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Microburbs Australian Property Data

by au.com.microburbs
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suburbs_shapes_mesh_blocks

ABS 2021 mesh-block polygons covering the suburb (GeoJSON FeatureCollection, MB code per feature).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geojsonNoWhen false, geometry is dropped — every Feature keeps its `properties` but its `geometry` is null. Use it to fetch the counts and per-feature attributes without the coordinates (default true — response unchanged).
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

B3.4/5.0
Behavior3/5

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

Annotations are absent, so the description carries the full burden. It does disclose the data source, year, geometry type, and per-feature attribute (MB code), which is useful. However, it omits details like coordinate reference system, response size, or read-only behavior.

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?

A single sentence that packs the essential facts: data source, year, geometry type, format, and attribute. It is front-loaded with the core resource and contains no filler.

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?

With an output schema present, the return format is partially covered. However, the description leaves gaps around how to specify suburb_name and when to choose this tool over sibling shape tools, making it only minimally adequate.

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 coverage is only 50%: the geojson parameter is well-described in the schema, but suburb_name lacks any description. The tool description does not compensate, only indirectly referencing 'the suburb', adding little beyond the parameter name.

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?

States a specific resource (ABS 2021 mesh-block polygons) and format (GeoJSON FeatureCollection), with per-feature MB code. This clearly distinguishes it from sibling shape tools like suburbs_shapes_boundary or suburbs_shapes_busy_roads.

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 on when to use this tool versus the many other suburbs_shapes_* alternatives. The description only defines the output, not the use case, exclusions, or selection criteria.

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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