Microburbs Australian Property Data

Suburb · Need for assistance

suburbs_area_stats_need_for_assistance

Read-onlyIdempotent

How many residents need help with everyday activities because of disability, long-term illness or old age, overall and among residents aged 65 and over, for 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 people or homes 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/need-for-assistance.

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": {
      "suburb_name": "<suburb_name>"
    },
    "name": "suburbs_area_stats_need_for_assistance"
  }
}

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, need_assistance_count, need_assistance_pct, no_need_assistance_count, no_need_assistance_pct, need_assistance_not_stated_count, need_assistance_not_stated_pct, total_aged_65_plus, aged_65_plus_need_assistance_count, aged_65_plus_need_assistance_pct. Omit for all.
`suburb_name`	Yes	Suburb name exactly as /v1/suburbs/list returns it, e.g. `Bondi` or `St Kilda (Vic.)`.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context beyond them: coverage limits (~11,000 suburbs, 545 council areas, small areas excluded), the single fixed snapshot (10 Aug 2021, not a range), and a per-call price of 5¢, which matters for invocation planning. It stops short of describing response shape or failure behavior, keeping it at a 4.

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 measure is stated first, then coverage, then cost — a sensible front-loading. Every block carries information (geography, exclusions, snapshot date, price, link to fuller docs), though the coverage paragraph is dense and could be tightened.

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 4-parameter filtered-statistics tool with no output schema, the description conveys what is measured, the two population breakdowns, the geographies, the time scope and the cost — enough to call it correctly. Only the return format and behavior for a non-matching `suburb_name` are left implicit.

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 formats for `from`/`to`, the full field list, and the exact-match rule for `suburb_name` already documented. The description adds no parameter-level detail beyond what the schema provides, so the baseline 3 applies.

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 names the exact measure ('residents need help with everyday activities because of disability, long-term illness or old age'), the dual breakdown (overall and aged 65+), and the two geographies covered (every suburb and council area). An agent can distinguish this from lga_area_stats_need_for_assistance because suburb-level coverage is stated explicitly.

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

Usage Guidelines3/5

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

Usage is implied by the scope statement rather than spelled out: it is clear this is the suburb-level need-for-assistance dataset for the 2021 snapshot, and that areas with too few people are omitted. There is no explicit when-to-use/when-not guidance or pointer to a sibling for a different geography or time period, and no note that only one period is available.

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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