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Microburbs Australian Property Data

by au.com.microburbs
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Suburb · Motor vehicles per dwelling

suburbs_area_stats_motor_vehicles
Read-onlyIdempotent

How many cars households keep: dwellings with no vehicle, one, two, three or four or more, for every suburb and council area.

Coverage: About 10,700 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/motor-vehicles.

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_motor_vehicles"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLast period to include, same formats as `from`.
fromNoFirst period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
fieldsNoComma-separated subset of: total_occupied_dwellings, no_vehicle_count, no_vehicle_pct, one_vehicle_count, one_vehicle_pct, two_vehicles_count, two_vehicles_pct, three_vehicles_count, three_vehicles_pct, four_plus_vehicles_count, four_plus_vehicles_pct, two_or_more_vehicles_count, two_or_more_vehicles_pct, vehicles_not_stated_count, vehicles_not_stated_pct. Omit for all.
suburb_nameYesSuburb name exactly as /v1/suburbs/list returns it, e.g. `Bondi` or `St Kilda (Vic.)`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish a safe, read-only, idempotent, closed-world read, so the description's value is in the operational context it adds: data vintage ('one snapshot at 10 August 2021', 'Current to 2021-08-10'), universe size (10,700 suburbs, 545 council areas), the exclusion rule for small areas, and an explicit '5¢ per call' pricing signal. Missing is any statement of response shape or row granularity, but the price and vintage disclosures are genuinely useful beyond the annotations.

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 metric definition is front-loaded in the first clause, followed by coverage, vintage, and price in descending order of importance. Four sentences, none purely redundant; the only slack is the slight overlap between the coverage list and the snapshot-date line.

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 tool with no output schema and fully documented parameters, the description covers what an agent needs: what is measured, geographic universe, exclusions, temporal vintage, cost, and a pointer to the full field list and method. The main gap is the lack of any differentiation from the LGA counterpart, which matters given the stated dual coverage.

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 from/to/fields/suburb_name are already well documented, and the baseline is 3. The description adds only indirect meaning—the 'one snapshot at 10 August 2021' note implies that from/to values outside that date will yield nothing—but it never frames this as parameter guidance, so an agent could still pass 2020 or 2020-Q3 and be surprised.

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 states a specific resource and metric set—'dwellings with no vehicle, one, two, three or four or more'—for 'every suburb and council area', which lets an agent distinguish this from the many other suburb statistical datasets by name and content. It stops short of naming the council-level sibling (lga_area_stats_motor_vehicles), and in fact claims coverage of '545 council areas', which muddies the suburb vs. LGA distinction rather than sharpening it.

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?

There is no explicit when-to-use guidance and no mention of alternatives; the agent must infer from the tool name that this is the suburb-granularity motor-vehicle dataset. The coverage note ('areas with too few people or homes for reliable figures are left out') is a data caveat, not routing guidance, and the overlap with the LGA sibling is left unresolved.

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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