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List areas

list_areas
Read-onlyIdempotent

List the administrative areas of one level, with their GURS eid. INPUT: level — municipality (212 of them), settlement (naselje), quarter_community (cetrtna skupnost), local_community (krajevna skupnost), cadastral_area (katastrska obcina). READ: boundary_matches_name — a cadastral area's NAME is a neighbourhood name and its BOUNDARY is not. THEN: use find_area instead when you have text to resolve; this tool enumerates, it does not search.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_areas"
  }
}

Input Schema

NameRequiredDescriptionDefault
levelNomunicipality
limitNo

Output Schema

NameRequiredDescriptionDefault
areasYes
as_ofYes
levelYes
n_totalYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, yet the description still adds real context: the size of the municipality set (212), the meaning of each level, and a data-quality warning that a cadastral area's name is a neighbourhood name while its boundary is not. It omits pagination behaviour (limit defaults to 50), which is the one behavioural gap.

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-loads the purpose in one sentence, then uses INPUT/READ/THEN labels to keep each addition distinct with no filler. The structured labels are terse but each line earns its place.

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 values need no explanation, and the description still flags the one output field that misleads (boundary_matches_name). Combined with the level semantics and the alternative-tool routing, an agent has everything needed to call it correctly.

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 coverage is 0%, so the description must carry the load; it does well for `level`, expanding each enum value in plain language and noting the municipality count. However, the `limit` parameter is never mentioned, so pagination semantics are undocumented in both schema and description.

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?

States a specific verb and resource ('List the administrative areas of one level') plus the key attribute returned (GURS eid). It also names the sibling it is not, so an agent can separate enumeration from search without opening either schema.

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 routes the agent: 'use find_area instead when you have text to resolve; this tool enumerates, it does not search.' That is a clear when-to-use/when-not statement against a named alternative.

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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