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Glama

Get food details

get_food
Read-onlyIdempotent

Get a food's complete profile by its number: type, scientific name, cooking method, nutrition per 100g, plus optional classifications, ingredients, and raw materials.

Instructions

Get one food by number: type, scientific name, cooking method, a short nutrition summary per 100 g (energy, fat, saturated fat, carbohydrates, sugar, fibre, protein, salt) and optionally its classifications, recipe ingredients and raw materials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYesFood number from search_foods (livsmedelsnummer).
includeNoExtra sections. 'ingredients' only exists for calculated foods (dishes).
languageNoLanguage for food and nutrient names: 'en' (English) or 'sv' (Swedish). Defaults to the server setting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds useful behavioral detail about the returned nutrition summary and optional sections, which goes beyond the annotations without contradicting them.

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 a single informative sentence with the key action front-loaded. It lists necessary return fields without unnecessary elaboration or repetition of schema details.

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?

There is no output schema, but the description sufficiently explains the return content, including the nutrient list and optional included sections. Combined with the fully documented input schema and annotations, an agent has enough context to call the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already well documented. The description adds little about parameter semantics beyond mentioning optional sections, but it doesn't need to compensate for missing schema documentation.

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 states a specific action ('Get one food by number') and a precise resource, then enumerates the exact fields returned. This makes it easy to distinguish from siblings like search_foods, compare_foods, and calculate_recipe_nutrition.

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 makes the usage context clear: it is for retrieving a single food when a food number is already known, with optional extended sections. It does not explicitly name alternatives or exclusion conditions, but the 'one food by number' framing is enough to guide selection.

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