Skill: garrza/garmer (version 1.0.2)

--- 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: ```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="[REDACTED_SECRET]", 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`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)