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Apple Health 数据查询分析技能 - 本地SQLite健康数据库管理与可视化工具

health-data by glebis/claude-skills

56 周安装量

68 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/glebis/claude-skills --skill health-data

Python Web框架数据分析健康科技

🇨🇳中文介绍

Apple Health 数据查询技能

查询并分析本地 SQLite 数据库中的健康数据，该数据库包含超过 630 万条记录，涵盖 43 项健康指标。

数据库位置

~/data/health.db

查询方法

1. Python 脚本（推荐用于常规查询）

使用 scripts/health_query.py 进行预置查询，并自动格式化输出：

# 每日摘要
python ~/.claude/skills/health-data/scripts/health_query.py --format markdown daily --date 2025-11-29

# 每周趋势
python ~/.claude/skills/health-data/scripts/health_query.py --format json weekly --weeks 4

# 睡眠分析
python ~/.claude/skills/health-data/scripts/health_query.py --format fhir sleep --days 7

# 最新生命体征
python ~/.claude/skills/health-data/scripts/health_query.py vitals

# 活动圆环
python ~/.claude/skills/health-data/scripts/health_query.py --format json activity --days 30

# 锻炼历史
python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running

# 自定义 SQL
python ~/.claude/skills/health-data/scripts/health_query.py --format json query "SELECT * FROM workouts LIMIT 5"

输出格式： markdown、、、

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2. 直接 SQL 查询（用于自定义/临时查询）

要进行灵活的查询，请直接对数据库运行 SQL。请参阅 references/schema.md 了解表结构和查询模板。

sqlite3 ~/data/health.db "SELECT AVG(value) FROM health_records WHERE record_type LIKE '%HeartRate%' AND start_date LIKE '2025-11%'"

获取今日关键指标：

python ~/.claude/skills/health-data/scripts/health_query.py daily

返回：步数、卡路里、心率（平均/最小/最大）、锻炼分钟数、距离、活动圆环状态。

比较周度表现：

python ~/.claude/skills/health-data/scripts/health_query.py weekly --weeks 4

返回：每周平均每日步数、静息心率、锻炼分钟数、锻炼次数。

分析睡眠模式：

python ~/.claude/skills/health-data/scripts/health_query.py sleep --days 14

返回：夜间时长、睡眠阶段（核心、深度、快速眼动）、平均睡眠小时数。

获取最近的生命体征读数：

python ~/.claude/skills/health-data/scripts/health_query.py vitals

返回：心率、心率变异性、静息心率、血氧、呼吸频率及其时间戳。

追踪圆环完成情况：

python ~/.claude/skills/health-data/scripts/health_query.py activity --days 30

返回：每日圆环值/目标、完成百分比、完美天数。

回顾锻炼记录：

python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running

返回：锻炼类型、时长、距离、卡路里、按类型汇总。

Markdown（默认）

人类可读的表格和列表。最适合报告和摘要。

结构化数据，便于程序化使用：

{
  "date": "2025-11-29",
  "metrics": {
    "steps": 8542,
    "active_calories": 450.5,
    "heart_rate": {"avg": 72.3, "min": 52, "max": 145}
  }
}

医疗保健互操作性格式。输出为包含使用 LOINC 编码的 Observation 资源的 FHIR Bundle。请参阅 references/fhir_mappings.md 了解编码映射。

终端友好的输出，包含条形图和统计信息：

============================================================
  DAILY SUMMARY - 2025-11-29
============================================================

METRICS
----------------------------------------
  steps                      2620
  active_calories           234.5
  heart_rate           avg:  67.5  min:  52  max: 108

ACTIVITY RINGS
----------------------------------------
  move       [███████░░░░░░░░░░░░░]  36.7% (238/650)
  exercise   [░░░░░░░░░░░░░░░░░░░░]   0.0% (0/35)
  stand      [████████████████████] 100.0% (10/10)

对于临时查询，请使用 references/schema.md 中的这些模式：

按小时统计心率（昼夜节律模式）：

SELECT strftime('%H', start_date) as hour, ROUND(AVG(value), 1) as avg_hr
FROM health_records
WHERE record_type = 'HKQuantityTypeIdentifierHeartRate'
AND value BETWEEN 40 AND 200
GROUP BY hour ORDER BY hour;

本月每日步数：

SELECT DATE(start_date) as day, SUM(value) as steps
FROM health_records
WHERE record_type = 'HKQuantityTypeIdentifierStepCount'
AND start_date >= DATE('now', 'start of month')
GROUP BY day ORDER BY day;

睡眠质量（深度 + 快速眼动睡眠小时数）：

SELECT DATE(start_date) as night,
       ROUND(SUM(duration_minutes)/60.0, 1) as quality_hours
FROM sleep_sessions
WHERE sleep_stage IN ('Deep', 'REM')
GROUP BY night ORDER BY night DESC LIMIT 14;

SELECT REPLACE(workout_type, 'HKWorkoutActivityType', '') as type,
       COUNT(*) as count, ROUND(SUM(duration_minutes)) as total_min
FROM workouts
WHERE start_date >= DATE('now', '-30 days')
GROUP BY type ORDER BY count DESC;

可用的记录类型

数据库包含 43 种健康指标类型，包括：

生命体征： 心率、心率变异性、静息心率、血氧、呼吸频率、血压

活动： 步数、距离、活动卡路里、基础代谢卡路里、爬楼层数、锻炼时间、站立时间

移动能力： 步行速度、步长、步行不对称性、楼梯速度、步行稳定性

身体： 体重、身体质量指数、体脂率

音频： 环境噪音、耳机暴露

其他： 最大摄氧量、日照时间、紫外线暴露

记录： 超过 630 万条测量数据
日期范围： 2015-10-13 至今
锻炼： 1,435 次记录
睡眠记录： 40,514 条记录
活动天数： 1,875 条每日摘要

health_query.py - 主要的查询工具，支持 Markdown/JSON/FHIR 输出

schema.md - 数据库模式、记录类型映射、SQL 查询模板
fhir_mappings.md - LOINC 编码和 FHIR R4 模板

找不到数据库： 确保 ~/data/health.db 存在。从 /Users/server/apple_health_export/ 运行导入脚本：

python import_health.py --status

指定日期范围内无数据： 检查可用日期范围：

SELECT MIN(start_date), MAX(start_date) FROM health_records;

异常值： 筛选生理有效范围（例如，心率 40-200 bpm）：

WHERE value BETWEEN 40 AND 200

2026 年 1 月 24 日

🇺🇸English

Apple Health Data Query Skill

Query and analyze health data from the local SQLite database containing 6.3M+ records across 43 health metrics.

Database Location

~/data/health.db

Query Methods

1. Python Script (Recommended for Common Queries)

Use scripts/health_query.py for pre-built queries with automatic formatting:

# Daily summary
python ~/.claude/skills/health-data/scripts/health_query.py --format markdown daily --date 2025-11-29

# Weekly trends
python ~/.claude/skills/health-data/scripts/health_query.py --format json weekly --weeks 4

# Sleep analysis
python ~/.claude/skills/health-data/scripts/health_query.py --format fhir sleep --days 7

# Latest vitals
python ~/.claude/skills/health-data/scripts/health_query.py vitals

# Activity rings
python ~/.claude/skills/health-data/scripts/health_query.py --format json activity --days 30

# Workout history
python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running

# Custom SQL
python ~/.claude/skills/health-data/scripts/health_query.py --format json query "SELECT * FROM workouts LIMIT 5"

Output formats: markdown, json, fhir, ascii

2. Direct SQL (For Custom/Ad-hoc Queries)

For flexible queries, run SQL directly against the database. See references/schema.md for table structures and query templates.

sqlite3 ~/data/health.db "SELECT AVG(value) FROM health_records WHERE record_type LIKE '%HeartRate%' AND start_date LIKE '2025-11%'"

Pre-built Queries

Daily Health Summary

Get today's key metrics:

python ~/.claude/skills/health-data/scripts/health_query.py daily

Returns: steps, calories, heart rate (avg/min/max), exercise minutes, distance, activity ring status.

Weekly Trends

Compare week-over-week performance:

python ~/.claude/skills/health-data/scripts/health_query.py weekly --weeks 4

Returns: average daily steps, resting HR, exercise minutes, workout count per week.

Sleep Analysis

Analyze sleep patterns:

python ~/.claude/skills/health-data/scripts/health_query.py sleep --days 14

Returns: nightly duration, sleep stages (Core, Deep, REM), average sleep hours.

Latest Vitals

Get most recent vital readings:

python ~/.claude/skills/health-data/scripts/health_query.py vitals

Returns: Heart Rate, HRV, Resting HR, Blood Oxygen, Respiratory Rate with timestamps.

Activity Rings

Track ring completion:

python ~/.claude/skills/health-data/scripts/health_query.py activity --days 30

Returns: daily ring values/goals, completion percentages, perfect day count.

Workout History

Review exercise sessions:

python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running

Returns: workout type, duration, distance, calories, summary by type.

Output Formats

Markdown (default)

Human-readable tables and lists. Best for reports and summaries.

JSON

Structured data for programmatic use:

{
  "date": "2025-11-29",
  "metrics": {
    "steps": 8542,
    "active_calories": 450.5,
    "heart_rate": {"avg": 72.3, "min": 52, "max": 145}
  }
}

FHIR R4

Healthcare interoperability format. Outputs as FHIR Bundle with Observation resources using LOINC codes. See references/fhir_mappings.md for code mappings.

ASCII

Terminal-friendly output with bar charts and statistics:

============================================================
  DAILY SUMMARY - 2025-11-29
============================================================

METRICS
----------------------------------------
  steps                      2620
  active_calories           234.5
  heart_rate           avg:  67.5  min:  52  max: 108

ACTIVITY RINGS
----------------------------------------
  move       [███████░░░░░░░░░░░░░]  36.7% (238/650)
  exercise   [░░░░░░░░░░░░░░░░░░░░]   0.0% (0/35)
  stand      [████████████████████] 100.0% (10/10)

Common SQL Patterns

For ad-hoc queries, use these patterns from references/schema.md:

Heart rate by hour (circadian pattern):

SELECT strftime('%H', start_date) as hour, ROUND(AVG(value), 1) as avg_hr
FROM health_records
WHERE record_type = 'HKQuantityTypeIdentifierHeartRate'
AND value BETWEEN 40 AND 200
GROUP BY hour ORDER BY hour;

Steps per day this month:

SELECT DATE(start_date) as day, SUM(value) as steps
FROM health_records
WHERE record_type = 'HKQuantityTypeIdentifierStepCount'
AND start_date >= DATE('now', 'start of month')
GROUP BY day ORDER BY day;

Sleep quality (deep + REM hours):

SELECT DATE(start_date) as night,
       ROUND(SUM(duration_minutes)/60.0, 1) as quality_hours
FROM sleep_sessions
WHERE sleep_stage IN ('Deep', 'REM')
GROUP BY night ORDER BY night DESC LIMIT 14;

Workout summary:

SELECT REPLACE(workout_type, 'HKWorkoutActivityType', '') as type,
       COUNT(*) as count, ROUND(SUM(duration_minutes)) as total_min
FROM workouts
WHERE start_date >= DATE('now', '-30 days')
GROUP BY type ORDER BY count DESC;

Record Types Available

The database contains 43 health metric types including:

Vitals: Heart Rate, HRV, Resting HR, Blood Oxygen, Respiratory Rate, Blood Pressure

Activity: Steps, Distance, Active Calories, Basal Calories, Flights Climbed, Exercise Time, Stand Time

Mobility: Walking Speed, Step Length, Walking Asymmetry, Stair Speed, Walking Steadiness

Body: Weight, BMI, Body Fat %

Audio: Environmental Noise, Headphone Exposure

Other: VO2 Max, Time in Daylight, UV Exposure

Data Coverage

Records: 6.3M+ measurements
Date range: 2015-10-13 to present
Workouts: 1,435 sessions
Sleep sessions: 40,514 records
Activity days: 1,875 daily summaries

Resources

scripts/

health_query.py - Main query tool with Markdown/JSON/FHIR output

references/

schema.md - Database schema, record type mappings, SQL query templates
fhir_mappings.md - LOINC codes and FHIR R4 templates

Troubleshooting

Database not found: Ensure ~/data/health.db exists. Run the import script from /Users/server/apple_health_export/:

python import_health.py --status

No data for date range: Check available date range:

SELECT MIN(start_date), MAX(start_date) FROM health_records;

Outlier values: Filter physiologically valid ranges (e.g., heart rate 40-200 bpm):

WHERE value BETWEEN 40 AND 200

Weekly Installs

Repository

glebis/claude-skills

GitHub Stars

First Seen

Jan 24, 2026

Security Audits

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DOCX文件创建、编辑与分析完整指南 - 使用docx-js、Pandoc和Python脚本

54,000 周安装

Apple Health 数据查询分析技能 - 本地SQLite健康数据库管理与可视化工具

🇨🇳中文介绍

Apple Health 数据查询技能

数据库位置

查询方法

1. Python 脚本（推荐用于常规查询）

相关 Skills

2. 直接 SQL 查询（用于自定义/临时查询）

预置查询

每日健康摘要

每周趋势

睡眠分析

最新生命体征

活动圆环

锻炼历史

输出格式

Markdown（默认）

JSON

FHIR R4

ASCII

常用 SQL 模式

可用的记录类型

数据覆盖范围

资源

scripts/

references/

故障排除

🇺🇸English

Apple Health Data Query Skill

Database Location

Query Methods

1. Python Script (Recommended for Common Queries)

2. Direct SQL (For Custom/Ad-hoc Queries)

Pre-built Queries

Daily Health Summary

Weekly Trends

Sleep Analysis

Latest Vitals

Activity Rings

Workout History

Output Formats

Markdown (default)

JSON

FHIR R4

ASCII

Common SQL Patterns

Record Types Available

Data Coverage

Resources

scripts/

references/

Troubleshooting

最新 Skills