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Garmin Connect MCP Server

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Get Primary Training Device

get_primary_training_device
Read-only

Retrieve your primary training device and view device priority settings to manage which Garmin device records activities.

Instructions

Get information about the primary training device and device priorities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.3.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The readOnlyHint and openWorldHint annotations already declare that this is a safe read operation. The description adds 'information about the primary training device and device priorities,' but this is more about scope than behavior. No additional behavioral traits (e.g., return format, rate limits, side effects) are disclosed, so it doesn't significantly exceed the annotations. No contradiction with annotations is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded and to the point. It contains no fluff or redundant wording. Every word adds value, specifying the subject (primary training device) and an additional aspect (priorities). This is a model of efficient description writing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema), the description is minimally adequate but vague. It doesn't specify what 'information' is returned (e.g., device ID, name, fitness level) or clarify what 'device priorities' means. The absence of an output schema makes the description the primary source of true return value knowledge, and this description leaves that ambiguous. For a read-only, no-argument tool, more specificity about the output would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema has no properties. Per the calibration rules, the baseline for 0 params is 4. The description doesn't need to explain parameters, and it doesn't complicate matters. The description's mention of 'information' and 'device priorities' gives slight context about what to expect from the invocation, but since there are no arguments, this dimension is inherently satisfied.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose clearly: 'Get information about the primary training device and device priorities.' This is a specific verb (Get) and resource (primary training device), and it adds 'device priorities' to distinguish from generic device tools. However, it doesn't explicitly differentiate from siblings like get_devices or get_device_settings, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, exclusions, or alternative tools, even though siblings like get_devices and get_device_settings exist. This leaves the agent to infer usage based on the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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