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Search French companies

search_companies

Search French companies by name, trade name, acronym, or officer name, with optional filters for NAF code, department, postal code, and active status to return compact summaries.

Instructions

Find French companies by name, trade name, acronym or officer name. Fuzzy — 'boulangerie dupont nantes' works. Returns compact summaries; call get_company for the full profile. Filters are optional and combine with AND.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
queryYesCompany name, trade name, acronym or officer name
naf_codeNoNAF rev.2 activity code, e.g. '62.01Z' for software development
departmentNoDépartement code, e.g. '44' for Loire-Atlantique, '2A' for Corse-du-Sud
active_onlyNoExclude companies that have ceased trading
postal_codeNoExact postal code
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses fuzzy behavior, compact summary output, and response-depth differences versus get_company. It does not mention pagination behavior or the active_only default, but the search-oriented nature makes the read-only behavior clear.

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?

Three efficient sentences front-load the search scope, provide a concrete example, route to the correct sibling, and explain filter semantics. No wasted words or repetition of the schema.

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?

The description covers expected behavior, output granularity, filter semantics, and an alternative tool. It lacks detail on pagination, defaults, and the role of list_establishments, but for a search tool with a small schema these are minor gaps.

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 coverage is 71%, and the description adds semantics beyond the schema by showing that the query can be a fuzzy multi-word phrase and that filters are optional and AND-combined. Page and limit are not described in prose, but their names and defaults largely make their behavior clear.

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 and resource: finding French companies by name, trade name, acronym, or officer name. It also clarifies fuzzy matching and explicitly distinguishes itself from get_company, which returns the full profile.

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?

It gives clear guidance to call get_company when the full profile is needed, and states filters are optional and AND-combined. It does not mention when to prefer list_establishments or explain_code, but the search-versus-lookup distinction is reasonably clear.

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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