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Jatin-IITB

Open Food Facts MCP Server

by Jatin-IITB

autocomplete

Search for food categories, brands, labels, ingredients, allergens, or additives by providing a partial query and taxonomy type to get autocomplete suggestions.

Instructions

Get autocomplete suggestions for categories, brands, labels, ingredients, allergens, or additives

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesAutocomplete query
taxonomyTypeYesType of taxonomy to search
langNoLanguage codeen
limitNoMaximum number of suggestions
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It fails to mention whether the tool is read-only, has rate limits, or how it handles partial matches. Basic behavioral traits are absent.

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, front-loaded sentence with no wasted words. It efficiently conveys the tool's purpose and scope.

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?

Given the absence of an output schema, the description should clarify the return format (e.g., array of suggestions). It does not, leaving ambiguity about what the agent will receive. For a simple autocomplete, this is acceptable but not 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?

Schema coverage is 100%, so parameters are fully documented in the input schema. The description adds minimal value by listing the taxonomy types, but the schema already defines them via enum. The description does not provide additional meaning beyond what is in the schema.

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 provides autocomplete suggestions for multiple taxonomy types. It uses a specific verb ('Get autocomplete suggestions') and lists the resource types. However, it does not explicitly distinguish from sibling tools like 'searchByCategory' or 'searchByBrand', which might be confused with autocomplete.

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?

No guidance is given on when to use this tool versus alternatives such as 'searchProducts' or 'advancedSearch'. The description only states what it does, leaving the agent to infer usage context.

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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