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Microburbs Australian Property Data

by au.com.microburbs
OverviewDiscussionsAdmin

Suburb · Rent payments

suburbs_area_stats_rent_payments
Read-onlyIdempotent

What renting households actually pay: weekly rent in 14 bands from under $75 to $950 or more, the median weekly rent, and who the landlord is (agent, private owner, public or community housing), for every suburb and council area.

Coverage: About 5,400 suburbs and localities and 536 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/rent-payments.

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_rent_payments"
  }
}

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_renting_households, rent_1_74_count, rent_1_74_pct, rent_75_99_count, rent_75_99_pct, rent_100_149_count, rent_100_149_pct, rent_150_199_count, rent_150_199_pct, rent_200_224_count, rent_200_224_pct, rent_225_274_count, rent_225_274_pct, rent_275_349_count, rent_275_349_pct, rent_350_449_count, rent_350_449_pct, rent_450_549_count, rent_450_549_pct, rent_550_649_count, rent_550_649_pct, rent_650_749_count, rent_650_749_pct, rent_750_849_count, rent_750_849_pct, rent_850_949_count, rent_850_949_pct, rent_950_plus_count, rent_950_plus_pct, rent_not_stated_count, rent_not_stated_pct, landlord_real_estate_agent_count, landlord_real_estate_agent_pct, landlord_private_person_count, landlord_private_person_pct, landlord_state_housing_count, landlord_state_housing_pct, landlord_community_housing_count, landlord_community_housing_pct, landlord_other_count, landlord_other_pct, landlord_not_stated_count, landlord_not_stated_pct, median_rent_weekly. 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

A3.7/5.0
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 non-structured behavior: a fixed snapshot at 10 August 2021, exclusion of areas with too few people or homes, the ~5,400 suburb / 536 council area scale, and a 5¢ per-call price. It does not describe response shape or pagination, but for a simple read tool that is a minor gap.

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 what the data contains, then coverage, then snapshot date, then cost — a sensible order with no filler sentences. There is small redundancy between 'one snapshot at 10 August 2021' and 'Current to 2021-08-10', and the standalone pricing line is duplicated emphasis rather than new information.

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 four parameters, no output schema and full schema coverage, the description supplies what an agent still needs: what the figures mean, geographic coverage, the fixed snapshot date, and per-call cost. Only a link to related or alternative datasets is missing to make it fully self-sufficient.

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 baseline is 3. The description does add some meaning, notably that the data is a single 2021 snapshot (which constrains what `from`/`to` can return) and that the `fields` list corresponds to rent bands and landlord categories, but it does not explain field selection trade-offs or naming beyond the schema.

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?

States a concrete subject and content: weekly rent in 14 bands, median weekly rent, and landlord type, for suburbs and council areas. An agent can tell it is the rent-payments dataset rather than a generic area stats tool. It is slightly muddied by claiming coverage 'for every suburb and council area', which overlaps the separate lga_area_stats_rent_payments sibling without acknowledging it.

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: the agent can infer this is for suburb-level rent and landlord questions and that the datapack route is documented at `/v1/datasets/rent-payments`. There is no explicit when-to-use/when-not guidance, no pointer to the lga_ sibling for council-area queries, and no mention of related datasets such as mortgage repayments.

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 toolsInspect
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