Individual skill
tooluniverse-cancer-variant-interpretation
Clinical interpretation of somatic cancer mutations for precision oncology. Transforms a gene + variant + cancer-type input into an actionable report: clinical evidence tier (CIViC, OncoKB), therapeutic options (FDA-approved + investigational), resistance mechanisms, prognosis, and matching clinical trials. Use for tumor-board variant calls, somatic-mutation actionability assessment, and treatment selection. Always cancer-type-specific.
plugin/skills/tooluniverse-cancer-variant-interpretation/SKILL.md
Source commit 5598a9fc97e32964fe9b703818e7d0747142f179
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- Last checked
- Nov 9, 2026
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- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
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- agents Repository topic
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ANALYSIS_DETAILS.mddoc · 14,487 bytesEXAMPLES.mddoc · 7,095 bytesINPUT_PARSING.mddoc · 1,871 bytesQUICK_START.mddoc · 4,794 bytesREPORT_TEMPLATE.mddoc · 5,033 bytesSCORING_TABLES.mddoc · 4,400 bytesSKILL.mdcore · 18,499 bytesSKILL.mdcore · 18,499 bytesSKILL.mdcore · 18,499 bytesTOOLS_REFERENCE.mddoc · 19,228 bytes
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# 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**:
1. **Report-first approach** - Create report file FIRST, then populate progressively
2. **Evidence-graded** - Every recommendation has an evidence tier (T1-T4)
3. **Actionable output** - Prioritized treatment options, not data dumps
4. **Clinical focus** - Answer "what should we treat with?" not "what databases exist?"
5. **Resistance-aware** - Always check for known resistance mechanisms
6. **Cancer-type specific** - Tailor all recommendations to the patient's cancer type when provided
7. **Source-referenced** - Every statement must cite the tool/database source
8. **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