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MIL — Machine Intelligence Layer

Search Swedish companies

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Read-only

Search Swedish companies by name or organisationsnummer (10 or 12 digits, dashes allowed). Also accepts simple discovery such as 'restaurants in Trelleborg', 'construction companies in Malmö', 'IT companies in Lund', or 'companies in Trelleborg' (also Swedish 'restauranger i Malmö'). Industries resolve through official English/Swedish SNI descriptions and business aliases, e.g. 'computer repair'/'datorreparation' and 'dining'/'restaurangverksamhet'. Known counties such as Skåne and explicit municipality names use registered administrative geography. Unrecognized or ambiguous wording falls back to name search. Locality is the registered locality, not nearby workplaces. Signal-filtered discovery is refused in free search; use paid find_distress_signals for a known company. Returns up to 10 results, each with an id to pass to fetch and a citable URL. Free (Basic identity only).

Input Schema

NameRequiredDescriptionDefault
queryYesCompany name, organisationsnummer such as 556012-5790, or simple discovery such as restaurants in Trelleborg

Output Schema

NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Company name, or organisationsnummer such as 556012-5790"New value: +"Company name, organisationsnummer such as 556012-5790, or simple discovery such as restaurants in Trelleborg"
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds genuinely useful behavior beyond that: a hard 10-result cap, the presence of an id and citable URL per result, the free tier being limited to Basic identity, the refusal of signal-filtered queries, and name-search fallback for ambiguous input. It also clarifies that locality means registered locality, not nearby workplaces — a semantic trap otherwise invisible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core capability, and each sentence carries distinct information (formats, discovery examples, resolution rules, fallback, limits). It is dense as one long paragraph and would scan better as a short bulleted list of query forms, but there is little wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is not required, and the description still covers scope, input grammar, result cap, cost tier, and refusal routing. Nothing needed to invoke it correctly appears to be missing; only explicit pagination is absent, which is minor given the stated 10-result cap.

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

Parameters5/5

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

Schema coverage is 100% for the single query parameter, so baseline would be 3, but the description goes well beyond the schema by specifying org-number format (10 or 12 digits, dashes allowed), the SNI/alias resolution mechanics, and Swedish-language query support. This is substantive grammar the schema does not encode.

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?

States a specific verb and resource (search Swedish companies) and enumerates accepted input forms — name, organisationsnummer, and free-text discovery. It distinguishes itself from find_distress_signals by refusing signal-filtered discovery, but it never differentiates itself from the sibling tool search_companies, which an agent cannot disambiguate from this description alone.

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?

Gives explicit when-not guidance ('Signal-filtered discovery is refused in free search; use paid find_distress_signals for a known company') and explains fallback behavior for unrecognized wording, plus names fetch as the follow-up consumer of returned ids. The remaining gap is the unaddressed overlap with search_companies.

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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