Tooluniverse Precision Oncology

Name: Tooluniverse Precision Oncology
Author: mims-harvard

Listed

mims-harvard·vlatest·other·Apache-2.0

Tooluniverse Precision Oncology leverages AI to analyze patient data & clinical guidelines for targeted treatment recommendations, improving cancer care decisions.

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-precision-oncology -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 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: cog.sanger.ac.uk.
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
cog.sanger.ac.ukundeclared
What it found (3 of 6)
- plugin/skills/tooluniverse-precision-oncology/scripts/gdsc_drug_response.py:35contacts cog.sanger.ac.uk
  "GDSC2": "https://cog.sanger.ac.uk/cancerrxgene/GDSC_release8.5/GDSC2_fitted_dose_response_27Oct23.xlsx",
- plugin/skills/tooluniverse-precision-oncology/scripts/gdsc_drug_response.py:36contacts cog.sanger.ac.uk
  "GDSC1": "https://cog.sanger.ac.uk/cancerrxgene/GDSC_release8.5/GDSC1_fitted_dose_response_27Oct23.xlsx",
- plugins/tooluniverse/skills/tooluniverse-precision-oncology/scripts/gdsc_drug_response.py:35contacts cog.sanger.ac.uk
  "GDSC2": "https://cog.sanger.ac.uk/cancerrxgene/GDSC_release8.5/GDSC2_fitted_dose_response_27Oct23.xlsx",
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-precision-oncology/SKILL.md
Scanned: 24 files, 6,174 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

What it does

The Tooluniverse Precision Oncology skill leverages AI to provide treatment recommendations for cancer patients based on their molecular profiles. It analyzes data from CIViC, ClinVar, OpenTargets, ClinicalTrials.gov, and structure-based analysis, adhering to a strict evidence hierarchy to ensure clinically sound suggestions. The tool prioritizes FDA-approved therapies and incorporates current NCCN guidelines and recent literature updates for accurate and up-to-date advice.

When to use it

When needing treatment options based on specific cancer mutations (e.g., EGFR exon 19 del, ALK fusion).
To understand potential resistance mechanisms when a patient progresses on targeted therapy.
For guidance on biomarker-to-drug mappings for various cancers including NSCLC, Breast, Colorectal and Melanoma.
When seeking to verify current approval status of therapies before making treatment decisions.
To identify whether progression is due to primary or acquired resistance mechanisms.

Key capabilities

Treatment Recommendation: Provides actionable treatment recommendations based on molecular profiles.
Evidence Hierarchy Adherence: Follows a strict ranking system for therapy selection (FDA approval > clinical trials > off-label use).
Database Integration: Utilizes CIViC, ClinVar, OpenTargets, ClinicalTrials.gov, and OncoKB data sources.
Biomarker-to-Drug Mapping: Offers established mappings between biomarkers and targeted therapies.
Resistance Mechanism Reasoning: Differentiates primary from acquired resistance mechanisms and identifies common patterns.

Example prompts

"What are the treatment options for a patient with NSCLC and an EGFR exon 19 deletion?"
"My patient progressed on osimertinib. What are potential resistance mechanisms I should investigate?"
"What is the recommended therapy for a breast cancer patient with a BRCA1 mutation?"

Tips & gotchas

Prioritize CIViC and OncoKB: When researching treatments, consult these databases before searching PubMed.
Stay Updated: Treatment guidelines and approvals change rapidly; always verify current information.
Adhere to the Evidence Hierarchy: Avoid recommending off-label therapies when approved options exist.