— name: family-health-analyzer description: Analyze family medical history, assess hereditary risk, identify family health patterns, and provide personalized prevention advice. allowed-tools: Read, Write, Grep, Glob risk: unknown source: community — # Family health-analysis skill ## When to Use – Use when you need to analyze family medical history, hereditary risk, or family-level health patterns. – When the task involves family health reports, identifying familial-clustering diseases, or generating prevention advice. – When you need to aggregate several family members' health data and then do a trend or risk assessment. ## Skill overview This skill provides in-depth analysis of family health data, including: – Hereditary-risk assessment – Familial disease-pattern identification – Analysis of shared family problems – Personalized prevention advice – Visual report generation ## Triggers Use this skill when the user requests any of: – "家庭健康报告" (family health report) – "家族病史分析" (family medical-history analysis) – "遗传风险评估" (hereditary-risk assessment) – "家庭健康趋勿" (family health trends) – the `/family report` command – the `/family risk` command ## Analysis steps ### Step 1: Determine the analysis goal Identify the type of user request: – Family medical-history analysis – Hereditary-risk assessment – Family health trends – Family health report ### Step 2: Read the family data **Data sources:** 1. Main data file: `data/family-health-tracker.json` 2. Integrated-module data: – `data/hypertension-tracker.json` – `data/diabetes-tracker.json` – `data/profile.json` ### Step 3: Data validation and cleaning **Validation items:** – Relationship integrity – Age plausibility – Data consistency ### Step 4: Hereditary-pattern identification **Identification algorithm:** 1. Familial-clustering analysis 2. Inheritance-pattern identification 3. Early-onset case identification (usually < 50 years old) ### Step 5: Risk-calculation algorithm **Weighted calculation:** “`python hereditary_risk_score = (number_of_first_degree_relatives_affected * 0.4) + (number_of_early_onset_cases * 0.3) + (degree_of_family_clustering * 0.3) Risk levels: – High risk: >= 70% – Medium risk: 40%-69% – Low risk: < 40% “` ### Step 6: Generate prevention advice **Advice categories:** – Screening advice: regular checkup items – Lifestyle advice: diet, exercise, daily routine – Care-seeking advice: when to see a doctor, which specialist to consult **Example:** “`json { "category": "screening", "action": "regular blood-pressure monitoring", "frequency": "3 times per week", "start_age": 35, "priority": "high" } “` ### Step 7: Generate a visual report **HTML report components:** 1. Family tree (ECharts tree diagram) 2. Hereditary-risk heatmap 3. Disease-distribution pie chart 4. Prevention-advice timeline ### Step 8: Output the result **Output formats:** 1. Text report (concise version): command-line output 2. HTML report (full version): visual charts ## Safety principles ### Medical safety boundaries – ✅ Only does statistical analysis based on family medical history – ✅ Provides prevention advice and screening reminders – ✅ Clearly marks uncertainty – ❌ Does not diagnose hereditary disease – ❌ Does not predict an individual's probability of disease – ❌ Does not recommend specific treatment plans ### Disclaimer Every analysis output must include: “` ⚠️ Disclaimer: 1. This analysis is based on family-history statistics and is for reference only. 2. The hereditary-risk assessment does not predict individual onset. 3. For all medical decisions, consult a professional doctor. 4. For genetic-counseling advice, consult a professional genetic counselor. “` ## Integrate existing modules – Read hypertension-management data – Read diabetes-management data – Link medication records — **Skill version**: v1.0 **Last updated**: 2025-01-08 **Maintainer**: WellAlly Tech ## Limitations – Use this skill only when the task clearly matches the scope described above. – Do not treat the output as a substitute for environment-specific validation, testing, or expert review. – Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.