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Tooluniverse Infectious Disease

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

This AI agent provides detailed information on infectious diseases, including symptoms, transmission, and treatment options, aiding in research & understanding.

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-infectious-disease -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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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-infectious-disease/SKILL.md
Scanned
18 files, 4,974 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 infectious-disease skill provides AI agents with access to curated data and analytical tools for monitoring, modeling, and responding to outbreaks of communicable diseases. It enables real-time tracking of epidemiological trends and supports evidence-based decision-making in public health scenarios.

When to use it

  • Analyze current outbreak patterns to predict potential spread in specific geographic regions.
  • Evaluate the effectiveness of various intervention strategies during a simulated or real crisis.
  • Generate reports on disease transmission dynamics for public health officials.
  • Identify high-risk populations based on demographic and environmental factors.

Key capabilities

  • Access to global infectious disease surveillance datasets.
  • Statistical modeling tools for outbreak forecasting.
  • Integration with epidemiological research literature.
  • Visualization of transmission chains and hotspots.

Example prompts

  • "Model the projected spread of a respiratory virus in urban areas over the next 14 days based on current mobility data."
  • "Summarize recent findings on vaccine efficacy against emerging viral variants from peer-reviewed journals."
  • "Identify key risk factors associated with increased hospitalization rates for seasonal influenza in elderly populations."

Tips & gotchas

Ensure you have access to the underlying ToolUniverse infrastructure, as this skill relies on external data feeds that may vary by region. Always validate AI-generated epidemiological insights against official health authority guidelines before making critical decisions.