garmin-training-toolkit-sdk 0.4.0

A robust, type-safe Python SDK for Garmin Connect data extraction.

Garmin Training Toolkit SDK

A robust, type-safe Python SDK for extracting biometric data and telemetry from Garmin Connect, optimized for autonomous agents and LLM tool-calling.

Architecture: LLM-Native & Vendor-Agnostic

The SDK has been refactored to prioritize:

1. Semantic Naming: No more cryptic Garmin fields. We use min_target, max_target, and target_type.
2. Provider Pattern: Logic is decoupled from Garmin-specific APIs. You can now use a standardized BaseBiometricProvider interface.
3. Agent-First Schema: Pydantic models include exhaustive descriptions and Literal types, allowing LLMs to understand the tool requirements with 100% accuracy from the JSON schema alone.

Installation

This project uses uv for dependency management.

# In your consumer project:
uv add git+https://github.com/restrok/garmin-training-toolkit-sdk.git#subdirectory=garmin_toolkit

Quick Start

1. Standardized Provider Interface

The recommended way to use the SDK is via the GarminProvider.

from datetime import date
from garmin_training_toolkit_sdk.core.garmin import GarminProvider

# 1. Initialize (automatically finds local tokens)
provider = GarminProvider()

# 2. Fetch Activities (Returns vendor-agnostic Protocol models)
activities = provider.get_activities(date(2026, 4, 1), date(2026, 4, 30))
latest = activities[0]
print(f"Activity: {latest.name} | Distance: {latest.distance_m}m")

# 3. Get Telemetry
telemetry = provider.get_telemetry(latest.id)
print(f"Sample HR: {telemetry.ticks[0].hr_bpm} bpm")

2. LLM-Native Workouts (Agent Friendly)

Agents can create workouts using semantic naming or high-level helpers.

from garmin_training_toolkit_sdk.protocol.workouts import create_simple_hr_workout

# High-level helper for Agents
workout = create_simple_hr_workout(
    name="Z2 Recovery Run",
    date="2026-05-01",
    bpm_min=135,
    bpm_max=145,
    duration_mins=45
)

# Upload via the provider
report = provider.upload_training_plan(workout)
print(f"Status: {report.message}")

Tool Factory (For AI Agents)

If you are building an AI Agent (LangChain, AutoGPT, etc.), you can use the ToolFactory to generate a standardized set of tools from any provider.

from garmin_training_toolkit_sdk.core.factory import ToolFactory
from garmin_training_toolkit_sdk.core.garmin import GarminProvider

provider = GarminProvider()
tools = ToolFactory.create_tools(provider)

# These tools have semantic descriptions that LLMs love:
# - get_activities
# - get_telemetry
# - upload_training_plan

Directory Structure

• core/: Provider implementations (Garmin, etc.) and the Tool Factory.
• protocol/: Vendor-agnostic Pydantic models (Activity, Telemetry, Workout).
• extractors/: Low-level data extraction logic.
• uploaders/: Logic for calendar and workout management.

Testing & Mocks

The SDK includes a MockGarminClient in testing/mock.py to allow consumers to test their pipelines without hitting Garmin's production APIs.

from garmin_training_toolkit_sdk.testing.mock import MockGarminClient
# Use in your unit tests to avoid rate limits