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nordic-data

by io.github.Mnymann

get_endpoint_schema

Read-onlyIdempotent

Discovery meta-tool. Returns the full parameter and response schema for a single Nordic Data API endpoint (path + method), read from the backend's live OpenAPI spec with $refs resolved inline. Use after list_endpoints to learn exactly which parameters an endpoint takes before calling it with call_endpoint. Admin endpoints are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesEndpoint path from list_endpoints, e.g. '/api/company/{country}/{id}'. Concrete paths like '/api/company/dk/22756214' are also accepted.
methodNoHTTP method for the endpoint (e.g. GET, POST). Defaults to GET. Must be a method the endpoint actually defines.GET

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint, it reveals that data is read from the 'backend's live OpenAPI spec with $refs resolved inline' and that admin endpoints are rejected. This adds meaningful behavioral context about data source, processing, and restrictions that annotations do not capture.

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?

Two sentences, front-loaded with the core purpose and followed by concise usage guidance. Every word earns its place with no redundancy.

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?

For a meta-tool, the description is complete: it states what it returns, where data comes from, when to use it, and an exclusion. Combined with the rich annotations and schema, it leaves no major gaps.

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 path and method already documented with examples and defaults. The description does not add parameter-level detail beyond what the schema provides, so the baseline 3 is appropriate.

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 opens with 'Discovery meta-tool' and clearly states it 'Returns the full parameter and response schema for a single Nordic Data API endpoint (path + method)'. The verb is specific and the resource is well-defined, distinguishing it from siblings like list_endpoints and call_endpoint.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to 'Use after list_endpoints to learn exactly which parameters an endpoint takes before calling it with call_endpoint', providing clear sequencing and placing it between list and call operations. Also notes that admin endpoints are rejected, which is a usage constraint.

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.

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