Microburbs Australian Property Data

Suburb · Field of study

suburbs_area_stats_field_of_study

Read-onlyIdempotent

What residents studied for their post-school qualification: engineering, health, management and commerce, IT, education, creative arts, trades and more, as counts and shares for every suburb and council area.

Coverage: About 8,900 suburbs and localities and 543 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/field-of-study.

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_field_of_study"
  }
}

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_with_qualification, natural_and_physical_sciences_count, natural_and_physical_sciences_pct, information_technology_count, information_technology_pct, engineering_count, engineering_pct, architecture_and_building_count, architecture_and_building_pct, agriculture_and_environment_count, agriculture_and_environment_pct, health_count, health_pct, education_count, education_pct, management_and_commerce_count, management_and_commerce_pct, society_and_culture_count, society_and_culture_pct, creative_arts_count, creative_arts_pct, food_hospitality_and_personal_services_count, food_hospitality_and_personal_services_pct, mixed_field_programmes_count, mixed_field_programmes_pct, field_inadequately_described_count, field_inadequately_described_pct, field_not_stated_count, field_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

A3.9/5.0

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 non-obvious behavior: a per-call price of 5¢, a single fixed snapshot at 2021-08-10, exclusion of areas too small for reliable figures, and a pointer to the dataset endpoint for method. A small gap remains in not explaining how the from/to period parameters behave against a single-snapshot 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 the subject, then coverage, currency, and price in a tight scannable block. The field enumeration is long but earns its place by previewing the schema's `fields` values; nothing is padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only lookup with no output schema, four fully described parameters, and exhaustive annotations, the description supplies everything an agent needs: what is counted, geographic scope, snapshot date, small-area exclusions, cost, and where to find the method. The only unresolved nuance (from/to on a single snapshot) is minor.

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 and suburb_name are all documented in the schema itself; baseline 3 applies. The description contributes only indirectly ('counts and shares'), and notably does not reconcile the from/to period filters with the stated single 2021 snapshot, which is the one piece of parameter meaning the schema leaves ambiguous.

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 the specific resource precisely: post-school qualification field-of-study counts and shares for suburbs/council areas, with the constituent fields spelled out (engineering, health, IT, trades, etc.). That is far beyond tautology. It stops short of 5 because it says coverage spans 'every suburb and council area' even though a separate lga_area_stats_field_of_study sibling exists, so the suburb-vs-LGA boundary is blurred.

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?

Implicit usage context is clear (you want qualification-field figures for a place), and the coverage note tells the agent which areas lack data. But there is no explicit when-to-use guidance against the LGA variant or against the general suburbs_area_stats_education tool, and no stated prerequisite beyond the suburb_name format which lives in the schema.

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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