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log_custom_food

Log a food item to a meal on a specific date and time using Garmin or FatSecret food IDs. Automatically assigns the meal from meal_time, falling back to snacks if no meal matches.

Instructions

Log a food item to a meal on a date

Adds a food entry to the nutrition log. The meal is determined automatically by matching meal_time against each meal's startTime/endTime window; falls back to SNACKS if no window matches.

Food sources:

  • "GARMIN" (default): user's custom food library. Use get_custom_foods to find food_id and serving_id.

  • "FATSECRET": branded/catalog food from FatSecret. Use search_foods to find food_id and serving_id. Pass the source value from the search_foods result (e.g. "FATSECRET").

Garmin custom food IDs are 32-char hex UUIDs; FatSecret IDs are numeric strings (e.g. "4132350"). Passing the wrong source for a given food_id returns a 400 from Garmin.

Args: meal_date: Date in YYYY-MM-DD format meal_time: Time in HH:MM:SS format (e.g. "12:30:00", account timezone) food_id: Food ID from get_custom_foods (GARMIN) or search_foods (FATSECRET) serving_id: Serving ID from get_custom_foods or search_foods serving_qty: Number of servings (default 1) source: Food namespace — "GARMIN" (default) or "FATSECRET"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoGARMIN
food_idYes
meal_dateYes
meal_timeYes
serving_idYes
serving_qtyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of explaining behavior. It discloses that the operation adds a food entry, describes the automatic meal determination with SNACKS fallback, and specifies the 400 error condition when the wrong source is passed. This is more than minimal behavioral context, though it does not mention permissions or reversibility.

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 well-organized with a summary, explanatory paragraphs, and a clear Args list. It is slightly repetitive in mentioning the source of food IDs, but the structure makes it easy to scan and the length is appropriate for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all necessary invocation context: how meal time maps to meals, how to obtain food/serving IDs, the meaning of the source parameter, and potential error behavior. An output schema exists, so omitting return details is acceptable.

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?

The Args section provides thorough explanations for all six parameters, including date/time formats, defaults, and the exact origin of food_id and serving_id. Since the schema has no descriptions, this fully compensates and leaves no ambiguity about parameter meaning.

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 action: 'Log a food item to a meal on a date' and elaborates that it adds a food entry to the nutrition log. It distinguishes itself from sibling tools by specifying the food sources (GARMIN/FATSECRET) and the need for food/serving IDs, making its purpose unambiguous.

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?

The description provides concrete usage instructions, telling users to call get_custom_foods or search_foods to obtain the required IDs and explaining the source parameter. It does not explicitly contrast with the similar log_food sibling, but the prerequisites and source handling give sufficient guidance for when to use this tool.

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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