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pluton74mac

garmin-mcp-triathlon

by pluton74mac

get_training_readiness_composite

Retrieve Garmin's training readiness score and factor breakdown to inform coaching decisions for today's session.

Instructions

Get Garmin's training readiness score with its factor breakdown.

Returns Garmin's own score and the percentage each of its six factors contributed — sleep, recovery time, HRV, acute load, sleep history, stress history. No interpretation: what the score means for today's session is a coaching decision.

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.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the factor breakdown and explicitly bounds the tool's scope (raw score, no interpretation), which is genuine added context. It is silent on data-availability behavior (e.g. what is returned when no readiness data exists for the date) and on whether the read requires a synced device.

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?

Front-loaded: the purpose and the return composition come first, followed by the scope disclaimer, then the argument. Every sentence earns its place; the 'Args:' block is slightly formal/redundant against the schema but conveys the date format.

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?

An output schema exists, so return values need not be re-explained (though they usefully are). The remaining gap is sibling routing in a family dense with readiness/status tools, plus no mention of data-availability failure modes — the description is adequate but incomplete for this context.

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?

One parameter with 0% schema description coverage — the schema only says type string, title 'Date'. The description compensates by specifying the expected format, 'Date in YYYY-MM-DD format', which is exactly the information the schema omits. It does not cover edge cases like date ranges or future dates.

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?

Specific verb + resource ('Get Garmin's training readiness score') with the return composition spelled out: the score plus the percentage contribution of six named factors. However, it never distinguishes itself from close siblings like get_training_readiness or get_morning_training_readiness, so the agent cannot tell from the description alone which of the three to call.

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 when-to-use guidance is given. The line 'No interpretation: what the score means for today's session is a coaching decision' scopes the tool's output but does not tell the agent when to pick this over get_training_readiness or get_morning_training_readiness, nor does it state any prerequisite such as needing recent device data.

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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