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infobel-api-mcp

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by techinfobel

search_categories_local

Retrieve country-specific business category codes by keyword search. Get local codes like SIC, NAF, or WZ for filtering business queries.

Instructions

Search country-specific category codes by one or more keywords.

Each keyword triggers a separate API call; results are merged and deduplicated. Returns matching local codes (e.g. SIC for US, NAF for France, WZ for Germany) for use in search_businesses local_codes field.

Args: keywords: One or more search terms (e.g. ["plomberie"], ["bakery", "boulangerie", "pastry"]). country_code: ISO 3166-1 alpha-2 country code (e.g. "FR", "DE", "US"). language_code: Display language for results (e.g. "en", "fr").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYes
country_codeYes
language_codeNoen

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description takes on full responsibility. It discloses that each keyword triggers a separate API call and that results are merged and deduplicated. This is valuable behavioral insight. It could mention if there are limits on keyword count or pagination, but given the output schema exists, it's adequate.

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 concise and well-structured. It starts with the main purpose, then adds behavioral detail, then lists parameters. Every sentence adds value, and the Args block is cleanly formatted. No wasted words.

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 tool's complexity (multi-keyword search, country-specific codes, integration with search_businesses), the description provides sufficient context: merging behavior, use case, parameter details. It leverages the output schema for return structure. Could mention whether there are limits on the number of keywords, but overall very informative.

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?

Schema description coverage is 0%, so the description must provide parameter meanings. It does so clearly in the Args block: explains keywords as search terms with examples, country_code as ISO alpha-2, and language_code with default. The examples ('plomberie', 'bakery', 'boulangerie') add clarity.

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 it searches country-specific category codes by keywords. It uses a specific verb ('Search') and resource ('country-specific category codes'). However, it does not explicitly differentiate from sibling tools like search_categories_international or search_categories_alt_international, missing an opportunity to clarify its unique scope.

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 explains the tool's purpose and provides a usage example (e.g., for search_businesses local_codes field). It mentions each keyword triggers a separate API call, which helps set expectations. However, it does not explicitly state when not to use this tool or list alternative tools for different scenarios.

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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