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Microburbs Australian Property Data

suburbs_demographics_ancestry_map

The dominant ancestry (and its share) in each of the suburb's microburbs, plus suburb-level ancestry shares. Pilot coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
suburb_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe endpoint's payload, or `null` when Microburbs has no value.
reasonNoMachine-readable slug naming the no-data condition (e.g. `no_avm_for_GANSW704074813`). Stable per endpoint. Omitted on success.
messageNoHuman-readable explanation. Omitted on success.
availableNo`false` on no-data responses. Omitted on success — branch on `data !== null` if you want a single discriminator.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It states the data scope (microburbs and suburb-level) and the caveat 'Pilot coverage', which is a useful behavioral trait. However, it does not disclose any operational behavior such as data format, error handling, or whether this is a read-only operation, though the name and output schema reduce some of that need.

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?

The description is a single sentence that conveys the data content and the early-access limitation with zero filler. It is front-loaded and every phrase earns its place.

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

Completeness3/5

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

For a simple one-parameter tool with an output schema, the description covers the core data returned. However, it lacks usage context, does not distinguish from sibling tools, and does not explain the 'microburbs' concept or the practical implications of 'Pilot coverage' for an agent deciding to call it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the suburb_name parameter beyond the word 'suburb's'. It does not mention expected format, valid values, or how to obtain a valid suburb name. The parameter's meaning is inferable from its name, but the description adds no semantic value.

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 clearly states the tool returns dominant ancestry (and share) for each microburbs plus suburb-level ancestry shares. It identifies the resource and content, but does not differentiate from the closely named sibling suburbs_ethnicity_ancestry, which likely covers similar ancestry data.

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?

No guidance is given on when to use this tool instead of alternatives such as suburbs_demographics_all or suburbs_ethnicity_ancestry. The only contextual hint is 'Pilot coverage', which implies limited scope but does not direct an agent toward or away from this tool.

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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