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Microburbs Australian Property Data

properties_risks_flood

Modelled flood overlays within 1 km. Read on_property — a returned row means "found nearby", not "this property floods".

Price: 10¢ per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geojsonNoWhen true, add a `geojson` FeatureCollection of the hazard polygons clipped to a 1km-radius circle around the property, plus `geojson_meta` (default false — response unchanged).
gnaf_idYes

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

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden and does so well: it discloses that the data is modelled, that a returned row means 'found nearby' rather than 'this property floods', and that the call costs 10¢. This prevents a serious misinterpretation, though more details about limits or failure modes could be added.

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?

Three short, front-loaded units: purpose, critical interpretation caveat, and price. There is no filler, and the code formatting plus bold price make the important caveats scannable.

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?

Given the output schema exists and there are only two parameters, the description plus schema cover the core invocation details: required `gnaf_id`, optional `geojson`, spatial radius, interpretation, and billing. It could be more complete by naming sibling-distinguishing use cases, but nothing essential for a safe call is missing.

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?

The schema already documents `geojson` in detail, and the description's 'within 1 km' adds spatial meaning. However, `gnaf_id` is left with only a type in both the schema and the description, and with 50% schema coverage the description does not fully compensate for the required parameter.

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 ('Modelled flood overlays') and the spatial scope ('within 1 km'), which is enough to distinguish it from bushfire, erosion, and landslide siblings. It lacks an explicit verb like 'Returns' and does not contrast itself with `properties_risks_historical_flood`, so it stops short of a 5.

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?

The intended use is implied: call this tool for modelled flood overlays within 1 km of a property. The `on_property` instruction is useful, but the description never states when to prefer this tool over `properties_risks_historical_flood`, `properties_risks_all`, or other risk tools, and it gives no explicit exclusions.

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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