Skip to main content
Glama

search_foods

Search Garmin's food catalog across FatSecret and custom foods to find branded items by name, returning identifiers and macros for logging.

Instructions

Search Garmin's general food catalog (FatSecret + Garmin custom foods)

Searches across the entire food catalog including FatSecret-sourced branded and generic foods, not just the user's Garmin custom foods. Use this to find branded packaged foods by name before logging them.

Returns food_id, source, name, brand, and all available servings with macros. The source field ("FATSECRET" or "GARMIN") and food_id together identify the right routing for log_custom_food — pass both to log_custom_food's food_id and source parameters respectively.

For the user's own custom foods only, use get_custom_foods instead.

Args: query: Food name or brand to search for (e.g. "Cheerios", "Greek yogurt") start: Starting index for pagination (default 0) limit: Maximum number of results per page (default 20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
startNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the search scope, the source field values ('FATSECRET' or 'GARMIN'), and the returned fields. It doesn't mention rate limits or error behavior, but for a search operation the core behavioral traits are well covered.

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 front-loaded with a one-line summary, then expands into scope, return semantics, routing, and parameter details. Every sentence adds value, and the Args section is clearly structured. No redundant or filler content.

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 selection (when to use vs get_custom_foods), invocation (all parameters), output semantics (returned fields and source values), and downstream usage (passing food_id and source to log_custom_food). It is complete for an agent to select and call the tool correctly.

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%, so the description must fully compensate. It does: query is explained as a food name or brand with examples, start is described as the pagination starting index, and limit as the maximum results per page. Defaults are also stated.

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 opens with a specific verb and resource: 'Search Garmin's general food catalog (FatSecret + Garmin custom foods)'. It clearly distinguishes itself from get_custom_foods by stating it searches the entire catalog, not just the user's custom foods.

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

Usage Guidelines5/5

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

It explicitly says to use this tool to find branded packaged foods by name before logging them, and explicitly names get_custom_foods as the alternative for the user's own custom foods. It also explains how results route into log_custom_food, giving clear when-to-use guidance.

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

Deploy Server

Other Tools