Microburbs Australian Property Data

LGA · Ancestry

lga_area_stats_ancestry

Read-onlyIdempotent

Where each ancestry group lives: counts and shares for 29 ancestries (English, Irish, Chinese, Indian, Lebanese and more) in every suburb and council area.

Coverage: About 11,000 suburbs and localities and 545 council areas across Australia, in all states and territories (areas with too few residents for reliable figures are left out); one snapshot at 10 August 2021. Current to 2021-08-10. Full description, field list and method: /v1/datasets/ancestry.

Price: 5¢ per call.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lga_name": "<lga_name>"
    },
    "name": "lga_area_stats_ancestry"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last period to include, same formats as `from`.
`from`	No	First period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
`fields`	No	Comma-separated subset of: total_population, australian_count, australian_pct, aboriginal_count, aboriginal_pct, english_count, english_pct, irish_count, irish_pct, scottish_count, scottish_pct, welsh_count, welsh_pct, german_count, german_pct, dutch_count, dutch_pct, french_count, french_pct, italian_count, italian_pct, greek_count, greek_pct, maltese_count, maltese_pct, spanish_count, spanish_pct, polish_count, polish_pct, russian_count, russian_pct, hungarian_count, hungarian_pct, croatian_count, croatian_pct, serbian_count, serbian_pct, macedonian_count, macedonian_pct, chinese_count, chinese_pct, indian_count, indian_pct, filipino_count, filipino_pct, vietnamese_count, vietnamese_pct, korean_count, korean_pct, sri_lankan_count, sri_lankan_pct, lebanese_count, lebanese_pct, south_african_count, south_african_pct, new_zealander_count, new_zealander_pct, maori_count, maori_pct, samoan_count, samoan_pct, other_ancestry_count, other_ancestry_pct, not_stated_count, not_stated_pct. Omit for all.
`lga_name`	Yes	Council (LGA) name exactly as /v1/lga/list returns it, e.g. `Lake Macquarie`.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

A3.5/5.0

Behavior4/5

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

The annotations already establish read-only, idempotent, non-destructive behavior with no open-world access, so the bar is lower. The description adds useful behavioral context beyond annotations: the 5¢ per-call price, dataset coverage, exclusion of areas with too few residents, and the single 2021 snapshot.

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?

The description is front-loaded with the core purpose and then provides coverage, currency, and price without excessive length. There is minor redundancy in stating the snapshot date twice ('10 August 2021' and '2021-08-10'), but overall it is efficient and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only dataset query with four well-documented parameters and no output schema, the description supplies the essential context: what the data measures, geographic coverage, exclusions, snapshot date, and cost. It could clarify how from/to behave given the single snapshot, but the schema covers parameter syntax adequately.

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%, so the input schema already documents lga_name, from, to, and fields thoroughly. The description adds little parameter-specific meaning beyond noting the 29 ancestry groups, which the schema's field list already covers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the resource and content: counts and shares for 29 ancestry groups, with coverage of council areas. However, the phrase 'in every suburb and council area' blurs the LGA-only scope and does not explicitly route agents away from the sibling suburbs_area_stats_ancestry tool.

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

Usage Guidelines2/5

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

The description provides dataset scope and price but no explicit when-to-use guidance, no exclusions, and no named alternative such as suburbs_area_stats_ancestry. An agent must infer that this tool is for LGA-level ancestry data rather than suburb-level results.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Microburbs Australian Property Data tools Inspect

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