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autocomplete_address

Read-onlyIdempotent

Address autocomplete using each country's authoritative register: DAWA (DK), Kartverket (NO), BAN (FR official), MML (FI), and Nominatim (others). Returns ranked address suggestions with coordinates. Supports 15 countries (DK, NO, SE, FI, IE, UK, FR, DE, CZ, PL, LV, EE, NL, BE, LU). Tier note: NL and DE require a Starter+ subscription — free-tier API keys receive HTTP 402 'upgrade_required'; do NOT retry on 402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial address — street name, postcode, city, or any combination. Min 2 characters.
countryYesISO 3166-1 alpha-2 country code, lowercase.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
suggestionsNoRanked address candidates, best match first.

TDQS

A4.7/5.0
Behavior5/5

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

Despite annotations already indicating read-only and idempotent, the description adds valuable behavior: country-specific backend selection, return of ranked suggestions with coordinates, and the 402 'upgrade_required' error handling. It also warns that NL and DE require a Starter+ subscription, which is crucial runtime context.

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, each dense with useful information: first sentence explains the mechanism, second lists return value and supported countries, third gives critical error handling. It is front-loaded with the core purpose and has no filler or redundant statements.

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?

With an output schema present, the description does not need to detail return fields, yet it still mentions ranked suggestions and coordinates. It covers the core functionality, all supported countries, and a key error scenario (402). The tool's complexity (multi-backend, country variations) is fully addressed in the description.

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?

The schema provides 100% coverage for parameters query and country, including descriptions and enum values. The description adds meaning beyond the schema by linking country codes to their authoritative registers and by highlighting the subscription limitation for NL and DE, which affects how the country parameter behaves.

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 it performs address autocomplete using authoritative registers and lists specific register names for countries (DAWA, Kartverket, BAN, MML, Nominatim). This distinguishes it from siblings like lookup_company or validate_vat, which serve different domains.

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 implies when to use (address suggestions) and gives concrete usage caveats: supported countries list, NL/DE subscription requirement, and explicit instruction 'do NOT retry on 402'. It lacks an explicit when-not-to-use statement, but the sibling tools are clearly in different domains, so the usage context is sufficient.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a clearly distinct function: address autocomplete, company lookup, enriched company data, KYB report, LEI lookup, sanctions screening, VAT validation, French history, and three discovery meta-tools. The discovery tools (list_endpoints, get_endpoint_schema, call_endpoint) form a clean trio with distinct roles. There is minor overlap between company_enriched, kyb_full, and lookup_company, but their scopes are well-differentiated in the descriptions.

Naming Consistency4/5

The naming pattern is largely consistent with noun-based descriptive names (company_enriched, lookup_company, lookup_lei, validate_vat, screen_sanctions, autocomplete_address). Three discovery tools use verb-based names (list_endpoints, get_endpoint_schema, call_endpoint), and fr_history breaks the pattern as a country-specific tool. Minor inconsistency but readable and predictable overall.

Tool Count4/5

11 tools is within a reasonable range for a data-provider server that covers 15 countries and multiple data domains (entities, sanctions, VAT, addresses, LEI). Each tool addresses a distinct need. Slightly heavy given some overlap, but the count is justified by the breadth of coverage.

Completeness4/5

The core business-intelligence surface is well covered: company lookup, enriched data, full KYB, LEI, sanctions, VAT, address autocomplete, and French history. The discovery meta-tools (list_endpoints, get_endpoint_schema, call_endpoint) elegantly bridge gaps by exposing 230+ additional endpoints. Minor gaps: no dedicated UK-specific or non-French history tool, and screening is limited to sanctions/PEP without a dedicated adverse-media tool separate from kyb_full.