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AiAgentKarl

nutrition-mcp-server

tool_get_nutrition_facts

Retrieve complete nutrition facts for any food using its USDA FoodData Central ID. Supports custom serving sizes for accurate calculations.

Instructions

Vollstaendige Naehrwertdaten fuer ein Lebensmittel abrufen.

Args: fdc_id: USDA FoodData Central ID (aus search_food) serving_grams: Portionsgroesse in Gramm fuer Berechnung (Standard: 100g)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fdc_idYes
serving_gramsNo
Behavior3/5

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

The description explains that the tool calculates nutritional values based on serving size (default 100g), which is a behavioral trait. However, it does not mention any side effects, errors, or safety (e.g., read-only). Since no annotations, more transparency expected.

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 concise with a clear summary and parameter list, but the German language might obscure for some users.

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

Completeness3/5

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

The description explains the input but not the output structure. Given no output schema, the agent lacks understanding of what data is returned. It is adequate but not fully complete.

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?

The description provides brief parameter explanations (fdc_id source and serving_grams purpose) beyond the schema field names, which is necessary given 0% schema description coverage. However, it lacks examples or constraints.

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 clearly states the tool retrieves complete nutritional data for a food item using a USDA ID. It implies comprehensiveness compared to sibling tools like tool_get_nutrient_info, but does not explicitly distinguish.

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 description explains the required input (fdc_id from search_food) and optional serving size, but does not provide guidance on when to choose this tool over siblings like tool_get_nutrient_info.

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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