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garmergarmer 分析

Agent Skill

garmer 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

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下载量

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:garmer(garmer 分析)
来源仓库:https://github.com/garrza/garmer
安装命令:
openclaw skills install garmer
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install garmer

简介

从 Garmin Connect 中提取健康和健身数据,包括活动、睡眠、心率、压力、步数和身体成分。当用户询问其 Garmin 数据、健身指标、睡眠分析或健康见解时使用。

SKILL.md

name
garmer
description
Extract health and fitness data from Garmin Connect including activities, sleep, heart rate, stress, steps, and body composition. Use when the user asks about their Garmin data, fitness metrics, sleep analysis, or health insights.
license
MIT
compatibility
Requires Python 3.10+, pip/uv for installation. Requires Garmin Connect account credentials for authentication.
metadata
author
MoltBot Team
version
0.1.0
moltbot
emoji
primaryEnv
GARMER_TOKEN_DIR
requires
bins
install
kind
uv
package
garmer
bins
label
Install garmer (uv)
kind
pip
package
garmer
bins
label
Install garmer (pip)

Garmer - Garmin Data Extraction Skill

This skill enables extraction of health and fitness data from Garmin Connect for analysis and insights.

Prerequisites

  1. A Garmin Connect account with health data
  2. The garmer CLI tool installed (see installation options in metadata)

Authentication (One-Time Setup)

Before using garmer, authenticate with Garmin Connect:

garmer login

This will prompt for your Garmin Connect email and password. Tokens are saved to ~/.garmer/garmin_tokens for future use.

To check authentication status:

garmer status

Available Commands

Daily Summary

Get today's health summary (steps, calories, heart rate, stress):

garmer summary
# For a specific date:
garmer summary --date 2025-01-15
# Include last night's sleep data:
garmer summary --with-sleep
garmer summary -s
# JSON output for programmatic use:
garmer summary --json
# Combine flags:
garmer summary --date 2025-01-15 --with-sleep --json

Sleep Data

Get sleep analysis (duration, phases, score, HRV):

garmer sleep
# For a specific date:
garmer sleep --date 2025-01-15

Activities

List recent fitness activities:

garmer activities
# Limit number of results:
garmer activities --limit 5
# Filter by specific date:
garmer activities --date 2025-01-15
# JSON output for programmatic use:
garmer activities --json

Activity Detail

Get detailed information for a single activity:

# Latest activity:
garmer activity
# Specific activity by ID:
garmer activity 12345678
# Include lap data:
garmer activity --laps
# Include heart rate zone data:
garmer activity --zones
# JSON output:
garmer activity --json
# Combine flags:
garmer activity 12345678 --laps --zones --json

Health Snapshot

Get comprehensive health data for a day:

garmer snapshot
# For a specific date:
garmer snapshot --date 2025-01-15
# As JSON for programmatic use:
garmer snapshot --json

Export Data

Export multiple days of data to JSON:

# Last 7 days (default)
garmer export

# Custom date range
garmer export --start-date 2025-01-01 --end-date 2025-01-31 --output my_data.json

# Last N days
garmer export --days 14

Utility Commands

# Update garmer to latest version (git pull):
garmer update

# Show version information:
garmer version

Python API Usage

For more complex data processing, use the Python API:

from garmer import GarminClient
from datetime import date, timedelta

# Use saved tokens
client = GarminClient.from_saved_tokens()

# Or login with credentials
client = GarminClient.from_credentials(email="user@example.com", password="pass")

User Profile

# Get user profile
profile = client.get_user_profile()
print(f"User: {profile.display_name}")

# Get registered devices
devices = client.get_user_devices()

Daily Summary

# Get daily summary (defaults to today)
summary = client.get_daily_summary()
print(f"Steps: {summary.total_steps}")

# Get for specific date
summary = client.get_daily_summary(date(2025, 1, 15))

# Get weekly summary
weekly = client.get_weekly_summary()

Sleep Data

# Get sleep data (defaults to today)
sleep = client.get_sleep()
print(f"Sleep: {sleep.total_sleep_hours:.1f} hours")

# Get last night's sleep
sleep = client.get_last_night_sleep()

# Get sleep for date range
sleep_data = client.get_sleep_range(
    start_date=date(2025, 1, 1),
    end_date=date(2025, 1, 7)
)

Activities

# Get recent activities
activities = client.get_recent_activities(limit=5)
for activity in activities:
    print(f"{activity.activity_name}: {activity.distance_km:.1f} km")

# Get activities with filters
activities = client.get_activities(
    start_date=date(2025, 1, 1),
    end_date=date(2025, 1, 31),
    activity_type="running",
    limit=20
)

# Get single activity by ID
activity = client.get_activity(12345678)

Heart Rate

# Get heart rate data for a day
hr = client.get_heart_rate()
print(f"Resting HR: {hr.resting_heart_rate} bpm")

# Get just resting heart rate
resting_hr = client.get_resting_heart_rate(date(2025, 1, 15))

Stress & Body Battery

# Get stress data
stress = client.get_stress()
print(f"Avg stress: {stress.avg_stress_level}")

# Get body battery data
battery = client.get_body_battery()

Steps

# Get detailed step data
steps = client.get_steps()
print(f"Total: {steps.total_steps}, Goal: {steps.step_goal}")

# Get just total steps
total = client.get_total_steps(date(2025, 1, 15))

Body Composition

# Get latest weight
weight = client.get_latest_weight()
print(f"Weight: {weight.weight_kg} kg")

# Get weight for specific date
weight = client.get_weight(date(2025, 1, 15))

# Get full body composition
body = client.get_body_composition()

Hydration & Respiration

# Get hydration data
hydration = client.get_hydration()
print(f"Intake: {hydration.total_intake_ml} ml")

# Get respiration data
resp = client.get_respiration()
print(f"Avg breathing: {resp.avg_waking_respiration} breaths/min")

Comprehensive Reports

# Get health snapshot (all metrics for a day)
snapshot = client.get_health_snapshot()
# Returns: daily_summary, sleep, heart_rate, stress, steps, hydration, respiration

# Get weekly health report with trends
report = client.get_weekly_health_report()
# Returns: activities summary, sleep stats, steps stats, HR trends, stress trends

# Export data for date range
data = client.export_data(
    start_date=date(2025, 1, 1),
    end_date=date(2025, 1, 31),
    include_activities=True,
    include_sleep=True,
    include_daily=True
)

Common Workflows

Health Check Query

When a user asks "How did I sleep?" or "What's my health summary?":

garmer snapshot --json

Activity Analysis

When a user asks about workouts or exercise:

garmer activities --limit 10

Trend Analysis

When analyzing health trends over time:

garmer export --days 30 --output health_data.json

Then process the JSON file with Python for analysis.

Data Types Available

  • Activities: Running, cycling, swimming, strength training, etc.
  • Sleep: Duration, phases (deep, light, REM), score, HRV
  • Heart Rate: Resting HR, samples, zones
  • Stress: Stress levels, body battery
  • Steps: Total steps, distance, floors
  • Body Composition: Weight, body fat, muscle mass
  • Hydration: Water intake tracking
  • Respiration: Breathing rate data

Error Handling

If not authenticated:

Not logged in. Use 'garmer login' first.

If session expired, re-authenticate:

garmer login

Environment Variables

  • GARMER_TOKEN_DIR: Custom directory for token storage
  • GARMER_LOG_LEVEL: Set logging level (DEBUG, INFO, WARNING, ERROR)
  • GARMER_CACHE_ENABLED: Enable/disable data caching (true/false)

References

For detailed API documentation and MoltBot integration examples, see references/REFERENCE.md.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算17,534

安全审计

VirusTotal

可疑

ClawScan

可疑

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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