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durely
by durely

Nutrition and hydration

garmin_get_nutrition
Read-onlyIdempotent

Fetch daily food logs from Garmin Connect or linked apps, including calories, macros, meals, goal comparisons, and hydration for a chosen date range.

Instructions

Get food logged in Garmin Connect (or a linked app such as MyFitnessPal) per day: calories, carbs, protein and fat against the day's goals, and meals; plus hydration (ml) from the daily summary.

Food logs are fetched from Garmin on demand and cached. Defaults to the last 7 days, at most 31 per call.

Input Schema

NameRequiredDescriptionDefault
end_dateNoDefaults to today
start_dateNoLocal calendar date, yyyy-MM-dd
response_formatNo'markdown' for readable text (default), 'json' for complete structured datamarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, non-destructive, so the safety profile is free. The description adds real behavioral context beyond that: data is fetched on demand and cached (implying possible latency and staleness) and the 7-day default / 31-day cap. It doesn't explain cache refresh behavior or failure modes, so not a 5.

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?

Two tight sentences/short paragraphs: the first front-loads what is returned, the second carries fetch/caching and window limits. No filler, every clause carries 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?

No output schema exists, so the description must carry the return payload, and it does list the metric groups and hydration units. It lacks detail on the shape of meal entries or how goals are represented, so an agent knows what it gets only at a coarse level.

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 coverage is 100%, so baseline is 3, but the description adds the start_date default ('last 7 days') that the schema lacks and the 31-day span limit, which is genuinely new constraint information an agent needs to avoid empty or rejected calls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: get food logged in Garmin Connect (or linked apps like MyFitnessPal) per day, enumerating the returned metrics (calories, carbs, protein, fat vs goals, meals) plus hydration in ml. No sibling tool covers nutrition, and the enumerations make the scope unmistakable.

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

Usage Guidelines4/5

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

Gives the operating window ('defaults to the last 7 days, at most 31 per call'), which tells an agent how to size requests, and the data-source note implies when this tool applies versus activity/sleep/health siblings. It stops short of explicitly naming an alternative or a when-not condition, but no sibling overlaps on this data.

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