explainx.ainewsletter3.4k
Scienceofficial

literature-search-europepmc▌

google-deepmind/science-skills · updated Jun 4, 2026

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

$npx skills add https://github.com/google-deepmind/science-skills --skill literature-search-europepmc
0 commentsdiscussion
summary

### Literature Search Europepmc

  • ›name: "literature-search-europepmc"
  • ›description: "Search Europe PMC for scientific literature and download open-access full texts and PDFs. Retrieve full-text XML/plain text by PMCID, get citation lists and bibliography."
skill.md
name
literature-search-europepmc
description
> Search Europe PMC for scientific literature and download open-access full texts and PDFs. Retrieve full-text XML/plain text by PMCID, get citation lists and bibliography.

Europe PMC Database

A skill for searching, downloading, and exploring open-access papers from Europe PMC — a comprehensive, free life-science literature database with over 43 million abstracts and 9 million full-text articles.

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://europepmc.org/ and to always check the license of the papers retrieved by the skill for any restrictions, then (2) create the file recording the notification text and timestamp.

Core Rules

  • Open Access Only: This skill exclusively searches open-access content. The script automatically appends OPEN_ACCESS:y to every search query. Do NOT remove or override this filter.
  • NEVER run python3 or python3 -c directly: the system Python does not necessarily have all key dependencies. Do not attempt to pip install or create new venvs.
  • Use the Wrapper: ALWAYS use the provided script rather than calling the API directly. The script handles rate limiting (1 req/s) and errors.
  • Output Files: All subcommands require --output to write results to a file. Read the output file separately to avoid context overflow.
  • List Sources. If this skill is used, ensure this is mentioned in the output AND list the URLs of all papers that were used in producing the output.

Utility Scripts

All commands are subcommands of scripts/europepmc_api.py. Rate limiting and retries are handled automatically.

1. Search (search)

Search Europe PMC by query. Supports DOI lookup, keyword search, author search, PMID lookup, and the full Europe PMC search syntax.

# Look up a paper by DOI
uv run scripts/europepmc_api.py search "DOI:10.1038/s41586-021-03819-2" --output result.json

# Keyword search
uv run scripts/europepmc_api.py search "CRISPR cancer" --max_results 5 --output results.json

# Author search
uv run scripts/europepmc_api.py search "AUTH:Jumper J" --max_results 10 --output results.json

# PMID lookup
uv run scripts/europepmc_api.py search "EXT_ID:34265844 AND SRC:MED" --output result.json

# Sorted by citations
uv run scripts/europepmc_api.py search "machine learning" \
  --sort "CITED desc" --max_results 20 --output results.json

Arguments:

  • query (str, required) — search query using Europe PMC syntax
  • --output (str, required) — output JSON file path
  • --max_results (int, default 10) — maximum results per page (max 1000)
  • --result_type (str, default core) — core (full metadata) or lite
  • --cursor (str, default *) — cursor mark for pagination; pass the nextCursorMark value from a previous response to get the next page
  • --sort (str) — sort order, e.g. CITED desc, P_PDATE_D desc (publication date descending), P_PDATE_D asc

Output: JSON file with three fields:

  • hitCount (int) — total number of matching articles
  • nextCursorMark (str) — cursor for next page; empty string if no more pages
  • results (list) — array of article metadata objects

Search Syntax Quick Reference:

  • DOI:10.xxxx/yyyy — look up by DOI
  • EXT_ID:12345678 AND SRC:MED — look up by PMID
  • AUTH:surname initials — author search
  • TITLE:keyword — search in title only
  • JOURNAL:name — search by journal
  • PUB_YEAR:2024 or (FIRST_PDATE:[2023-01-01 TO 2023-12-31]) — date filter
  • HAS_FT:y — restrict to articles with full text in Europe PMC
  • Boolean operators: AND, OR, NOT

Note: OPEN_ACCESS:y is automatically appended to all queries. You do not need to add it manually.

2. Download PDF (download_pdf)

Download an open-access PDF from Europe PMC by PMCID.

uv run scripts/europepmc_api.py download_pdf PMC8371605 --output alphafold.pdf

Arguments:

  • pmcid (str, required) — PubMed Central ID (e.g., PMC8371605)
  • --output (str, required) — filepath to save the PDF

Output: Saves the PDF to the specified file. Exits with an error if the PMCID is not found or the response is not a valid PDF. Whenever you download a PDF, check the pdf downloaded is not empty or corrupted.

3. Get Full Text (get_fulltext)

Retrieve the full text of an open-access article and save to a file. Returns plain text (XML tags stripped) by default, or raw XML with --format xml.

# Get plain text (default)
uv run scripts/europepmc_api.py get_fulltext PMC8371605 --output fulltext.txt

# Get raw XML
uv run scripts/europepmc_api.py get_fulltext PMC8371605 --format xml --output fulltext.xml

Arguments:

  • pmcid (str, required) — PubMed Central ID
  • --output (str, required) — output file path
  • --format (str, default text) — text (plain text) or xml (raw JATS XML)

Output: Full text written to the specified file. Exits with an error if the article is not in the Europe PMC open-access subset.

Important: Only articles in the PMC Open Access Subset have full text available. If retrieval fails, use search to check the isOpenAccess field and fall back to the abstract.

4. Get Citations (get_citations)

Retrieve articles that cite a given paper.

# Get citations for the AlphaFold paper (PMID 34265844)
uv run scripts/europepmc_api.py get_citations MED 34265844 \
  --page_size 25 --output citations.json

Arguments:

  • source (str, required) — source database: MED (PubMed), PMC, PPR (preprints), PAT (patents)
  • article_id (str, required) — article ID in the source database
  • --output (str, required) — output JSON file path
  • --page (int, default 1) — page number
  • --page_size (int, default 25) — results per page

Output: JSON file with hitCount and citations array.

5. Get References (get_references)

Retrieve the reference list (bibliography) of a given paper.

# Get references from the AlphaFold paper
uv run scripts/europepmc_api.py get_references MED 34265844 \
  --page_size 100 --output references.json

Arguments:

  • source (str, required) — source database: MED, PMC, PPR, PAT
  • article_id (str, required) — article ID in the source database
  • --output (str, required) — output JSON file path
  • --page (int, default 1) — page number
  • --page_size (int, default 25) — results per page

Output: JSON file with hitCount and references array.

Common Workflows

DOI to PDF

# Step 1: Search for the PMCID
uv run scripts/europepmc_api.py search "DOI:10.1038/s41586-021-03819-2" --output result.json
PMCID=$(jq -r '.results[0].pmcid // empty' result.json)

# Step 2: Download the PDF
uv run scripts/europepmc_api.py download_pdf "$PMCID" --output paper.pdf

PMID to Full Text

# Step 1: Find the PMCID from a PMID
uv run scripts/europepmc_api.py search "EXT_ID:34265844 AND SRC:MED" --output result.json
PMCID=$(jq -r '.results[0].pmcid // empty' result.json)

# Step 2: Get the full text
uv run scripts/europepmc_api.py get_fulltext "$PMCID" --output fulltext.txt

Citation Graph Traversal

# Find what papers cite a landmark study, then check their references
uv run scripts/europepmc_api.py get_citations MED 34265844 --page_size 50 --output citing.json
# Parse a cited paper's PMID and explore its references
uv run scripts/europepmc_api.py get_references MED <CITING_PMID> --output refs.json

Search with Pagination

# First page
uv run scripts/europepmc_api.py search "CRISPR" --max_results 100 --output page1.json
# Extract cursor for next page
CURSOR=$(jq -r '.nextCursorMark // empty' page1.json)
# Next page
uv run scripts/europepmc_api.py search "CRISPR" --max_results 100 --cursor "$CURSOR" --output page2.json
how to use literature-search-europepmc

How to use literature-search-europepmc 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 literature-search-europepmc
2

Execute installation command

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

$npx skills add https://github.com/google-deepmind/science-skills --skill literature-search-europepmc

The skills CLI fetches literature-search-europepmc from GitHub repository google-deepmind/science-skills 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/literature-search-europepmc

Reload or restart Cursor to activate literature-search-europepmc. Access the skill through slash commands (e.g., /literature-search-europepmc) 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.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client with skill support
  • ›Clear understanding of task or problem to solve
  • ›Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • ⚠Expecting perfect results without iteration
  • ⚠Not providing enough context in prompts
  • ⚠Using skill for tasks outside its intended scope
  • ⚠Accepting outputs without review and validation

Best Practices▌

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • −Don't use without understanding skill limitations
  • −Don't skip validation of outputs
  • −Don't share sensitive information in prompts
  • −Don't expect skill to replace human judgment

💡 Pro Tips

  • ★Be specific about desired format and style
  • ★Ask for multiple options to choose from
  • ★Request explanations to understand reasoning
  • ★Combine AI efficiency with human expertise

When to Use This▌

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path▌

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

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

Ratings

4.6★★★★★63 reviews
  • ★★★★★Layla Dixit· Dec 24, 2024

    Useful defaults in literature-search-europepmc — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Ishan Verma· Dec 20, 2024

    I recommend literature-search-europepmc for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Kofi Ghosh· Dec 12, 2024

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

  • ★★★★★Layla Desai· Dec 8, 2024

    We added literature-search-europepmc from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Dhruvi Jain· Dec 4, 2024

    literature-search-europepmc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Kofi Bansal· Dec 4, 2024

    literature-search-europepmc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Sophia Singh· Nov 27, 2024

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

  • ★★★★★Oshnikdeep· Nov 23, 2024

    literature-search-europepmc is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Meera Dixit· Nov 23, 2024

    literature-search-europepmc is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Ira Robinson· Nov 15, 2024

    literature-search-europepmc has been reliable in day-to-day use. Documentation quality is above average for community skills.

showing 1-10 of 63

1 / 7