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log_food

Requires a Garmin Connect+ subscription (check with has_connect_plus). Logs a catalogue or custom food into a meal. Needs Connect+. PUTs /nutrition-service/food/logs with one REGULAR_LOG item and returns the whole day's log. FoodLogInput = {date, foodId, servingId, servings? = 1, time?, meal?, source? = "GARMIN", regionCode?, languageCode?}. Pass the catalogue food's source/regionCode/languageCode for a search result. Needs a mealId, which only exists after Garmin's nutrition setup in the app (400 mealId must not be null otherwise; this method throws a clearer error first). The meal is the named one, else the one whose window holds time, …

Input Schema

NameRequiredDescriptionDefault
inputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (which only cover non-readonly/openWorld/non-destructive), the description discloses the subscription/auth requirement, the underlying PUT endpoint and REGULAR_LOG payload shape, the precondition on mealId, the 400 error condition, and that it returns the whole day's log. That is substantial behavioral context an agent cannot infer from annotations.

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 key constraint (Connect+ requirement, then the mealId precondition) is front-loaded and every sentence carries information. It is dense with internal jargon and the trailing ellipsis shows it is truncated mid-sentence, which slightly hurts structure.

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?

For a nested-object mutation tool with no output schema, it covers the return value (the whole day's log), the auth prerequisite, the precondition and the failure mode. The visible truncation means some explanatory content is cut off, so it is strong but not fully complete.

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 reported at 0%, so the description carries the load: it restates the full FoodLogInput shape with defaults (servings=1, source=GARMIN) and adds cross-field guidance (pass the catalogue food's source/regionCode/languageCode for a search result). foodId and servingId still lack meaning anywhere, which keeps it below 5.

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 gives a specific verb (logs) and resource (a catalogue or custom food into a meal), and the added detail about source/regionCode/languageCode for a search result distinguishes it from create_custom_food and quick_add_food. An agent can tell exactly what this tool does without opening the schema.

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?

It clearly states prerequisites: a Garmin Connect+ subscription (with the sibling has_connect_plus named as the check) and a mealId that only exists after Garmin's in-app nutrition setup, plus the 400 failure otherwise. It stops short of explicitly contrasting when to use this versus quick_add_food, so it is clear context without full alternative routing.

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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