Tooluniverse Rare Disease Diagnosis

Name: Tooluniverse Rare Disease Diagnosis
Author: mims-harvard

Checked

mims-harvard·vlatest·other·Apache-2.0

This AI analyzes patient data to identify potential rare disease diagnoses, accelerating investigation and improving diagnostic accuracy for complex cases.

Repository

Install on your platform

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

Run this in your project

terminal

$ npx skills add mims-harvard/tooluniverse --skill tooluniverse-rare-disease-diagnosis -a claude-code

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 28 Sept 2026

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-rare-disease-diagnosis/SKILL.md
Scanned: 21 files, 9,468 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.

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About this skill

The tooluniverse-rare-disease-diagnosis skill enables AI agents to access specialized medical databases and literature to identify potential rare disease conditions based on patient symptoms and clinical data. It facilitates the cross-referencing of complex symptom clusters with global case studies to generate preliminary diagnostic hypotheses for healthcare professionals.

When to use it

Analyzing ambiguous or atypical symptom presentations that do not match common disease patterns.
Supporting clinicians during initial triage when standard diagnostic tools yield inconclusive results.
Researching specific genetic disorders or syndromes linked to unique patient histories.
Compiling comprehensive literature reviews on emerging rare conditions for case discussions.

Key capabilities

Access to curated repositories of rare disease information and clinical guidelines.
Symptom-to-disease matching algorithms designed for low-prevalence conditions.
Integration with global medical databases for up-to-date epidemiological data.
Generation of structured diagnostic reports summarizing potential matches and evidence.

Example prompts

"Identify potential rare diseases associated with a combination of unexplained fever, skin rashes, and joint pain in a pediatric patient."
"Cross-reference the symptoms of chronic fatigue and cognitive decline with recent literature on autoimmune disorders to suggest possible diagnoses."
"Summarize current research findings on the genetic markers for Wilson's disease based on the provided patient lab results."

Tips & gotchas

This tool is designed to assist medical professionals, not replace clinical judgment; always verify AI-generated hypotheses with authoritative sources and further testing. Ensure that patient data shared with the agent complies with all relevant privacy regulations and ethical guidelines before analysis.