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Glama

get_nutrition

Retrieve daily food log and macro breakdown for any date to track calorie intake and nutrition from Garmin Connect.

Instructions

Food log and meals for a day (calories, macros) if nutrition tracking is used.

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

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It usefully discloses that the tool returns food log/meals with calories and macros and that the date defaults to today. However, it does not explain what happens if nutrition tracking is not used or no data exists for the day, leaving a meaningful behavioral gap.

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 compact sentences plus a parameter note, with the core meaning front-loaded. Every sentence earns its place, and there is no redundant restating of the tool name or schema details.

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 simple getter with one optional parameter and an output schema present, the description covers the essential calling details: what it returns, the date format, and the default. The main remaining gap is the conditional 'if nutrition tracking is used' behavior, which leaves uncertainty about the no-tracking/no-data case. Overall it is nearly complete for its complexity.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates for the only parameter: it specifies the exact date format (YYYY-MM-DD) and the default behavior (today), which are the critical semantics an agent needs. The schema itself only lists the property as string/null with a null default, so the description adds substantial value beyond the structured definition.

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 identifies the specific resource (food log/meals for a day) and the payload content (calories, macros), so an agent can tell what data this tool returns. It lacks an explicit verb like 'retrieves' but the tool name 'get_nutrition' supplies that. It does not explicitly contrast with related siblings like get_lifestyle_log or get_daily_summary, so it stops short of a 5.

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 phrase 'if nutrition tracking is used' provides a context condition, but there is no guidance on how to determine that condition or what alternative tool to prefer when it does not hold. It does not name sibling alternatives or exclusions. This is adequate implied usage, not explicit routing.

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