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milos106

ares-mcp

by milos106

ares_search_by_address

Identify shell companies by finding all Czech companies registered at a specific address. Get IČOs, names, and ARES canonical addresses.

Instructions

Find all Czech companies whose registered seat (sídlo) matches a given address. Useful for shell-company / virtual-office detection: an address with dozens or hundreds of entities at it is a strong signal. Returns IČOs, names, and the canonical address ARES holds for each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of IČOs to return per page.
adresaYesFree-form Czech address text — e.g. 'Vratimovská 689/117, Ostrava' or 'Pyšelská 2327/2, Praha'. The tool forwards it to ARES as a sidlo.textovaAdresa filter.
offsetNoPagination offset.
Behavior3/5

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

With no annotations, the description must carry the full burden of behavioral disclosure. It does mention the output (IČOs, names, canonical address) and implies a read/search operation. However, it does not disclose matching behavior (e.g., exact vs. fuzzy), potential empty results, or pagination behavior beyond what the schema already provides. This is adequate but has gaps.

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 three sentences: what it does, a practical use case, and the return format. It is front-loaded with the primary function and contains no redundant information. Every sentence adds value.

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 tool has no output schema, but the description compensates by listing the key return fields. It explains the purpose, use case, and output enough for an agent to decide and invoke it. Minor gaps exist around matching behavior and edge cases, but overall it is sufficiently complete for a search tool.

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 description coverage is 100%, so the baseline is 3. The description does not add additional parameter semantics beyond the schema; it mentions 'given address' but the schema already thoroughly describes adresa with examples. Limit and offset are fully described in the schema, so the description contributes nothing extra.

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 uses a specific verb ('Find all Czech companies') and clearly identifies the resource (companies by registered seat) and the matching criterion (a given address). It distinguishes itself from siblings like ares_search_companies and ares_lookup_company by focusing on address-based bulk search and explicitly mentions the returned fields (IČOs, names, canonical address).

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 provides a clear use case for shell-company or virtual-office detection, which implies when to use this tool. However, it does not explicitly contrast with alternatives or state when not to use it, leaving some ambiguity relative to sibling tools like ares_standardize_address.

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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