Microburbs Australian Property Data

Suburb · Method of travel to work

suburbs_area_stats_travel_to_work

Read-onlyIdempotent

How working residents got to work: car as driver or passenger, train, bus, tram, ferry, bike, walking, working from home, and the share using public transport, for every suburb and council area.

Coverage: About 8,800 suburbs and localities and 540 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/travel-to-work.

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_travel_to_work"
  }
}

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_employed, public_transport_count, public_transport_pct, car_as_driver_count, car_as_driver_pct, car_as_passenger_count, car_as_passenger_pct, train_count, train_pct, bus_count, bus_pct, ferry_count, ferry_pct, tram_or_light_rail_count, tram_or_light_rail_pct, taxi_or_ride_share_count, taxi_or_ride_share_pct, truck_count, truck_pct, motorbike_or_scooter_count, motorbike_or_scooter_pct, bicycle_count, bicycle_pct, walked_only_count, walked_only_pct, other_single_method_count, other_single_method_pct, two_methods_count, two_methods_pct, two_methods_with_train_count, two_methods_with_train_pct, two_methods_with_bus_count, two_methods_with_bus_pct, three_methods_count, three_methods_pct, worked_at_home_count, worked_at_home_pct, did_not_go_to_work_count, did_not_go_to_work_pct, method_not_stated_count, method_not_stated_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

A3.8/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add operational context — which it does well: coverage of ~8,800 suburbs and 540 council areas, a single 10 August 2021 snapshot, exclusion of small areas, and a 5¢ per-call price. The cost disclosure is unusually valuable for an agent deciding whether to call. It does not describe result shape or behavior for a suburb not in the dataset.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with what the data is, then coverage counts, snapshot date, doc pointer, and price in a bolded final line. Every sentence carries distinct information and there is no filler or repetition of the schema.

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?

With no output schema, the description still supplies the critical context an agent needs: data vintage (2021-08-10 snapshot), geography coverage, and the fact that small areas are excluded — so a missing suburb is interpretable. What is missing is any statement of return structure (rows per suburb, units for counts vs pct), which the agent must infer from the field names.

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/from-to/fields/suburb_name are already fully documented in the schema, including the field list and the exact-name matching note. The description adds nothing parameter-specific beyond pointing to /v1/datasets/travel-to-work for the full field list. Baseline 3 applies.

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 names the exact resource and its content: method of travel to work breakdowns (car, train, bus, ferry, bike, walking, WFH, public transport share) for suburbs and council areas. An agent knows precisely what data comes back. It lacks explicit routing against the near-identical sibling lga_area_stats_travel_to_work, and its 'every suburb and council area' phrasing slightly blurs that boundary.

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 rather than stated: an agent can infer this is the tool for retrieving travel-to-work figures for a named suburb. There is no explicit when-to-use, no when-not-to-use, and no mention of the LGA-level sibling as the alternative when council-area aggregates are wanted. Coverage limits ('areas with too few people or homes are left out') give partial scoping guidance.

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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