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Garmer

Extract health and fitness data from Garmin Connect including activities, sleep, heart rate, stress, steps, and body composition. Use when the user asks about t

Introduction

# 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:

```bash 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:

```bash garmer status ```

## Available Commands

### Daily Summary

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

```bash 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):

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

### Activities

List recent fitness activities:

```bash 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:

```bash # 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:

```bash 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:

```bash # 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

```bash # 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:

```python 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="[email protected]", password="pass") ```

### User Profile

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

# Get registered devices devices = client.get_user_devices() ```

### Daily Summary

```python # 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

```python # 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

```python # 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

```python # 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

```python # 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

```python # 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

```python # 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

```python # 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

```python # 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?":

```bash garmer snapshot --json ```

### Activity Analysis

When a user asks about workouts or exercise:

```bash garmer activities --limit 10 ```

### Trend Analysis

When analyzing health trends over time:

```bash 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:

```bash 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`.

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