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Microburbs Australian Property Data

Suburb · Applications

suburbs_development_da_count
Read-onlyIdempotent

Shown in the suburb report as the 'Applications' headline figure in the Development section.

Count of development applications in the last 5 years, one per site address, in the dwelling, subdivision, aged-care, education, industrial and utilities categories. /development/applications lists every category so its total is larger.

Price: 6¢ per call.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "suburb_name": "<suburb_name>"
    },
    "name": "suburbs_development_da_count"
  }
}

Input Schema

NameRequiredDescriptionDefault
suburb_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
      -  "properties": {
      -    "available": {
      -      "anyOf": [
      -        {
      -          "type": "boolean"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "`false` on no-data responses. Omitted on success — branch on `data !== null` if you want a single discriminator.",
      -      "title": "Available"
      -    },
      -    "data": {
      -      "anyOf": [
      -        {
      -          "example": {
      -            "da_count": 0
      -          },
      -          "properties": {
      -            "da_count": {
      -              "anyOf": [
      -                {
      -                  "type": "integer"
      -                },
      -                {
      -                  "type": "null"
      -                }
      -              ],
      -              "description": "Number of recent DAs in the suburb.",
      -              "title": "Da Count"
      -            }
      -          },
      -          "required": [
      -            "da_count"
      -          ],
      -          "title": "DaCount",
      -          "type": "object"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "The endpoint's payload, or `null` when Microburbs has no value."
      -    },
      -    "message": {
      -      "anyOf": [
      -        {
      -          "type": "string"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "Human-readable explanation. Omitted on success.",
      -      "title": "Message"
      -    },
      -    "reason": {
      -      "anyOf": [
      -        {
      -          "type": "string"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "Machine-readable slug naming the no-data condition (e.g. `no_avm_for_GANSW704074813`). Stable per endpoint. Omitted on success.",
      -      "title": "Reason"
      -    }
      -  },
      -  "title": "ApiResponse[DaCount]",
      -  "type": "object",
      -  "x-fastmcp-top-level-schema": "ApiResponse_DaCount_"
      -}New value: +null
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world behavior, so the bar is lower. The description still adds real context beyond them: the 5-year lookback, deduplication by site address (one per site), the included category subset, and the 6¢ per-call cost.

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?

Front-loaded with the headline figure and its definition, followed by the disambiguation note and pricing. Three short blocks, no filler, and the most decision-relevant facts come first.

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?

For a one-parameter read tool with no output schema, it covers scope, category coverage, deduplication, differentiation and cost. The only meaningful gap is what the return value looks like (a bare integer) and how `suburb_name` should be formatted.

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?

There is a single required parameter, `suburb_name`, and schema description coverage is 0%, so the description must carry the burden. It says nothing about expected format (plain name vs. ID, state disambiguation), though the parameter name is largely self-explanatory.

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?

States a precise verb and resource ("Count of development applications") plus the exact scope: last 5 years, one per site address, and a named category list. It also frames the figure's role in the suburb report ("'Applications' headline figure in the Development section"), so an agent knows exactly what number this returns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Differentiates itself from `/development/applications` by explaining that the other lists every category and therefore has a larger total, which routes the agent between the two. It does not state an explicit when-not-to-use rule or name the sibling tool directly, but the comparison is clear enough to choose correctly.

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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