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Microburbs Australian Property Data

List LGAs

lga_list
Read-onlyIdempotent

All Australian LGAs. Optional ?state= filter (e.g. 'NSW'). Returns {lga, state} per row. Flat cost.

Price: 3¢ per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoFilter by state / territory (NSW, VIC, ...). Optional — ~540 LGAs nationally.

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": [
      -        {
      -          "items": {
      -            "description": "One row in the LGA directory.",
      -            "example": {
      -              "lga": "Lake Macquarie",
      -              "state": "NSW"
      -            },
      -            "properties": {
      -              "lga": {
      -                "description": "LGA name.",
      -                "title": "Lga",
      -                "type": "string"
      -              },
      -              "state": {
      -                "description": "State / Territory abbreviation (NSW, VIC, ...).",
      -                "title": "State",
      -                "type": "string"
      -              }
      -            },
      -            "required": [
      -              "lga",
      -              "state"
      -            ],
      -            "title": "LgaListItem",
      -            "type": "object"
      -          },
      -          "type": "array"
      -        },
      -        {
      -          "type": "null"
      -        }
      -      ],
      -      "description": "The endpoint's payload, or `null` when Microburbs has no value.",
      -      "title": "Data"
      -    },
      -    "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[list[LgaListItem]]",
      -  "type": "object",
      -  "x-fastmcp-top-level-schema": "ApiResponse_list_LgaListItem__"
      -}New value: +null
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds the return shape, the flat-cost model, and the per-call price, which are genuinely useful behavioral details beyond the annotations.

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 compact and front-loaded: it states the resource, the filter, the output shape, and the cost in four short pieces. Every sentence earns its place and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one optional parameter, the description is complete: it specifies the output fields, the optional filter, the closed-world scope of all Australian LGAs, and the price. Since there is no output schema, providing the row shape is essential and is done well.

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?

Schema coverage is 100%, and the schema already explains the state parameter including examples and national count. The description mostly restates the filter behavior, so it adds no significant semantic value beyond the schema.

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?

The description clearly identifies the resource as all Australian LGAs and the operation as returning them, with an optional state filter. 'Returns {lga, state} per row' makes the tool's output explicit, and the naming/scope distinguishes it from lga_profile and region-list siblings.

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 optional state filter gives some usage direction, but the description never says when to prefer this tool over alternatives like lga_profile, sa4_list, or suburbs_list. The intended use is implied rather than stated.

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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