  • Need templates for specific research areas
  • Looking for best practice query patterns
  • Conducting systematic reviews
  • Searching for specific study designs or populations

Reference Loading Strategy: Load reference files into context as needed based on the specific task. For brief queries or basic searches, the information in this SKILL.md may be sufficient. For complex operations, consult the appropriate reference file.

Common Workflows

Workflow 1: Basic Literature Search

  1. Identify key concepts and synonyms
  2. Construct query with Boolean operators and field tags
  3. Review initial results and refine query
  4. Apply filters (date, article type, language)
  5. Export results for analysis

Workflow 2: Systematic Review Search

  1. Define research question using PICO framework
  2. Identify all relevant MeSH terms and synonyms
  3. Construct comprehensive search strategy
  4. Search multiple databases (include PubMed)
  5. Document search strategy and date
  6. Export results for screening and review

Workflow 3: Programmatic Data Extraction

  1. Design search query and test in web interface
  2. Implement search using ESearch API
  3. Use history server for large result sets
  4. Retrieve detailed records with EFetch
  5. Parse XML/JSON responses
  6. Store data locally with caching
  7. Implement rate limiting and error handling

Workflow 4: Citation Discovery

  1. Start with known relevant article
  2. Use Similar Articles to find related work
  3. Check citing articles (when available)
  4. Explore MeSH terms from relevant articles
  5. Construct new searches based on discoveries
  6. Use ELink to find related database entries

Workflow 5: Ongoing Literature Monitoring

  1. Construct comprehensive search query
  2. Test and refine query for precision
  3. Save search to My NCBI account
  4. Set up email alerts for new matches
  5. Create RSS feed for feed reader monitoring
  6. Review new articles regularly

Tips and Best Practices

Search Strategy

  • Start broad, then narrow with field tags and filters
  • Include synonyms and MeSH terms for comprehensive coverage
  • Use quotation marks for exact phrases
  • Check Search Details in Advanced Search to verify query translation
  • Combine multiple searches using search history

API Usage

  • Obtain API key for higher rate limits (10 req/sec vs 3 req/sec)
  • Use history server for result sets > 500 articles
  • Implement exponential backoff for rate limit handling
  • Cache results locally to minimize redundant requests
  • Always include descriptive User-Agent header

Quality Filtering

  • Prefer systematic reviews and meta-analyses for synthesized evidence
  • Use publication type filters to find specific study designs
  • Filter by date for most recent research
  • Apply language filters as appropriate
  • Use free full text filter for immediate access

Citation Management

  • Export early and often to avoid losing search results
  • Use .nbib format for compatibility with most reference managers
  • Create My NCBI account for permanent collections
  • Document search strategies for reproducibility
  • Use Collections to organize research by project

Limitations and Considerations

Database Coverage

  • Primarily biomedical and life sciences literature
  • Pre-1975 articles often lack abstracts
  • Full author names available from 2002 forward
  • Non-English abstracts available but may default to English display

Search Limitations

  • Display limited to 10,000 results maximum
  • Search history expires after 8 hours of inactivity
  • Clipboard holds max 500 items with 8-hour expiration
  • Automatic term mapping may produce unexpected results

API Consi

how to use pubmed-database

How to use pubmed-database on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pubmed-database
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill pubmed-database

The skills CLI fetches pubmed-database from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pubmed-database

Reload or restart Cursor to activate pubmed-database. Access the skill through slash commands (e.g., /pubmed-database) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.773 reviews
  • Aditi Nasser· Dec 28, 2024

    pubmed-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Isabella Khanna· Dec 24, 2024

    Keeps context tight: pubmed-database is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Daniel Anderson· Dec 16, 2024

    pubmed-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Zaid Li· Dec 12, 2024

    Solid pick for teams standardizing on skills: pubmed-database is focused, and the summary matches what you get after install.

  • Charlotte Liu· Dec 4, 2024

    pubmed-database fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Charlotte Farah· Nov 23, 2024

    Registry listing for pubmed-database matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zaid Gonzalez· Nov 19, 2024

    Solid pick for teams standardizing on skills: pubmed-database is focused, and the summary matches what you get after install.

  • Isabella Tandon· Nov 15, 2024

    pubmed-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Isabella Malhotra· Nov 7, 2024

    Solid pick for teams standardizing on skills: pubmed-database is focused, and the summary matches what you get after install.

  • Charlotte Nasser· Nov 3, 2024

    pubmed-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

showing 1-10 of 73

1 / 8