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Microburbs Australian Property Data

suburbs_demographics_tenure

Explicit total owner-occupation rate plus owned-outright / mortgaged / renting / public-housing shares — a suburb rollup and the per-microburb downscaled Census shares. owner_occupied_pct is the requested headline; it equals owned outright plus mortgaged and is null if either is absent. census_year makes the 2021 reference period explicit.

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

C2.7/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It adds useful context: owner_occupied_pct is null if either component is absent, and census_year pins the 2021 reference period. However, it doesn't explicitly state this is a read-only operation, nor describe any other behavioral traits like error conditions or output format. It provides some transparency but leaves room for more.

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

Conciseness4/5

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

The description is concise, two sentences, and front-loads the core purpose before diving into specifics. It avoids fluff and uses technical detail efficiently. Not overly long, but it could be slightly more structured with a direct statement of the parameter.

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?

The description provides useful field-level details and the census year, but omits the parameter entirely. With one required parameter, it should at least say it takes a suburb name. Since an output schema exists, the description needn't detail the return structure, but the missing parameter and lack of usage context make it incomplete for an agent to call correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description never mentions the suburb_name parameter. The only parameter is completely undocumented in the description, leaving the agent to infer that it's a suburb name from the tool name. This is a major gap since the description should compensate for the lack of schema documentation.

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 returns owner-occupation rate and shares for owned-outright, mortgaged, renting, and public-housing, making the resource specific. It explains the headline field owner_occupied_pct and its calculation, which distinguishes it from other demographics tools like age or income. However, it doesn't explicitly say 'for a suburb's tenure breakdown' in a crisp one-liner, so it's not quite 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 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 alternatives. It doesn't mention that this is the tenure-specific tool, nor does it point to any sibling like suburbs_demographics_all for broader demographic data. The context of many siblings makes this gap significant.

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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