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Agent skill

Scientific DB Pubmed Database

by affaan-m in affaan-m/ECC

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

MITAuto-check passedResearch & Science

Install Scientific DB Pubmed Database

skills CLI
$ npx skills add affaan-m/ECC --skill scientific-db-pubmed-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC scientific-db-pubmed-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scientific-db-pubmed-database .claude/skills/scientific-db-pubmed-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scientific-db-pubmed-database
GitHub stars
277k
Used in
1 other repo
Token cost
~1.2k tokens
SKILL.md length
370 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 4 steps: esearch.fcgi: search and return PMIDs. → esummary.fcgi: return lightweight… → efetch.fcgi: fetch abstracts or full… → …
  • A task needs biomedical literature from PubMed rather than general web search
  • SKILL.md covers When to Use, Query Construction, MeSH and Subheadings and Filters, plus 4 more sections
  • Reaches eutils.ncbi.nlm.nih.gov; needs NCBI_API_KEY

What it does

Scientific DB Pubmed Database is an agent skill from affaan-m/ECC. Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring. Use when a task needs biomedical literature from PubMed rather than general web search.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Academic paper search and Web search. It works with PubMed and NCBI. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • A task needs biomedical literature from PubMed rather than general web search
  • Tasks that involve Academic paper search
  • Tasks that involve Web search

Example prompts

  • “/scientific-db-pubmed-database”

Requirements

  • Python 3
  • A credential in NCBI_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • eutils.ncbi.nlm.nih.gov

    Also links to:

    • pubmed.ncbi.nlm.nih.gov
    • ncbi.nlm.nih.gov
    • support.nlm.nih.gov

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • NCBI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scientific DB Pubmed Database loads about 1.2k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 370 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 370 words, ~1,207 tokens.

Download SKILL.mdSave it as .claude/skills/scientific-db-pubmed-database/SKILL.md (or your agent's skills folder).
name
scientific-db-pubmed-database
description
Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring. Use when a task needs biomedical literature from PubMed rather than general web search.
metadata.origin
community

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.

text
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:

text
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:

text
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:

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

Availability filters:

text
free full text[sb]
hasabstract[text]
Show full SKILL.md (177 more words)Show less

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.

python
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:

markdown
| 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

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/scientific-db-pubmed-database of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Scientific DB Pubmed Database next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scientific DB Pubmed Database compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scientific DB Pubmed Database this skillaffaan-m/ECC277k1 repos~1.2kAutomated safety check: PassMIT
PubMed REST API Searchdavila7/claude-code-templates33k14 repos~3.9kAutomated safety check: PassMIT
Pubmed Databasegoogle-deepmind/science-skills3.2k2 repos~2.1kAutomated safety check: NotesApache-2.0
Ncbi Sequence Fetchgoogle-deepmind/science-skills3.2k1 repos~2.3kAutomated safety check: NotesApache-2.0
Journal Skillsaipoch/medical-research-skills1.9k—~1.7kAutomated safety check: PassMIT
Pubmed Databasejaechang-hits/SciAgent-Skills3741 repos~4.4kAutomated safety check: PassCC-BY-4.0

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Works with

Categories

Questions about Scientific DB Pubmed Database

What does Scientific DB Pubmed Database do?

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring. Scientific DB Pubmed Database is an agent skill from affaan-m/ECC. Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

When should I use Scientific DB Pubmed Database?

Scientific DB Pubmed Database fits situations like: A task needs biomedical literature from PubMed rather than general web search; tasks that involve Academic paper search; tasks that involve Web search.

How do I install Scientific DB Pubmed Database in Claude Code?

Run `npx skills add affaan-m/ECC --skill scientific-db-pubmed-database -a claude-code`. Or copy the skill folder (skills/scientific-db-pubmed-database in affaan-m/ECC) into .claude/skills/scientific-db-pubmed-database in your project. Claude Code loads it when a task matches its description.

How do I install Scientific DB Pubmed Database in Codex?

Run `npx skills add affaan-m/ECC --skill scientific-db-pubmed-database -a codex`. Or copy the skill folder (skills/scientific-db-pubmed-database in affaan-m/ECC) into .agents/skills/scientific-db-pubmed-database in your project. Codex loads it when a task matches its description.

Can I use Scientific DB Pubmed Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill scientific-db-pubmed-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scientific-db-pubmed-database, .gemini/skills/scientific-db-pubmed-database, .github/skills/scientific-db-pubmed-database and .opencode/skills/scientific-db-pubmed-database in your project.

What does Scientific DB Pubmed Database need to run?

Going by SKILL.md and its folder, Scientific DB Pubmed Database needs credentials named NCBI_API_KEY. Our summary lists: Python 3; A credential in NCBI_API_KEY.

Does Scientific DB Pubmed Database access the network?

SKILL.md names 4 domains. In commands or code: eutils.ncbi.nlm.nih.gov; the agent is likely to contact it when it follows the instructions. As links in the text: pubmed.ncbi.nlm.nih.gov, ncbi.nlm.nih.gov and support.nlm.nih.gov. This is read from the text; nothing was executed.

Is Scientific DB Pubmed Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scientific DB Pubmed Database use?

Scientific DB Pubmed Database is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scientific DB Pubmed Database use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scientific DB Pubmed Database?

Skills that share tags, products or a category with Scientific DB Pubmed Database: PubMed REST API Search (davila7/claude-code-templates, 33k stars), Pubmed Database (google-deepmind/science-skills, 3.2k stars), Ncbi Sequence Fetch (google-deepmind/science-skills, 3.2k stars) and Journal Skills (aipoch/medical-research-skills, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scientific DB Pubmed Database?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.