{"skill":{"slug":"live-to-100","displayName":"Live To 100","summary":"收集用户身体指标、生活习惯、既往病史和目标，生成可执行的长寿行动计划与分阶段复盘机制，并提供风险评分、自动周报/月报、保健品安全检查和每日饮食营养均衡分析（含热量缺口）。Use when users ask for longevity plans, healthy routine optimization, be...","description":"---\nname: live-to-100\ndescription: 收集用户身体指标、生活习惯、既往病史和目标，生成可执行的长寿行动计划与分阶段复盘机制，并提供风险评分、自动周报/月报、保健品安全检查和每日饮食营养均衡分析（含热量缺口）。Use when users ask for longevity plans, healthy routine optimization, behavior-change schedules, supplement safety review, daily meal/nutrition analysis, calorie deficit tracking, or recurring reminders for hydration, standing breaks, sleep, and exercise.\n---\n\n# Live To 100\n\n## Core Rule\n\nPosition the output as lifestyle guidance, not diagnosis or emergency care.\nIf the user reports urgent danger signs (e.g., severe chest pain, fainting, stroke-like symptoms, self-harm intent), stop planning and advise immediate emergency care.\n\n## Workflow\n\n### 1) Collect baseline data\n\nUse `references/intake-template.md` as the intake form.\nAsk only for missing high-impact fields first:\n- Age, biological sex, height, weight, waist\n- Blood pressure (if known), resting heart rate, sleep duration\n- Activity level (steps, exercise days/week, sedentary hours)\n- Smoking, alcohol, caffeine timing\n- Current diseases, medications, supplement list\n- Main goal and constraints (time, budget, injuries, shift work)\n\nIf data is partial, continue with assumptions and clearly label assumptions.\n\n### 2) Build longevity profile\n\nProduce a concise risk-and-opportunity snapshot:\n- `Green`: already solid habits to maintain\n- `Yellow`: moderate gaps to improve in 4-12 weeks\n- `Red`: possible high-risk items that need clinician follow-up\n\nPrioritize behavior changes by expected impact and feasibility.\nDo not overload the plan with more than 3 major behavior goals at once.\n\nThen calculate a `Longevity Risk Score (0-100)` using `references/risk-scoring.md`:\n- Show total score and sub-scores (body composition, cardiometabolic, sleep/recovery, activity/sedentary, habits, medical context).\n- Explain top 3 contributors and which 2-3 changes can move the score most in 4 weeks.\n- If critical data is missing, output a provisional score and list missing fields.\n\n### 3) Generate actionable plan\n\nReturn a 12-week plan in 3 phases:\n- `Phase 1 (Week 1-2)`: minimum viable routine and reminders\n- `Phase 2 (Week 3-6)`: progressive overload and consistency targets\n- `Phase 3 (Week 7-12)`: stabilization and relapse prevention\n\nInclude these dimensions:\n- Hydration\n- Standing/mobility breaks\n- Sleep timing and wind-down\n- Exercise (aerobic + strength + daily movement)\n- Nutrition guardrails\n- Supplements (after safety screening only)\n\nFor each action, specify:\n- Trigger (`when`)\n- Action (`what`)\n- Minimum bar (`minimum version`)\n- Upgrade path (`next level`)\n\n### 4) Configure reminders\n\nUse `references/reminder-presets.md` and adapt to user wake/sleep schedule.\nFor complex timetables (multiple windows, weekday/weekend differences, interval reminders, quiet hours), use `references/reminder-timetable.md`.\nAlways output a reminder table with:\n- Reminder type\n- Time or interval\n- Message\n- Duration\n- Completion rule\n\nSupport at least these reminders:\n- Drink water\n- Stand up / move\n- Sleep routine\n- Workout\n- Supplements\n\nIf the platform supports recurring automations, generate platform-ready schedules.\nIf not, output copy-paste reminder text for phone calendar or todo apps.\n\nWhen structured schedule JSON is available, generate concrete reminders with:\n`python scripts/generate_reminder_timetable.py --input schedule.json --output reminders.md`\n\n### 5) Apply supplement safety gate\n\nUse `references/supplement-safety.md` before confirming any supplement advice:\n- Check contraindications against existing diseases, meds, allergies, pregnancy/breastfeeding status, kidney/liver flags.\n- Check dosage and timing boundaries; avoid adding stacked supplements with overlapping risks.\n- Output status per supplement: `Safe to continue`, `Needs clinician review`, or `Avoid for now`.\n- If conflict exists, prioritize food-first alternatives and medical follow-up over additional supplements.\n\n### 6) Close the loop with auto reports\n\nAdd a lightweight check-in protocol:\n- Daily: adherence score (0-100) + 1 blocker\n- Weekly: trend on sleep, movement, training sessions, waist/weight\n- Every 4 weeks: adjust targets based on adherence and recovery\n\nWhen adherence is low, reduce plan complexity before increasing intensity.\n\nGenerate reports using `references/report-templates.md`:\n- Weekly report: adherence, metric deltas, blockers, and next-week focus.\n- Monthly report: score trend, behavior consistency, supplement safety events, and plan adjustments.\n- Keep each report short and action-oriented.\n\n### 7) Analyze daily meals and calorie deficit\n\nUse `references/daily-nutrition-log.md` for daily food logging input.\nEvaluate these outputs every day:\n- Total calories and estimated calorie deficit/surplus vs target\n- Macro totals (protein/carbs/fat) and ratio balance\n- Fiber and hydration adequacy\n- Food diversity and ultra-processed food proportion (if available)\n\nReturn:\n- `Nutrition Balance Score (0-100)`\n- `Calorie Deficit Status` (on target / too aggressive / insufficient)\n- 2-3 concrete meal adjustments for next day\n\nWhen structured daily log JSON is available, generate analysis with:\n`python scripts/analyze_daily_nutrition.py --input nutrition_day.json --output nutrition_report.md`\n\n## Output Format\n\nUse this order:\n1. `Health Snapshot` (Green/Yellow/Red)\n2. `Longevity Risk Score` (total + sub-scores + key drivers)\n3. `12-Week Longevity Plan`\n4. `Reminder Schedule`\n5. `Supplement Safety Check`\n6. `Daily Nutrition Balance and Calorie Deficit`\n7. `Check-in and Auto Report Rules`\n8. `Medical Follow-up Flags` (if applicable)\n\nKeep recommendations specific, measurable, and time-bound.\nAvoid abstract advice without concrete behaviors.\n\n## Resources\n\n- Intake template: `references/intake-template.md`\n- Daily nutrition intake template: `references/daily-nutrition-log.md`\n- Reminder defaults: `references/reminder-presets.md`\n- Complex timetable schema: `references/reminder-timetable.md`\n- Risk model: `references/risk-scoring.md`\n- Supplement safety: `references/supplement-safety.md`\n- Weekly/monthly report templates: `references/report-templates.md`\n- Report generator script: `scripts/generate_health_reports.py`\n- Reminder timetable generator script: `scripts/generate_reminder_timetable.py`\n- Daily nutrition analyzer script: `scripts/analyze_daily_nutrition.py`\n\nUse the script when structured JSON data is available:\n`python scripts/generate_health_reports.py --input user_data.json --output report.md`\n","tags":{"latest":"1.0.0"},"stats":{"comments":0,"downloads":399,"installsAllTime":0,"installsCurrent":0,"stars":0,"versions":1},"createdAt":1774410714405,"updatedAt":1778492175875},"latestVersion":{"version":"1.0.0","createdAt":1774410714405,"changelog":"Initial release","license":"MIT-0"},"metadata":null,"owner":{"handle":"rq-wu","userId":"s179tgnagc08c6zhys0mtbww8h83hkvc","displayName":"RQ-Wu","image":"https://avatars.githubusercontent.com/u/50363829?v=4"},"moderation":null}