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AiAgentKarl

nutrition-mcp-server

tool_search_food

Search over 1 million foods in the USDA FoodData Central database using keywords like 'apple' or 'chicken breast'.

Instructions

Lebensmittel in der USDA FoodData Central Datenbank suchen (1M+ Eintraege).

Args: query: Suchbegriff (z.B. "apple", "chicken breast", "whole wheat bread") limit: Anzahl der Ergebnisse (max. 25, Standard: 10)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo
Behavior2/5

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

No annotations are provided, so the description must convey behavioral traits. It mentions the database size (1M+ entries) and limit constraints (max 25), but does not disclose whether the tool is read-only, performance characteristics, authentication needs, or any side effects. The description carries the full burden but only provides minimal behavioral context.

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 extremely concise with two short paragraphs. The first sentence states the purpose immediately, and the parameter descriptions are efficient with examples. Every sentence earns its place, and there is no superfluous information.

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?

Given the simplicity of the tool (2 parameters, no output schema), the description is largely complete. It covers purpose, parameter meanings, and constraints. However, for completeness in context of siblings, a brief note on when to search vs. use other tools would improve it. Still, it is adequate for a straightforward search function.

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

Parameters4/5

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

The description adds significant meaning beyond the input schema: it explains that 'query' is a search term with concrete examples ('apple', 'chicken breast'), and clarifies 'limit' with a maximum of 25 and default of 10. With schema description coverage at 0%, the description compensates well by providing clear semantics and constraints for both parameters.

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 searches foods in the USDA FoodData Central database with over 1 million entries. It uses a specific verb ('suchen') and resource ('Lebensmittel in der USDA FoodData Central Datenbank'), and the scope is well-defined. However, it does not explicitly distinguish from siblings like 'compare_foods' or 'find_foods_high_in', though the search function is implied.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It only describes the parameters without any context about appropriate scenarios, prerequisites, or when to avoid it. For a search tool among several food-related tools, clear usage guidance would be beneficial.

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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