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JohanBellander

garmin-mcp-server

get_race_predictions

Get predicted race times for 5K, 10K, half marathon, and marathon based on your current fitness data from Garmin Connect.

Instructions

Get race time predictions based on current fitness. Returns predicted times for 5K, 10K, half marathon, and marathon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full transparency burden. It discloses that predictions are based on current fitness and that it returns four distance-specific times. However, it does not clarify what 'current fitness' relies on, whether recent activity data is required, or if there are any limitations or assumptions in the prediction. The read-only nature is implied by 'Get' but not explicitly stated.

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 two short sentences with no filler. The first sentence states the action and basis, and the second enumerates the exact outputs. It is front-loaded with the primary purpose and every word contributes necessary information.

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

Completeness4/5

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

For a tool with no parameters and an output schema, the description is largely complete: it tells the agent what the tool does and what it returns. The main missing elements are explicit prerequisites or limitations, such as whether outdated fitness data would still produce a prediction or whether the user must have a recent activity logged. These are minor gaps for a simple no-argument read operation.

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 input schema has zero properties and therefore schema description coverage is 100% by default, but there are no parameters to document. With no parameters, the description does not need to explain argument meanings; it instead clarifies the output and basis. This meets the baseline appropriate for a zero-parameter tool.

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 clearly identifies the tool as providing race time predictions and enumerates the specific distances (5K, 10K, half marathon, marathon). This specificity distinguishes it from related siblings like get_personal_records, which provide historical records, and get_endurance_score, which returns a score. However, it does not explicitly mention or contrast any sibling tool, so it stops one step short of full differentiation.

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

Usage Guidelines3/5

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

The phrase 'based on current fitness' implies the tool should be used when the agent needs predicted race times derived from a user's present fitness level. Yet the description gives no explicit when-to-use guidance, no exclusions, and no mention of alternative tools such as get_endurance_score or get_vo2max. Thus the usage context is only implied, not stated.

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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