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kavakoss

mcp-garmin-connect

by kavakoss

get_recent_load

Retrieve training volume by sport for a selected number of past days to monitor workload and plan workout balance.

Instructions

Training volume aggregated by sport over the last N days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.2.0
    • addedInput schema / properties / days / description
      Added value: +"Lookback window in days."
    • addedInput schema / properties / days / maximum
      Added value: +365
    • addedInput schema / properties / days / minimum
      Added value: +1
  2. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that the result is an aggregation grouped by sport rather than raw activities, which is meaningful context. It omits any mention of read-only safety, auth needs, or data source, but these are low-risk for a simple aggregation and an output schema exists.

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?

A single tight sentence with zero filler, and the aggregation scope is front-loaded before the time window. Nothing is wasted.

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?

The tool is simple (one optional parameter, output schema present), so the description need not explain return values or bounds. It is nearly complete, with the only real gap being lack of differentiation from the closely named sibling get_training_load.

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

Parameters3/5

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

Schema description coverage is 100% and the single 'days' parameter is fully documented in the schema as 'Lookback window in days.' The description reinforces the windowing concept ('last N days') but adds no syntax, bounds, or default information beyond the schema, so baseline 3 applies.

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 names a specific resource and scope: training volume aggregated by sport over a configurable day window. It is far more specific than the bare name 'get_recent_load'. However, it does not differentiate itself from sibling 'get_training_load', leaving ambiguity about which load tool to pick.

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?

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives such as get_training_load or get_fitness. The only hint is the word 'recent', which is implied usage at best.

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