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tooluniverse-precision-medicine-stratification

Maintainer FreedomIntelligence · Last updated April 1, 2026

Comprehensive patient stratification for precision medicine by integrating genomic, clinical, and therapeutic data. Given a disease/condition, genomic data (germline variants, somatic mutations, expression), and optional clinical parameters, performs multi-phase analysis across 9 phases covering disease disambiguation, genetic risk assessment, disease-specific molecular stratification, pharmacogenomic profiling, com….

OpenClawNanoClawAnalysisReproductiontooluniverse-precision-medicine-stratification🏥 medical & clinicalmedical toolscomprehensive

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-precision-medicine-stratification

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • Transform patient genomic and clinical profiles into actionable risk stratification, treatment recommendations, and personalized therapeutic strategies. Integrates germline genetics, somatic alterations, pharmacogenomics, pathway biology, and clinical evidence to produce a quantitative risk score with tiered management recommendations.
  • KEY PRINCIPLES: 1. Report-first approach - Create report file FIRST, then populate progressively 2. Disease-specific logic - Cancer vs metabolic vs rare disease pipelines diverge at Phase 2 3. Multi-level integration - Germline + somatic + expression + clinical data layers 4. Evidence-graded - Every finding has an evidence tier (T1-T4) 5. Quantitative output - Precision Medicine Risk Score (0-100) with transparent components 6. Pharmacogenomic guidance - Drug selection AND dosing recommendations 7. Guideline-concordant - Reference NCCN, ACC/AHA, ADA, and other guidelines 8. Source-referenced - Every statement cites the tool/database source 9. Completeness checklist - Mandatory section showing data availability and analysis coverage 10. English-first queries - Always use English terms in tool calls. Respond in user's language.
  • result = tu.tools.OpenTargets_get_disease_id_description_by_name(diseaseName='breast cancer').

Source Doc

Excerpt From SKILL.md

When to Use

Apply when user asks:

  • "Stratify this breast cancer patient: ER+/HER2-, BRCA1 mutation, stage II"
  • "What is the risk profile for this diabetes patient with HbA1c 8.5 and CYP2C19 poor metabolizer?"
  • "NSCLC patient with EGFR L858R, stage IV, TMB 25 - treatment strategy?"
  • "Predict prognosis and recommend treatment for this cardiovascular patient"
  • "Patient has Marfan syndrome with FBN1 mutation - risk stratification"
  • "Alzheimer's risk assessment: APOE e4/e4, family history positive"
  • "Personalized treatment plan for type 2 diabetes with genetic risk factors"
  • "Which therapy is best for this patient's molecular profile?"

NOT for (use other skills instead):

  • Single variant interpretation -> Use tooluniverse-variant-interpretation or tooluniverse-cancer-variant-interpretation
  • Immunotherapy-specific prediction -> Use tooluniverse-immunotherapy-response-prediction
  • Drug safety profiling only -> Use tooluniverse-adverse-event-detection
  • Target validation -> Use tooluniverse-drug-target-validation
  • Clinical trial search only -> Use tooluniverse-clinical-trial-matching
  • Drug-drug interaction analysis only -> Use tooluniverse-drug-drug-interaction
  • PRS calculation only -> Use tooluniverse-polygenic-risk-score

Required Input

  • Disease/condition: Free-text disease name (e.g., "breast cancer", "type 2 diabetes", "Marfan syndrome")
  • At least one of: Germline variants, somatic mutations, gene list, or clinical biomarkers

Strongly Recommended

  • Genomic data: Specific variants (e.g., "BRCA1 c.68_69delAG", "EGFR L858R"), gene names, or expression changes
  • Clinical parameters: Age, sex, disease stage, biomarkers (HbA1c, PSA, LDL-C)

Use cases

  • Use when clinicians ask about patient risk stratification, treatment selection, prognosis prediction, or personalized therapeutic strategy across cancer, metabolic, cardiovascular, neurological, or rare diseases.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

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