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JJRPF

Garmin MCP Server

by JJRPF

get_training_readiness

Retrieve the training readiness score and contributing metrics for a specific date to evaluate recovery status and decide whether to push or rest.

Instructions

Get training readiness data with curated metrics

Returns training readiness score and contributing factors.

Args: date: Date in YYYY-MM-DD format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does state that the tool returns a score and contributing factors and that the data is 'curated,' which gives some insight. However, it does not explain what 'curated metrics' means, whether the readiness value has a known scale, or any other behavioral traits beyond the basic return.

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

Conciseness4/5

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

The description is short and front-loaded with the core purpose, followed by the return summary and parameter documentation. The phrase 'curated metrics' is somewhat vague and could be removed, but the overall structure is efficient and easy to parse.

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?

For a single-parameter read tool with an output schema available, the description covers the essentials: what it does and the required date format. However, the lack of any differentiation from get_morning_training_readiness and the vague 'curated metrics' wording leave a noticeable completeness gap for an agent selecting among many similar data tools.

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?

Schema description coverage is 0%, but the description compensates well by specifying the date format as YYYY-MM-DD. This adds practical meaning beyond the schema's bare string type and title. It could go further by clarifying what the date represents in relation to training readiness, but the format guidance is genuinely useful.

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 tool retrieves training readiness data and returns a readiness score plus contributing factors. However, it does not distinguish itself from the closely related sibling get_morning_training_readiness, so it misses the differentiation that would earn 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 about when to use this tool versus alternatives such as get_morning_training_readiness or get_training_status. It only documents the required date parameter, which helps invocation but not tool selection.

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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