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Glama

garmin_race_predictions

Read-only

Query your Garmin data to see predicted race times for 5K, 10K, half marathon, and full marathon.

Instructions

Predicted race times for 5K, 10K, half and full marathon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.5/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the distances covered and the predictive nature of the data, which is useful context but does not disclose more nuanced behavior such as whether predictions are based on recent training, can be missing, or are updated dynamically. The description adds some value but not rich behavioral detail.

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 short sentence with no filler. The key information (distances) is front-loaded and every word adds value. It is appropriately sized for a zero-parameter read-only tool.

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 simple, read-only, zero-parameter tool with an output schema, the description is nearly complete. It identifies the resource and the specific race distances. A minor gap is the lack of any hint about how predictions are generated or what could affect them, but given the annotations and output schema, nothing essential is missing for a correct invocation.

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?

There are zero parameters, and the schema is empty, so the baseline is 4 per calibration guidance. The description compensates by clarifying the scope of the result (5K, 10K, half, full marathon), which gives the agent a clear idea of what data will be returned even though there is nothing to configure.

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 states the resource: predicted race times for the four common race distances. It lacks an explicit verb like 'returns' or 'gets', but the noun phrase is specific enough to identify the tool's function and differentiate it from siblings like garmin_personal_records (actual records) and garmin_vo2max (a different metric).

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling health and performance tools (training_status, personal_records, vo2max), an agent could confuse race predictions with actual race history or training metrics. The description gives no context on use cases or exclusions.

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