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Tooluniverse Disease Research

Listed
mims-harvard·vlatest·other·Apache-2.0

This AI agent swiftly researches diseases by leveraging a vast medical knowledge base, providing quick and reliable information for various needs.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mims-harvard/tooluniverse --skill tooluniverse-disease-research -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mims-harvard

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: purl.obolibrary.org.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    purl.obolibrary.orgundeclared

    What it found

    • plugin/skills/tooluniverse-disease-research/SKILL.md:80contacts purl.obolibrary.org
      # -> [{"semantic_tags": ["http://purl.obolibrary.org/obo/MONDO_0004979"],
    • plugins/tooluniverse/skills/tooluniverse-disease-research/SKILL.md:80contacts purl.obolibrary.org
      # -> [{"semantic_tags": ["http://purl.obolibrary.org/obo/MONDO_0004979"],
    • skills/tooluniverse-disease-research/SKILL.md:80contacts purl.obolibrary.org
      # -> [{"semantic_tags": ["http://purl.obolibrary.org/obo/MONDO_0004979"],

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mims-harvard/tooluniverse at f5c37eebeb.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
f5c37eebeb
Manifest
skills/tooluniverse-disease-research/SKILL.md
Scanned
18 files, 6,150 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The tooluniverse-disease-research skill enables AI agents to access and analyze specialized medical literature, clinical trial data, and epidemiological reports to support healthcare decision-making. It provides structured retrieval of disease-specific information from trusted repositories like PubMed and ClinicalTrials.gov.

When to use it

  • Investigating the latest treatment protocols for rare or emerging infectious diseases.
  • Summarizing outcomes from recent Phase III clinical trials for specific oncology drugs.
  • Cross-referencing epidemiological data to identify regional disease outbreak patterns.
  • Extracting contraindications and side effect profiles for polypharmacy management.

Key capabilities

  • Searches curated medical databases including PubMed, ClinicalTrials.gov, and WHO reports.
  • Filters results by publication date, study type, and geographic region.
  • Synthesizes complex clinical data into readable summaries with citation links.
  • Identifies gaps in current research regarding specific patient demographics.

Example prompts

  • "What are the latest findings on mRNA vaccine efficacy against new variants published in the last six months?"
  • "Summarize the side effect profiles and contraindications for immunotherapy agents used in non-small cell lung cancer."
  • "Find recent clinical trials comparing telemedicine versus in-person care for managing chronic heart failure."

Tips & gotchas

Ensure you verify AI-generated medical summaries against primary sources before applying them to patient care, as the tool aggregates data rather than providing diagnostic advice. Limit queries to specific disease areas to avoid overwhelming results from broad searches across multiple unrelated conditions.