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Microburbs Australian Property Data

by au.com.microburbs
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Suburb · Mortgage repayments

suburbs_area_stats_mortgage_repayments
Read-onlyIdempotent

What home-owners with a mortgage pay each month: repayments in 11 bands from under $300 to $4,000 or more, and the median monthly repayment, for every suburb and council area.

Coverage: About 7,200 suburbs and localities and 498 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/mortgage-repayments.

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_mortgage_repayments"
  }
}

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_mortgaged_households, mortgage_0_299_count, mortgage_0_299_pct, mortgage_300_449_count, mortgage_300_449_pct, mortgage_450_599_count, mortgage_450_599_pct, mortgage_600_799_count, mortgage_600_799_pct, mortgage_800_999_count, mortgage_800_999_pct, mortgage_1000_1399_count, mortgage_1000_1399_pct, mortgage_1400_1799_count, mortgage_1400_1799_pct, mortgage_1800_2399_count, mortgage_1800_2399_pct, mortgage_2400_2999_count, mortgage_2400_2999_pct, mortgage_3000_3999_count, mortgage_3000_3999_pct, mortgage_4000_plus_count, mortgage_4000_plus_pct, mortgage_not_stated_count, mortgage_not_stated_pct, median_mortgage_monthly. 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

A3.9/5.0
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 earns credit for adding what they cannot: a 5¢ per-call charge, exclusion of areas with too few people or homes, and an explicit data vintage (2021-08-10). The pricing disclosure in particular materially affects invocation decisions. It stops short of describing response shape or pagination, hence not a 5.

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 the payload sentence, then coverage, then price, then a pointer to the full dataset doc. Every sentence carries information; the only minor cost is the somewhat long parenthetical about excluded areas, but it is not filler.

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 must convey what comes back, and it does at a conceptual level (11 count/percent bands plus median_mortgage_monthly), with a pointer to the dataset page for fields and method. Combined with 100% schema coverage on inputs, an agent has enough to call it correctly; only the concrete response envelope is unspecified.

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 all four parameters are already documented, including the exact-format requirement for suburb_name and the full field allowlist. The description adds conceptual framing (the 11 bands and the median) that helps interpret the `fields` values, but no format or edge-case detail beyond the schema. Baseline 3 is appropriate.

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 a specific resource and measure ('repayments in 11 bands from under $300 to $4,000 or more, and the median monthly repayment') and its unit of geography ('every suburb and council area'), which lets an agent separate it from siblings like suburbs_area_stats_rent_payments or lga_area_stats_mortgage_repayments without opening a schema.

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?

It gives useful qualifying context — ~7,200 suburbs and 498 council areas, small areas excluded, single snapshot at 2021-08-10 — so an agent knows whether the data suits the question. But it never states when to prefer this over the LGA-level or rent-payments siblings, nor any exclusion; usage is only implied by the name.

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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