Skills pubmed-database

📦

pubmed-database

Name: pubmed-database
Author: davila7

Content revision r2 Safe 🌐 Network access🔑 Env variables⚙️ External commands

Search PubMed and Build Reproducible Queries

Biomedical researchers need precise, reproducible searches across a large literature database. This skill builds PubMed queries and guides E-utilities retrieval workflows.

Supports: Claude Codex Code(CC)

📊 76 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "pubmed-database" from https://skillstore.io/skills/davila7-pubmed-database.md and its manifest at https://skillstore.io/api/skills/davila7-pubmed-database/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/davila7-pubmed-database.md Signed manifest GET /api/skills/davila7-pubmed-database/manifest Signed lockfile GET /api/skills/davila7-pubmed-database/lockfile

Test it

Using "pubmed-database". Find recent randomized trials about exercise for type 2 diabetes.

Expected outcome:

Concepts: type 2 diabetes, exercise therapy, randomized controlled trials.
Suggested search: diabetes mellitus, type 2[mh] AND exercise therapy[mh] AND randomized controlled trial[pt] AND 2022:2026[dp].
Review Search Details in PubMed and add relevant free-text synonyms before final use.

Using "pubmed-database". Plan retrieval of 2,000 PubMed records for an evidence dataset.

Expected outcome:

Run ESearch with history enabled and retain the returned history identifiers.
Retrieve records through EFetch in bounded batches using the history identifiers.
Apply NCBI rate limits, a descriptive User-Agent, retries, and local caching.

Using "pubmed-database". Locate an article from a partial citation.

Expected outcome:

Use ECitMatch when journal, year, volume, page, and author are available. Otherwise combine known metadata with PubMed field tags.

Security Audit

Safe

v9 • 7/23/2026 Open versioned report

The official NCBI URLs and requests are expected for a PubMed API skill, and every API key occurrence is a non-secret placeholder. The command-execution and reconnaissance alerts are Markdown formatting or ordinary guidance; no prompt injection, credential theft, or harmful intent was found.

Files scanned

1,645

Lines analyzed

Review items

False positives ignored

Risk Factors

🌐 Network access (6)

references/api_reference.md:8 SKILL.md:134 SKILL.md:146 SKILL.md:125 SKILL.md:450 SKILL.md:451

🔑 Env variables (17)

⚙️ External commands (32)

No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.

Audited by: codex View Audit History →

Share & cite this report

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Open versioned report

Copy report link

https://skillstore.io/skills/davila7-pubmed-database/audits/9?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

davila7. (2026). pubmed-database security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-pubmed-database/audits/9

BibTeX citation

@techreport{davila7-davila7-pubmed-database-2026,
  author = {davila7},
  title = {pubmed-database security audit report (audit version 9)},
  institution = {Skillstore},
  year = {2026},
  number = {9},
  url = {https://skillstore.io/skills/davila7-pubmed-database/audits/9},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "pubmed-database security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
  - name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-pubmed-database/audits/9"
identifiers:
  - type: other
    value: "skillstore:davila7-pubmed-database:audit:9"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

davila7 Recommended Current

davila7-pubmed-database

Skillstore Score 76

Evidence Confidence High

Skillstore usage 13

Updated

2026-08-21

K-Dense-AI

k-dense-ai-pubmed-database

Skillstore Score 71

Evidence Confidence High

Skillstore usage 34

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Design a systematic search

Translate a clinical question into documented MeSH, synonym, and study-design search blocks.

Retrieve research records

Search PubMed and fetch abstracts or structured citations through an E-utilities workflow.

Automate literature monitoring

Plan repeatable searches, batching, caching, exports, and alerts for an evidence pipeline.

Try These Prompts

Create a basic PubMed query

Create a PubMed query for [topic]. Include common synonyms, one relevant MeSH term, and a date range of [years].

Refine results by study type

Refine this PubMed query for [study type], [population], [language], and [date range]: [current query]. Explain each added field tag.

Build a PICO search strategy

Build a reproducible PubMed strategy for this PICO question: [question]. Separate concepts, synonyms, MeSH terms, and final Boolean combinations.

Plan a batched E-utilities workflow

Design an E-utilities workflow for [query] and approximately [record count] records. Cover ESearch, history, EFetch batching, rate limits, caching, and errors.

Best Practices

Combine MeSH terms with free-text synonyms, then verify PubMed query translation before relying on results.
Document the exact query, search date, filters, result count, and export format for reproducibility.
Respect NCBI rate limits and use history, batching, caching, retries, and a descriptive User-Agent.

Avoid

Do not treat one narrow keyword query as a complete systematic search.
Do not place a real API key directly into shared prompts, files, logs, or examples.
Do not fetch large result sets in one request or ignore NCBI rate-limit responses.