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Microburbs Australian Property Data

suburbs_shapes_busy_roads

Busy-road line segments clipped to the suburb — the report's road-noise exposure proxy.

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

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states what the data represents (road-noise proxy) but does not describe behavior such as error handling, rate limits, or the structure of the response. It doesn't contradict any annotations (none exist), but it fails to add meaningful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise, but it is under-specified. It could be improved by adding a sentence about the purpose and parameters without becoming verbose. The current structure is efficient but sacrifices necessary information.

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

Completeness2/5

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

For a tool with two parameters and no annotations, the description is incomplete. It lacks usage guidance, parameter semantics, and behavioral details. Although an output schema exists, the description doesn't explain what the agent will receive or how to interpret it, leaving critical gaps for correct invocation.

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?

The tool description does not mention either parameter, and the schema only documents the 'geojson' parameter. The 'suburb_name' parameter lacks any description in the schema, and the tool description offers no help, leaving its semantics entirely implicit. The geojson description exists in the schema but not in the tool description, so the description adds no value 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?

The description clearly identifies the resource (busy-road line segments) and the operation (clipped to the suburb), and explains its role as a road-noise exposure proxy. It differentiates from sibling tools like suburbs_shapes_boundary and suburbs_shapes_noise_heatmap by specifying line segments vs. boundary or heatmap. However, it doesn't explicitly state the output format (e.g., GeoJSON) or that it returns features, which could be clearer.

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?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of when to choose this over suburbs_shapes_noise_heatmap or other shape tools, nor any exclusions or prerequisites. An agent must infer the use case from the name and description alone, which is insufficient for a large sibling set.

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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