Token导航 LogoToken导航

Agent Skill · 待分类

health-coach(健康教练)

health-coach 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

health-coach 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 1,396。

总安装 3,501周安装 143GitHub Stars 25下载 1,133核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:health-coach(健康教练)
来源仓库:https://github.com/h1an1/health-coach
仓库路径:skills/health-coach
安装命令:
npx skills add https://github.com/h1an1/health-coach --skill health-coach
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/h1an1/health-coach --skill health-coach

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

health-coach 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合整理仓库状态与协作事项。适用于需要围绕代码变更或协作流程进行信息梳理的场景。通过 npx skills add 命令安装,需结合原始 README 核验具体用法。

安装前建议确认权限范围、维护状态及是否触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/health-coach

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/h1an1/health-coach --skill health-coach;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

health-coach 怎么安装?

在终端执行 npx skills add https://github.com/h1an1/health-coach --skill health-coach。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

health-coach 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

health-coach 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

health-coach 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

health-coach 用的人多吗?

公开数据是累计安装 3,501 次,近一周安装 143 次,下载 1,133 次,GitHub 25 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

health-coach 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
health-coach

健康教练 · 本页

3,50125只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Health Coach

A clinical-grade personal health management skill. Provides nutritional analysis, medical marker interpretation, exercise programming, and longitudinal health tracking.

Setup

On first use, initialize a user health profile:

  1. Copy config/profile.template.md → user workspace as health/profile.md
  2. Copy config/goals.template.md → user workspace as health/goals.md
  3. Copy config/reminders.template.md → user workspace as health/reminders.md
  4. Create health/logs/ directory for daily logs

All personal data stays in the user's workspace. Never commit health data to shared repos.

Core Workflows

1. Meal Analysis (Photo or Text)

When user shares a meal photo or describes food:

  1. Identify all food items, estimate portion sizes
  2. Reference references/nutrition.md for caloric density, macro ratios
  3. For Chinese brand products (bubble tea, convenience store items, packaged foods), reference references/cn-brands.md for accurate nutritional data
  4. Calculate: calories, protein (g), carbs (g), fat (g), fiber (g)
  5. Compare against user's daily targets from health/goals.md
  6. Provide remaining budget for the day
  7. Flag nutritional gaps or excesses

Output format: concise, no lecture. Numbers first, advice second.

2. Lab Result Interpretation

When user shares blood work, FeNO, urinalysis, or other medical data:

  1. Reference references/medical-markers.md for normal ranges and clinical significance
  2. Flag out-of-range values with severity (mild/moderate/concerning)
  3. Explain what each marker means in plain language
  4. Note trends if historical data exists in profile
  5. Always remind: this is informational, not a diagnosis. Consult their doctor.

3. Exercise Logging & Programming

When user shares workout data or asks for exercise advice:

  1. Log workout to daily record: type, duration, calories, heart rate
  2. Reference references/exercise.md for programming principles
  3. Check user's injury history from profile before recommending exercises
  4. Suggest modifications for known limitations
  5. Track weekly volume and progressive overload

4. Body Metrics Tracking

When user reports weight, body fat, measurements:

  1. Update health/profile.md with new data point
  2. Calculate trend (7-day average, 30-day trend)
  3. Compare against goal trajectory
  4. Provide context: "On track" / "Ahead" / "Behind by X"

5. Supplement Guidance

When user asks about supplements or reports what they take:

  1. Reference references/supplements.md
  2. Check for interactions with user's medications (from profile)
  3. Advise timing (with meals, empty stomach, etc.)
  4. Evidence-based recommendations only — no hype

5b. Weight Loss Medication Guidance

When user asks about GLP-1, semaglutide, Ozempic, Wegovy, tirzepatide, or any weight loss medication:

  1. Reference references/medications.md for mechanism, efficacy, side effects, contraindications
  2. Cross-reference user's profile: BMI, comorbidities, current medications, medical history
  3. Use the clinical decision framework to assess whether medication is appropriate
  4. Discuss realistic expectations: typical weight loss %, timeline, muscle loss risk
  5. Emphasize: medication + lifestyle > medication alone; stopping without habits = rebound
  6. Always: this requires a physician's prescription and monitoring. Never self-prescribe.

6. Progress Reports

Generate weekly or monthly reports using templates/weekly-report.md or templates/monthly-report.md:

  • Weight/body composition trend
  • Exercise frequency and volume
  • Average daily calories and macro split
  • Notable lab results or health events
  • Adherence score
  • Next period focus areas

7. Apple Health Integration

When Apple Health data is available (via Shortcuts or export):

  1. Parse activity, workout, body measurement, and sleep data
  2. Cross-reference with manual logs
  3. Use for more accurate calorie expenditure estimates
  4. Reference references/apple-health.md for data format and fields

Reminders

Configure reminders in health/reminders.md. Supported types:

  • Wake-up / sleep
  • Meal times (with pre-meal supplement reminders)
  • Movement breaks (sedentary alerts)
  • Workout schedule
  • Medication / supplement timing
  • Weigh-in schedule

Important Guidelines

  • Privacy first: All data local, never suggest uploading health data
  • Not a doctor: Always caveat medical interpretations
  • No extremes: Never recommend <1200 cal/day, crash diets, or dangerous supplements
  • Injury-aware: Always check profile for injuries before exercise advice
  • Evidence-based: Cite clinical guidelines where possible
  • Culturally aware: Support diverse cuisines and food traditions in meal analysis
  • Metric + Imperial: Support both unit systems based on user preference

8. Weight Loss Analysis & Metabolism

Integrated from weightloss-analyzer by WellAlly Tech

When tracking weight loss progress or calculating metabolic targets:

Body Composition Assessment

  • BMI (WHO Asian standards): Normal 18.5-24, Overweight 24-28, Obese ≥28
  • Body fat: Male normal 15-20%, elevated 20-25%, obese >25%
  • Waist circumference: Male ≥90cm = abdominal obesity risk
  • Waist-to-hip ratio: Male ≥0.9 = abdominal obesity
  • Ideal weight: BMI method = height(m)² × 22; Broca = (height(cm) - 100) × 0.9

Metabolic Rate Calculation

  • Mifflin-St Jeor (recommended):

- Male: BMR = (10 × weight_kg) + (6.25 × height_cm) - (5 × age) + 5 - Female: BMR = (10 × weight_kg) + (6.25 × height_cm) - (5 × age) - 161

  • Katch-McArdle (body fat based): BMR = 370 + (21.6 × lean_mass_kg)
  • TDEE = BMR × activity factor (sedentary 1.2 / light 1.375 / moderate 1.55 / high 1.725)

Energy Deficit Management

  • Deficit = TDEE - intake + exercise burn
  • 1kg fat ≈ 7700 kcal; safe loss rate: 0.5-1kg/week (deficit 500-1000 kcal/day)
  • Minimum intake: male 1500 kcal/day, female 1200 kcal/day, absolute min = BMR × 1.2

Phase Management

  • Weight loss phase: Track rate, monitor speed, adjust deficit
  • Plateau detection: 2+ weeks with <0.5kg change → consider metabolic adaptation, water retention, muscle gain
  • Maintenance phase: Target weight ±2kg; monitor and adjust promptly

9. Sleep Analysis

Integrated from sleep-analyzer by WellAlly Tech

When analyzing sleep patterns or providing sleep improvement advice:

Sleep Quality Assessment

  • Duration trend: Track average sleep hours over time
  • Sleep efficiency: Time asleep / time in bed (target >85%)
  • Sleep latency: Time to fall asleep (>30min = concern)
  • Night awakenings: Count and duration
  • Sleep consistency score: Variability in bed/wake times (0-100)
  • Social jetlag: Weekend vs weekday sleep difference

Sleep Problem Identification

  • Insomnia types: Onset difficulty, maintenance difficulty, early waking, mixed
  • Sleep apnea risk: STOP-BANG screening (score ≥3 = refer to doctor)
  • Sleep debt: Ideal duration minus actual duration accumulated over time

Sleep-Health Correlations

  • Sleep ↔ Exercise: Exercise days vs rest days sleep quality; exercise timing effects
  • Sleep ↔ Diet: Caffeine cutoff (2pm), alcohol impact, late meals
  • Sleep ↔ Mood: Bidirectional relationship, stress impact on latency
  • Sleep ↔ Weight: Poor sleep → increased appetite hormones, weight gain risk

Improvement Recommendations (Priority Order)

  1. Fix wake time consistency (including weekends)
  2. Establish pre-sleep routine (devices off 30min before)
  3. Optimize environment (18-22°C, dark, quiet)
  4. Lifestyle: move exercise earlier, caffeine before 2pm, no alcohol 3h before bed

10. Advanced Nutrition Analysis

Integrated from nutrition-analyzer by WellAlly Tech

Extends Workflow #1 with deeper nutritional analysis:

Micronutrient Tracking

  • Track vitamins (A, C, D, E, K, B-complex) and minerals (Ca, Fe, Mg, Zn, Se, K, Na)
  • Calculate RDA achievement rate per nutrient
  • Status classification: <50% severe deficiency, 50-75% insufficient, 75-100% approaching, 100-150% adequate, >150% high/check UL

Nutritional Quality Scoring

  • Nutrient density score (0-10): Vitamins achieved (40%) + Minerals achieved (30%) + Fiber (20%) + Limiting nutrients penalty (10%)
  • Food diversity score: Number of distinct food groups per day/week
  • Balanced diet score: Macro ratio alignment with targets

Meal Pattern Analysis

  • Eating window duration (hours between first and last meal)
  • Meal frequency and timing consistency
  • Weekday vs weekend dietary differences
  • Sodium/potassium ratio tracking (target K:Na > 2.0)

Key Nutrient Safety Boundaries

  • Vitamin A: UL 3000μg/day long-term
  • Vitamin D: UL 100μg/day long-term
  • Iron: UL 45mg/day long-term
  • Sodium: target <2300mg/day (ideal <1500mg)
  • Persistent intake <1200 kcal/day → flag malnutrition risk

11. Health Trend Analysis

Integrated from health-trend-analyzer by WellAlly Tech

For longitudinal health monitoring and multi-dimensional trend analysis:

Multi-Dimension Tracking

  • Weight/BMI trend: Direction, rate of change, goal trajectory
  • Symptom patterns: Frequency, severity, triggers, seasonal patterns
  • Medication adherence: Compliance rate, missed dose patterns
  • Lab result trends: Longitudinal biomarker tracking with reference ranges
  • Mood & sleep: Bidirectional correlations

Correlation Engine

  • Medication ↔ Symptoms: Did starting a new med correlate with symptom changes?
  • Lifestyle ↔ Outcomes: Diet/sleep/exercise impact on symptoms and mood
  • Treatment effectiveness: Before/after comparison for interventions (e.g., tirzepatide)

Change Detection & Alerts

  • Significant changes: Rapid weight change (>1kg/week), new symptoms, medication changes
  • Deterioration patterns: Early identification of health decline
  • Improvement recognition: Highlight positive trends
  • Threshold alerts: Approaching dangerous levels (BMI extremes, blood pressure spikes)

Predictive Insights

  • Risk assessment based on trend direction and velocity
  • Plateau prediction for weight loss phases
  • Preventive recommendations based on pattern recognition

12. Fitness & Exercise Analysis

Integrated from fitness-analyzer by WellAlly Tech

Extends Workflow #3 with deeper exercise analytics:

Exercise Trend Analysis

  • Volume trends: Duration, distance, calories burned over time
  • Frequency trends: Weekly exercise days, consistency score (0-100)
  • Intensity distribution: Low/moderate/high intensity ratio
  • Type distribution: Balance between cardio, strength, flexibility

Progress Tracking

  • Running: Pace improvement, distance progression, HR at same pace
  • Strength: Weight increases, volume (sets × reps × weight), RPE trends
  • Endurance: Duration extension, distance growth
  • Recovery: Resting HR trend as fitness indicator

Exercise Habit Analysis

  • Preferred exercise times (morning/afternoon/evening)
  • Consistency score: How regular is the exercise pattern?
  • Rest day distribution and recovery adequacy
  • Social jetlag equivalent for exercise (weekday vs weekend patterns)

Exercise-Health Correlations

  • Exercise ↔ Weight: Calorie expenditure vs weight change
  • Exercise ↔ Blood pressure: Long-term BP reduction from regular activity
  • Exercise ↔ Sleep: Exercise timing and sleep quality impact
  • Exercise ↔ Mood: Exercise as mood regulation tool

MET-Based Calorie Calculation

  • Walking (3-5 km/h): 3.5-5 MET
  • Jogging (8 km/h): 8 MET
  • Running (10 km/h): 10 MET
  • Swimming: 6-10 MET
  • Strength training: 5 MET
  • Calories = MET × weight(kg) × hours

Safety Signals

  • Exercise HR > 95% max HR → flag
  • Resting HR > 100 bpm → flag
  • 7+ consecutive high-intensity days → overtraining risk
  • Weight loss > 1kg/week → potentially unhealthy

Disclaimer / 免责声明

⚠️ This skill is for informational and educational purposes only. It does not provide medical diagnosis, treatment, or professional health advice. Always consult a qualified healthcare provider for medical concerns.

⚠️ 本技能提供的所有健康、营养、运动建议仅供参考,不构成医疗诊断或治疗建议。如有健康问题,请咨询专业医生。

Acknowledgments

Sections 8-12 incorporate knowledge from OpenClaw-Medical-Skills by WellAlly Tech and MD BABU MIA, PhD (Biomedical AI Team). Original skills: weightloss-analyzer, sleep-analyzer, nutrition-analyzer, health-trend-analyzer, fitness-analyzer. Licensed under MIT. Thank you for the excellent open-source contributions to health AI! 🙏

平台分布

Codex

33.99%
按下载量换算385

Claude

30.62%
按下载量换算347

Cursor

17.89%
按下载量换算203

Gemini CLI

9.72%
按下载量换算110

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills