Building My First Agent: “Inner Scout” with Garmin, Finch, and Zapier

I’m in the early stages of creating something I’m calling Inner Scout—a personal system that helps me work with my body, energy, and emotions, instead of pushing through them blindly. The goal is to build a daily feedback loop that gently answers the question:

“What kind of day is this and what do I need to support it?”

This system pulls from my Garmin watch, Finch app, and eventually my Oura ring, weather data, and calendar. For now, I’m prototyping the concept using Zapier, Google Sheets, and FitnessSyncer. Here’s what I’ve done so far, what I’m learning, and where it’s headed.

Step 1: Syncing Garmin Activity Data

Since Garmin doesn’t connect directly to Zapier, I used FitnessSyncer to get my workouts into a Google Sheet. Every time I go for a walk, bike ride, or workout, it logs:

  • Date

  • Activity type

  • Duration

  • Distance

  • Average heart rate

This became the foundation of my daily data layer.

Step 2: Tracking Stress & Mood (Finch-Inspired)

While I plan to fully integrate mood tracking from Finch, I’m starting with a manual system. Each day, I log:

  • A 1–5 stress score

  • A mood word (like “tired” or “clear”)

  • A short note about the day

Eventually, Finch entries and mood streaks will be automated into this flow. For now, it’s a great way to establish patterns and test prompts.

Step 3: Automating Data Collection with Zapier

I built a simple Zapier setup:

  • Zap 1: Every new activity from FitnessSyncer → add a row in my Google Sheet

  • Zap 2: Daily mood check-in (entered manually or prompted by a recurring notification) → add to the same sheet

This gave me a centralized place to compare how my body was doing and how I felt about the day.

Step 4: Adding Local Weather Data

Environmental context matters too. I’ve started pulling in local weather data each day using the OpenWeatherMap API, logged alongside my other data points:

  • Temperature

  • Humidity

  • Precipitation

  • Sunrise/sunset times

  • Barometric pressure (eventually)

Why? Because I’ve noticed that:

  • Humidity messes with my mood

  • Rainy days correlate with lower productivity

  • Sunny, dry mornings feel creatively energizing

Even this early on, I’ve spotted trends I wouldn’t have otherwise linked to physical or emotional states.

Step 5: Visualizing and Comparing the Data

Here’s a simplified view of how I’m currently structuring the sheet:

DateActivityDurationHR AvgStressWeatherNotes6/01/2024Running30 min145 bpm372°F ☀️Felt relaxed after run6/02/2024Cycling45 min135 bpm485°F ☁️ HumidStressful, sticky, no breeze6/03/2024Walking25 min110 bpm268°F 🌤️Calm evening walk

I’m using:

  • Line and scatter charts to explore correlations

  • Dual-axis graphs to overlay HR and stress scores

  • Google Sheets formulas to calculate running averages and trends

Where It’s Going Next

What I have now is a spreadsheet and some automation—but the vision is bigger.

Coming Soon:

  • Oura Ring data for sleep, HRV, and temperature

  • Finch mood entries pulled in automatically

  • Google Calendar integration for meeting load and mental context

  • A custom Relay.app Agent that reviews all this data each morning and gently suggests:

    • What kind of work to focus on

    • When to rest

    • Whether to go hard or go easy

Eventually, Inner Scout will feel like a personal wellness assistant, quietly guiding my day based on signals I usually ignore.

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