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Microburbs Australian Property Data

suburbs_demographics_cohorts

How the suburb ranks inside its SA4 region and against its touching neighbours on renter share, welfare dependency, overseas-born parents and public housing.

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

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state that this is a read-only operation (obvious but not stated), nor does it mention any limitations such as data source, update frequency, or whether it works only for Australian suburbs. It only describes the output concept without revealing potential side effects, performance, or constraints.

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, well-structured sentence that front-loads the core concept (ranking) and lists the specific metrics. There is no filler or redundancy. Every word adds value, making it highly efficient for an agent to parse.

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 specifies the metrics and comparison scope (SA4 region and neighbors), which is sufficient for basic understanding. However, it lacks details about the output format (though an output schema exists, its content is not provided here), data coverage, or any limitations. Given the tool's moderate complexity, the description is adequate but not exhaustive.

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?

There is only one parameter, suburb_name, and the description does not add any meaning beyond the schema. It does not clarify the expected format (e.g., full name vs. postcode), case sensitivity, or that it must be an Australian suburb. Since schema coverage is 0%, the description should compensate, but it entirely ignores the 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 states the tool's function: ranking a suburb against its SA4 region and neighboring suburbs on specific metrics (renter share, welfare dependency, overseas-born parents, public housing). This is a specific verb-resource pairing and distinguishes it from generic demographics tools like suburbs_demographics_tenure or suburbs_demographics_all by naming the exact cohorts. It does not explicitly name alternative tools, but the purpose is unambiguous.

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 versus its siblings. There is no mention of alternatives or when not to use it. The description only states what it does, leaving the agent to infer its use case from the metrics listed. No prerequisites or contextual conditions are provided.

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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