Tooluniverse Cancer Variant Interpretation
This is a structured pipeline for turning somatic mutations into treatment recommendations. Feed it a gene, variant, and cancer type, and it walks through CIViC evidence tiers, cBioPortal prevalence, OpenTargets drug associations, resistance mechanisms, and active clinical trials, then synthesizes an actionable report. The workflow is prescriptive: it explicitly tells Claude to create the report file first, look up facts instead of guessing, and compute statistics instead of describing them. The driver versus passenger reasoning section is solid, distinguishing recurrent hotspots from likely noise. You'd use this for tumor board prep or when a patient's sequencing report lands and you need to know what therapies actually exist for their specific alteration. It's designed for cancer, but the evidence-grading and source-tracking patterns could apply to other clinical interpretation tasks.
- skills.sh installs
- 382
- GitHub stars
- 1.8K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add mims-harvard/tooluniverse --skill tooluniverse-cancer-variant-interpretation --agent claude-codeInstalls into .claude/skills of the current project.
Files
Cancer Variant Interpretation for Precision Oncology
Comprehensive clinical interpretation of somatic mutations in cancer. Transforms a gene + variant input into an actionable precision oncology report covering clinical evidence, therapeutic options, resistance mechanisms, clinical trials, and prognostic implications.
KEY PRINCIPLES:
- Report-first approach - Create report file FIRST, then populate progressively
- Evidence-graded - Every recommendation has an evidence tier (T1-T4)
- Actionable output - Prioritized treatment options, not data dumps
- Clinical focus - Answer "what should we treat with?" not "what databases exist?"
- Resistance-aware - Always check for known resistance mechanisms
- Cancer-type specific - Tailor all recommendations to the patient's cancer type when provided
- Source-referenced - Every statement must cite the tool/database source
- English-first queries - Always use English terms in tool calls (gene names, drug names, cancer types), even if the user writes in another language. Respond in the user's language
Sponsors
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- Repository
- github.com/mims-harvard/tooluniverse
- First seen
- Jun 3, 2026
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