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by robobobby

fi_company_lookup

Retrieve detailed Finnish company information using a Business ID (Y-tunnus), including registers, addresses, and historical data.

Instructions

Look up a Finnish company by Business ID (Y-tunnus). Returns detailed information including registers, addresses, and history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
business_idYesFinnish Business ID (Y-tunnus), e.g., '0112038-9' or '2331972-6'

Implementation Reference

  • The implementation of the 'fi_company_lookup' tool, which handles the validation of the Business ID and fetches company details from the PRH API.
    server.tool(
      "fi_company_lookup",
      "Look up a Finnish company by Business ID (Y-tunnus). Returns detailed information including registers, addresses, and history.",
      {
        business_id: z.string().describe("Finnish Business ID (Y-tunnus), e.g., '0112038-9' or '2331972-6'"),
      },
      async ({ business_id }) => {
        const clean = business_id.trim();
        // Finnish business IDs are format: 7 digits, dash, 1 check digit
        if (!/^\d{7}-\d$/.test(clean)) {
          return { content: [{ type: "text", text: "Invalid Business ID format. Expected format: 1234567-8 (7 digits, dash, check digit)." }] };
        }
    
        const data = await apiFetch("/companies", { businessId: clean });
        const companies = data.companies || [];
    
        if (companies.length === 0) {
          return { content: [{ type: "text", text: `No company found with Business ID ${clean}.` }] };
        }
    
        return { content: [{ type: "text", text: formatCompanyDetail(companies[0]) }] };
      }
    );
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return includes 'detailed information including registers, addresses, and history,' which adds some context beyond the input schema. However, it lacks critical details such as error handling (e.g., for invalid IDs), rate limits, authentication requirements, or data freshness—important for a lookup tool with potential external dependencies.

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?

The description is concise and front-loaded, consisting of two clear sentences: one stating the action and input, and another outlining the return information. There's no wasted text, though it could be slightly more structured (e.g., bullet points for return details) for a perfect score.

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 tool's moderate complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and return scope but lacks usage guidelines, behavioral details (e.g., error cases), and output specifics. This makes it minimally viable but with clear gaps for an agent to operate effectively.

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%, with the parameter 'business_id' well-documented in the schema as 'Finnish Business ID (Y-tunnus), e.g., '0112038-9' or '2331972-6'.' The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.

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's purpose: 'Look up a Finnish company by Business ID (Y-tunnus).' It specifies the verb ('Look up'), resource ('Finnish company'), and key identifier ('Business ID'). However, it doesn't explicitly differentiate from sibling tools like 'fi_search_companies' or 'no_company_lookup', which would be needed for a score of 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools (e.g., 'fi_search_companies' for broader searches or 'no_company_lookup' for Norwegian companies) or specify use cases like exact-match lookups versus fuzzy searches. This lack of comparative context leaves the agent without clear selection criteria.

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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