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get_hydration

Retrieve daily hydration data for any date, including water intake in ml, goal, and sweat loss estimate. Get your Garmin hydration log to track fluid balance.

Instructions

Hydration log for a day: intake in ml, goal, sweat loss estimate.

Args: date: Calendar date in YYYY-MM-DD format. Defaults to today.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoCompacted Garmin payload; null if unavailable.
noteNoExplains missing data or truncation.
paramsNoParameters used.
sourceYesGarmin Connect API method the data came from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
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 discloses the default behavior (date defaults to today) and the type of data returned. However, it does not mention permissions, error handling, or whether the data is read-only (though the 'get' prefix suggests so). This is minimal but not misleading.

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 two sentences: the first front-loads the purpose and outcome fields, the second explains the single parameter concisely. No filler words or redundant 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?

Despite having an output schema (not shown), the description names the key fields (intake, goal, sweat loss) and explains the default behavior. For a simple one-parameter read tool, this provides sufficient context for an agent to call it correctly, though it could benefit from a note on timezone handling or data granularity.

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?

The schema only shows a date parameter with a null default, but the description clarifies that the date is a calendar date in YYYY-MM-DD format and that it defaults to today. This adds meaningful semantic meaning beyond the schema, which is essential since schema coverage is 0%.

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?

The description clearly states the verb 'get' and the resource 'hydration log for a day', specifying the data fields (intake, goal, sweat loss). This distinguishes it from sibling tools like get_nutrition or get_lifestyle_log, as there is no other hydration-specific tool in the list.

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

Usage Guidelines3/5

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

The description implies usage for retrieving daily hydration data but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. Among the many sibling tools, none overlap directly with hydration, so the context is fairly clear, but explicit guidance is absent.

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