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by robobobby

dk_address_search

Search Danish addresses using text queries to find locations with coordinates for autocomplete and validation purposes.

Instructions

Search for Danish addresses by free-text query (street name, full address, postal code + city). Returns matching addresses with coordinates. Great for autocomplete and address validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesAddress search text, e.g. 'Nørrebrogade 1, København' or 'Ølsemagle Strand'
limitNoMax results (default 10)
municipalityNoFilter by municipality code (e.g. '0101' for Copenhagen)
postal_codeNoFilter by postal code (e.g. '2200')

Implementation Reference

  • The handler function for dk_address_search, which constructs query parameters and fetches data from the DAWA API.
    async ({ query, limit, municipality, postal_code }) => {
      try {
        const params = { q: query, struktur: "mini", per_side: limit || 10 };
        if (municipality) params.kommunekode = municipality;
        if (postal_code) params.postnr = postal_code;
        const data = await dawaFetch("/adresser", params);
        return { content: [{ type: "text", text: formatAddressList(data) }] };
      } catch (err) {
        return { content: [{ type: "text", text: `Error: ${err.message}` }], isError: true };
      }
    }
  • Input schema for dk_address_search, defining query, limit, municipality, and postal_code parameters using zod.
    {
      query: z.string().describe("Address search text, e.g. 'Nørrebrogade 1, København' or 'Ølsemagle Strand'"),
      limit: z.number().min(1).max(50).optional().describe("Max results (default 10)"),
      municipality: z.string().optional().describe("Filter by municipality code (e.g. '0101' for Copenhagen)"),
      postal_code: z.string().optional().describe("Filter by postal code (e.g. '2200')"),
    },
  • Registration of the dk_address_search tool using the server.tool method.
    server.tool(
      "dk_address_search",
      "Search for Danish addresses by free-text query (street name, full address, postal code + city). Returns matching addresses with coordinates. Great for autocomplete and address validation.",
      {
        query: z.string().describe("Address search text, e.g. 'Nørrebrogade 1, København' or 'Ølsemagle Strand'"),
        limit: z.number().min(1).max(50).optional().describe("Max results (default 10)"),
        municipality: z.string().optional().describe("Filter by municipality code (e.g. '0101' for Copenhagen)"),
        postal_code: z.string().optional().describe("Filter by postal code (e.g. '2200')"),
      },
      async ({ query, limit, municipality, postal_code }) => {
        try {
          const params = { q: query, struktur: "mini", per_side: limit || 10 };
          if (municipality) params.kommunekode = municipality;
          if (postal_code) params.postnr = postal_code;
          const data = await dawaFetch("/adresser", params);
          return { content: [{ type: "text", text: formatAddressList(data) }] };
        } catch (err) {
          return { content: [{ type: "text", text: `Error: ${err.message}` }], isError: true };
        }
      }
    );
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior by mentioning the return type ('addresses with coordinates') and use cases ('autocomplete and address validation'), but lacks details on rate limits, authentication needs, error handling, or pagination. This is adequate but leaves gaps in behavioral understanding.

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 front-loaded with the core purpose, followed by output details and use cases in two concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.

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 (4 parameters, no output schema, no annotations), the description is reasonably complete for a search tool. It covers purpose, output, and use cases, but lacks details on response format, error scenarios, or performance characteristics, which would be helpful for an agent to use it 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?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying the query parameter's flexibility ('free-text query') and the tool's general purpose, but does not provide additional semantic context for parameters like municipality or postal_code. This meets the baseline for high schema coverage.

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 clearly states the tool's purpose with specific verbs ('Search for Danish addresses') and resources ('addresses'), including the scope ('by free-text query') and output ('Returns matching addresses with coordinates'). It distinguishes itself from siblings like dk_postal_code_lookup or dk_reverse_geocode by focusing on free-text search rather than specific lookups.

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 clear context for when to use the tool ('Great for autocomplete and address validation'), which helps differentiate it from siblings. However, it does not explicitly state when not to use it or name specific alternatives (e.g., dk_nearby_addresses for proximity-based searches), which prevents a perfect score.

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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