pubmed-database

pubmed-database is a skill for Claude Code, Codex from google-deepmind/science-skills. It costs 79 tokens per session (2,007 once invoked), scanned A, original, Apache-2.0.

A research skill for searching PubMed, a database of biomedical and medical research, including published clinical trials. It can retrieve article text and connect papers with databases of genes, proteins, nucleotides, and chemical compounds.

In plain words
What is it for?
Use it to find medical papers, read abstracts or full text, verify spellings and citations, and investigate links to genes or compounds.
Why use it?
It brings literature searches, article details, citation checks, and related biological information into one workflow.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

About the project

Science Skills is a collection of add-ons that give AI agents structured instructions, scripts, and references for scientific research, including genomics, structural biology, cheminformatics, and literature search. Researchers use it to guide agents through specialized scientific tasks with information from databases and tools such as AlphaGenome, AFDB, and UniProt. The catalogue entries are individual skills from this collection.

google-deepmind/science-skills · 2,835 stars · on GitHub · antigravity.google

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/google-deepmind/science-skills/pubmed_database
Any agent
npx skills add google-deepmind/science-skills --skill pubmed_database
Clone the repo
git clone --depth 1 https://github.com/google-deepmind/science-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pubmed-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/google-deepmind/science-skills/pubmed_database.svg)](https://agentmods.dev/skills/google-deepmind/science-skills/pubmed_database)
Your own site
<a href="https://agentmods.dev/skills/google-deepmind/science-skills/pubmed_database"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/pubmed_database.svg" alt="Measured on agentmods" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,007 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.02007
Opus 5 $0.00039 $0.01004
Sonnet 5 $0.00016 $0.00401
Haiku 4.5 $0.00008 $0.00201

Measured 6d ago against content hash f1f4a89fb2b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

pubmed-database scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/pubmed_api.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

requests/second. Querying the API any other way (e.g. via curl, wget, or
skills/pubmed_database/SKILL.md · 186 lines

How it starts

The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PubMed API

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If .licenses/pubmed_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://pubmed.ncbi.nlm.nih.gov/disclaimer/ and https://www.ncbi.nlm.nih.gov/home/about/policies/ 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.
  3. .env file: Make sure the .env file exists in your home directory. Create one if it does not exist.
  4. NCBI_API_KEY (optional): Raises the NCBI E-utilities rate limit from 3 to 10 requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You MUST use the safe credentials protocol in the credentials skill to check for and request this key if this skill looks relevant to the user's request.
  5. USER_EMAIL (optional): Identifies the caller to NCBI (recommended by their Terms of Use). You MUST use the safe credentials protocol in the credentials skill to check for and request this credential if this skill looks relevant to the user's request.

This skill provides CLI access to the NCBI PubMed and PubMed Central APIs via scripts/pubmed_api.py — a single CLI with 10 functions covering search, fetch, linking, full text, spelling, discovery, citation matching, and caching.

Core Rules

  • API Use: Always use the provided wrapper scripts/pubmed_api.py which manages rate limits automatically and prevents API abuse. Setting the NCBI_API_KEY environment variable raises the rate limit from 3 to 10 requests/second. Querying the API any other way (e.g. via curl, wget, or hand-written code) is strictly forbidden.
  • JSON Processing: Use jq to filter and transform JSON output (or python equivalents if jq is not available) to prevent hallucinations and context overflow.
  • Temporary Files: To avoid polluting the working directory with JSON files, use a temporary directory inside the current directory. When running multiple agents or tasks in parallel, ensure each uses a unique subdirectory name (e.g., tmp_$TASK_ID/) to avoid file collisions.
  • Notification: 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.

Read the full file on GitHub · 186 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 186 lines · 79 tokens per session scan A f1f4a89fb2b7

Subscribe to this mod's changes

pubmed-database is a skill published in the GitHub repository google-deepmind/science-skills (2,835 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 2,007 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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