StatsMapped: Irish statistics (CSO, county & council data)

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list_areas

List counties, local authorities or districts with IDs and names by country and level to pass valid area identifiers to query_data.

Instructions

Use when you need the ids and names of the areas (counties, local authorities, districts) to pass to query_data.

List every geography at one boundary level, for one country ('ireland' or 'united-kingdom'). level defaults to "county" (Ireland's 26 counties); the UK's own primary level is "lad" (local authority districts), not "county". Other levels exist per country (e.g. Ireland's "local_authority", "garda_division") -- see a dataset's own compatible_levels from query_data for which levels a given stat is actually published at. Returns each area's id (used by query_data's area-scoped modes, always paired with the SAME country), name and level. Slim by default; include_parents=True adds each area's parents (the regions it sits in) and Irish-language name.

Input Schema

Name	Required	Default
`level`	No	county
`country`	No	ireland
`include_parents`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.4Oct 25, 2026

addedInput schema / properties / include_parents

Added value: +{
+  "default": false,
+  "title": "Include Parents",
+  "type": "boolean"
+}

First observedv0.1.0Sep 20, 2026

TDQS

A4.7/5.0

Behavior4/5

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

No annotations exist, so the description carries the full burden and does well: it discloses output fields (`id`, `name`, `level`), that results are slim by default, what `include_parents=True` adds, and the pairing constraint that an `id` must always be used with the SAME `country` in `query_data`. It stops short of mentioning ordering, pagination, or whether the list is exhaustive per level, but the behavioral picture is largely complete for a read-only lookup.

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-loaded with the use case, then defaults, then caveats, then return shape — a sensible order with no filler sentences. It runs slightly long and repeats the `id`-is-for-`query_data` point twice, which is the only wasted effort.

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 three-optional-parameter lookup with no annotations, the description covers defaults, country/level coupling, the extended-output option, and the cross-tool key contract. An output schema exists, so the brief return-value sketch is sufficient and nothing needed to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate and it does: it gives `level`'s default ('county', 26 Irish counties), the country-specific twist that the UK's primary level is 'lad' rather than 'county', the allowed `country` values ('ireland' or 'united-kingdom'), and the exact effect of `include_parents`. That is meaning the schema cannot supply.

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 every geography at one boundary level, for one country') and immediately names its consumer, `query_data`. An agent can distinguish it from `query_data` 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?

Opens with an explicit when-to-use ('Use when you need the ids and names of the areas ... to pass to `query_data`') and clarifies the division of labour by pointing to `compatible_levels` on `query_data` for per-dataset level availability. The when-not is implicit but strong: this tool lists geographies, `query_data` fetches statistics.

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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