family-health-analyzer

Family Health Analysis Skill

When to Use

• Use when there is a need to analyze family medical history, genetic risk, or family-level health patterns.
• The task involves family health reports, identification of diseases clustering in families, or generation of prevention recommendations.
• There is a need to aggregate health data from multiple family members and then perform trend or risk assessment.

Skill Overview

This skill provides in-depth analysis of family health data, including:

• Genetic Risk Assessment
• Family Disease Pattern Identification
• Family Shared Problem Analysis
• Personalized Prevention Recommendations
• Visualization Report Generation

Trigger Conditions

Use this skill when the user requests the following:

• "Family Health Report"
• "Family Medical History Analysis"
• "Genetic Risk Assessment"
• "Family Health Trends"
• Execute the /family report command
• Execute the /family risk command

Analysis Steps

Step 1: Determine the analysis objective

Identify the user request type:

• Family medical history analysis
• Genetic risk assessment
• Family health trends
• Family health report

Step 2: Read family data

Data sources:

1. Primary 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: Genetic pattern identification

Identification algorithms:

1. Familial clustering analysis
2. Genetic pattern identification
3. Record age at onset; the "early-onset" threshold depends on the specific disease and validated guidelines, and is not uniformly set at 50 years

Step 5: Descriptive summary, do not calculate clinical risk

Do not use unverified weighted formulas to generate percentages. The number of relatives, number of early-onset cases, and degree of clustering are not in the same units and are not normalized data; the original 0.4/0.3/0.3 weights and 70% threshold have no clinical calibration basis. Record only the actually known relationships, diagnostic sources, ages at onset, and missing items, and let professionals determine whether further evaluation is needed.

Recording example (not an executable calculation algorithm):

已知一级亲属病史：按疾病、关系和发病年龄逐条列出
来源：本人确认／医疗记录／待核实
缺失信息：明确列出，不推定为阴性
后续：向医生或遗传咨询师提出待评估问题，不输出发病概率

Step 6: Generate prevention recommendations

Recommendation categories:

• Screening recommendations: regular examination items
• Lifestyle recommendations: diet, exercise, sleep schedule
• Medical consultation recommendations: when to seek care, which specialty to consult

Example:

{
  "category": "screening",
  "action": "定期血压监测",
  "frequency": "由医生依据实际情况确定",
  "start_age": null,
  "priority": "high"
}

Step 7: Generate visualization report

HTML report components:

1. Family tree (ECharts tree diagram)
2. Known medical history distribution chart (must not be labeled as individual genetic risk probability)
3. Disease distribution pie chart
4. Prevention recommendation timeline

Step 8: Output results

Output formats:

1. Text report (concise version): command-line output
2. HTML report (full version): visualization charts

Safety Principles

Medical safety boundaries

• ✅ Perform statistical analysis based only on family medical history
• ✅ Provide prevention recommendations and screening reminders
• ✅ Clearly indicate uncertainty
• ❌ Do not perform genetic disease diagnosis
• ❌ Do not predict individual disease probability
• ❌ Do not recommend specific treatment plans

Disclaimer

Each analysis output must include:

⚠️ 免责声明:
1. 本分析基于家族病史统计,仅供参考
2. 遗传风险评估不预测个体发病
3. 所有医疗决策请咨询专业医师
4. 遗传咨询建议咨询专业遗传咨询师

Integrate existing modules

• Read hypertension management data
• Read diabetes management data
• Link medication records

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Skill version: v1.0 Last updated: 2025-01-08 Maintainer: WellAlly Tech

Limitations

• Chinese is the original audience language, not a defect; interact in the language specified by the user. The original text already contains a clear medical disclaimer, which must be retained.
• data/*.json and the /family command are external application conventions; AAS does not distribute these data, runtime, or algorithms; first locate the real data source explicitly authorized by the user, and do not fake successful commands.
• Family/genetic information is highly sensitive; collect only the minimal fields for which consent has been obtained, anonymize relative records, and store them privately; do not infer a person's diagnosis from a relative's association.
• CDC Family Health History descriptionEmphasize discussing with medical professionals; this skill does not provide medical diagnosis, treatment, or self-directed changes to screening plans.
• 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.