affaan-m/ECC

pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

84CollectingNetwork access
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "skills/scientific-db-pubmed-database"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn pubmed-database's source instructions into a guide you can follow

According to the pinned SKILL.md from affaan-m/ECC: Use this skill when a task needs biomedical literature from PubMed rather than general web search.

npx skills add https://github.com/affaan-m/ECC --skill "skills/scientific-db-pubmed-database"
Check the pinned source

Best fit

  • Searching MEDLINE or life-sciences literature.
  • Building PubMed queries with MeSH terms, field tags, dates, or article types.
  • Looking up PMIDs, abstracts, publication metadata, or related citations.

Bring this context

  • A concrete task that matches the documented purpose of pubmed-database.
  • The files, examples, or context the task depends on.
  • Your constraints, target environment, and definition of done.

Expected outputs

  • exact search string
  • database searched
  • date searched

Key source sections

Read pubmed-database through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

E-utilities Workflow

NCBI E-utilities supports repeatable API workflows:

SKILL.md · E-utilities Workflow
esearch.fcgi: search and return PMIDs.esummary.fcgi: return lightweight article metadata.efetch.fcgi: fetch abstracts or full records in XML, MEDLINE, or text.
02

Review Checklist

Are field tags valid PubMed tags?

SKILL.md · Review Checklist
Are field tags valid PubMed tags?Are MeSH terms paired with free-text synonyms for newer topics?Is the date range explicit and appropriate?
03

When to Use

Searching MEDLINE or life-sciences literature.

SKILL.md · When to Use
Searching MEDLINE or life-sciences literature.Building PubMed queries with MeSH terms, field tags, dates, or article types.Looking up PMIDs, abstracts, publication metadata, or related citations.
04

Query Construction

Start with the research question, split it into concepts, then combine concepts with Boolean operators.

SKILL.md · Query Construction
[ti]: title[ab]: abstract[tiab]: title or abstract
05

MeSH and Subheadings

Prefer MeSH when the concept has a stable controlled-vocabulary term. Combine MeSH with title/abstract terms when the topic is new or terminology varies.

SKILL.md · MeSH and Subheadings
Prefer MeSH when the concept has a stable controlled-vocabulary term. Combine MeSH with title/abstract terms when the topic is new or terminology varies.Correct subheading syntax puts the subheading before the field tag:Use [majr] only when the topic must be central to the paper. It can improve precision but may miss relevant work.

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use pubmed-database to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned pubmed-database source to [task]. Pay particular attention to these source sections: “E-utilities Workflow”, “Review Checklist”, “When to Use”, “Query Construction”, “MeSH and Subheadings”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current pubmed-database result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “E-utilities Workflow” has been checked.

The source section “Review Checklist” has been checked.

The source section “When to Use” has been checked.

The source section “Query Construction” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

FAQ

What does pubmed-database do?

Use this skill when a task needs biomedical literature from PubMed rather than general web search.

How do I start using pubmed-database?

The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/scientific-db-pubmed-database". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
234,327
Repository forks
35,711
Quality
84/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

84/100
Documentation28/30
Specificity23/25
Maintenance20/20
Trust signals13/25

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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 2 min

PubMed Database

Use this skill when a task needs biomedical literature from PubMed rather than general web search.

When to Use

  • Searching MEDLINE or life-sciences literature.
  • Building PubMed queries with MeSH terms, field tags, dates, or article types.
  • Looking up PMIDs, abstracts, publication metadata, or related citations.
  • Running systematic-review search passes that need repeatable search strings.
  • Using NCBI E-utilities directly from Python, shell, or another HTTP client.

Query Construction

Start with the research question, split it into concepts, then combine concepts with Boolean operators.

concept_1 AND concept_2 AND filter
synonym_a OR synonym_b
NOT exclusion_term

Useful PubMed field tags:

  • [ti]: title
  • [ab]: abstract
  • [tiab]: title or abstract
  • [au]: author
  • [ta]: journal title abbreviation
  • [mh]: MeSH term
  • [majr]: major MeSH topic
  • [pt]: publication type
  • [dp]: date of publication
  • [la]: language

Examples:

diabetes mellitus[mh] AND treatment[tiab] AND systematic review[pt] AND 2023:2026[dp]
(metformin[nm] OR insulin[nm]) AND diabetes mellitus, type 2[mh] AND randomized controlled trial[pt]
smith ja[au] AND cancer[tiab] AND 2026[dp] AND english[la]

MeSH and Subheadings

Prefer MeSH when the concept has a stable controlled-vocabulary term. Combine MeSH with title/abstract terms when the topic is new or terminology varies.

Correct subheading syntax puts the subheading before the field tag:

diabetes mellitus, type 2/drug therapy[mh]
cardiovascular diseases/prevention & control[mh]

Use [majr] only when the topic must be central to the paper. It can improve precision but may miss relevant work.

Filters

Publication types:

  • clinical trial[pt]
  • meta-analysis[pt]
  • randomized controlled trial[pt]
  • review[pt]
  • systematic review[pt]
  • guideline[pt]

Date filters:

2026[dp]
2020:2026[dp]
2026/03/15[dp]

Availability filters:

free full text[sb]
hasabstract[text]

E-utilities Workflow

NCBI E-utilities supports repeatable API workflows:

  1. esearch.fcgi: search and return PMIDs.
  2. esummary.fcgi: return lightweight article metadata.
  3. efetch.fcgi: fetch abstracts or full records in XML, MEDLINE, or text.
  4. elink.fcgi: find related articles and linked resources.

Use an email and API key for production scripts. Store API keys in environment variables, never in committed files or command history.

import os
import time
import requests

BASE = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils"


def esearch(query: str, retmax: int = 20) -> list[str]:
    params = {
        "db": "pubmed",
        "term": query,
        "retmode": "json",
        "retmax": retmax,
        "tool": "ecc-pubmed-search",
        "email": os.environ.get("NCBI_EMAIL", ""),
    }
    api_key = os.environ.get("NCBI_API_KEY")
    if api_key:
        params["api_key"] = api_key

    response = requests.get(f"{BASE}/esearch.fcgi", params=params, timeout=30)
    response.raise_for_status()
    time.sleep(0.35)
    return response.json()["esearchresult"]["idlist"]


pmids = esearch("hypertension[mh] AND randomized controlled trial[pt] AND 2024:2026[dp]")
print(pmids)

For batches, prefer NCBI history server parameters (usehistory=y, WebEnv, query_key) instead of passing very long PMID lists through URLs.

Output Discipline

For each search pass, record:

  • exact search string
  • database searched
  • date searched
  • filters used
  • result count
  • export format
  • any manual exclusions

Example:

| Database | Date searched | Query | Filters | Results |
| --- | --- | --- | --- | ---: |
| PubMed | 2026-05-11 | `sickle cell disease[mh] AND CRISPR[tiab]` | 2020:2026[dp], English | 42 |

Review Checklist

  • Are field tags valid PubMed tags?
  • Are MeSH terms paired with free-text synonyms for newer topics?
  • Is the date range explicit and appropriate?
  • Does the search log include enough detail to reproduce the query?
  • Are API keys loaded from the environment?
  • Does HTTP code call raise_for_status() or otherwise handle non-200 responses before parsing?
  • Are rate limits respected?

References

Source repo
affaan-m/ECC
Skill path
skills/scientific-db-pubmed-database/SKILL.md
Commit SHA
4e973d3eaf92
Repository license
MIT
Data collected