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JJRPF

Garmin MCP Server

by JJRPF

add_hydration_data

Record water consumption in milliliters with a date and timestamp to log hydration data for accurate daily fluid tracking.

Instructions

Add hydration data

Args: value_in_ml: Amount of liquid in milliliters cdate: Date in YYYY-MM-DD format timestamp: Timestamp in YYYY-MM-DDThh:mm:ss.sss format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cdateYes
timestampYes
value_in_mlYes

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

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral implications. It only restates the addition of hydration data plus parameter formats, without noting side effects, validation behavior, idempotency, or authorization requirements.

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 concise and front-loaded with the core action, followed by a clean argument list with no fluff. It is efficiently structured, though it could be slightly more informative without becoming bloated.

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 simple three-parameter write tool, the parameter documentation is adequate and the output schema covers return values. However, the lack of usage guidance and behavioral context leaves notable gaps, especially given the absence of annotations.

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%, so the parameter explanations in the description carry the meaning. All three parameters are described with useful semantics: value in milliliters, date format, and timestamp format, which goes beyond the bare schema.

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 a specific action (Add) and resource (hydration data), making the tool's purpose obvious. It is distinguishable from the sibling get_hydration_data, which retrieves data rather than writing it.

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 on when to use this tool versus alternatives, no prerequisites, and no mention of the corresponding retrieval tool. Usage must be inferred entirely from the tool name and the sibling list.

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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