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Microburbs Australian Property Data

properties_context_nearby_for_sale

Currently for-sale listings within radius_km of the property (newest first, max 30) with AVM and rent-yield comparison.

Price: 20¢ per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gnaf_idYes
radius_kmNoSearch radius in km (0.1-5).

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?

The description discloses key behavioral traits: results are newest first, capped at 30, and cost 20¢ per call. These details go beyond what annotations (none) or schema provide. It does not state whether the operation is read-only, but for a listing retrieval this is likely implied; given the absence of annotations, this level of transparency is above average.

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, efficient sentence covering the core function, followed by a clear pricing note. No filler, and the most important information (what and how) is front-loaded.

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?

The description covers purpose, ordering, limit, and cost, which is good for a simple two-parameter tool. However, it omits explanation of the required gnaf_id parameter, and the output schema (though present) does not cover parameter explanation. Given the low parameter count and existing output schema, this is acceptable but not complete.

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 only 50% (radius_km is described, gnaf_id is not). The description mentions radius_km but adds no new meaning beyond the schema. It does not explain gnaf_id, which is required, nor its format or source. The description fails to compensate for the undocumented required parameter.

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?

Description clearly states the tool returns current for-sale listings within a radius of a property, with AVM and rent-yield comparison, and orders them newest first with a max of 30. This distinguishes it from siblings like properties_comparables_recent_sales_nearby (recent sales, not active listings) and properties_sale_history (historical sales).

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?

It provides context (currently for-sale listings near a property) but does not explicitly mention when to use this tool over alternatives like suburbs_listings_for_sale or properties_surroundings_properties. No explicit exclusions or alternative routing is given, so the agent must infer usage from the stated purpose.

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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