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Garmer

by @garrza

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.

Versionv1.0.2
Downloads2,525
Installs2
Comments1
TERMINAL
clawhub install garmer

πŸ“– About This Skill


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: - garmer install: - id: uv kind: uv package: garmer bins: - garmer label: Install garmer (uv) - id: pip kind: pip package: garmer bins: - garmer 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.

    βš™οΈ Configuration

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