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Microburbs Australian Property Data

Suburb · Underclass drag

suburbs_demographics_underclass_drag
Read-onlyIdempotent

Welfare-dependency and public-housing shares with the suburb's underclass tier (High / Mid / Low) and the capital-growth impact associated with that tier. Regional and neighbour ranks for the same two metrics are served by /demographics/cohorts.

Input Schema

TableJSON 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": [
      -        {
      -          "additionalProperties": true,
      -          "description": "Welfare dependency + public housing, with the underclass tier.",
      -          "example": {
      -            "growth_impact": {
      -              "band": "Middle 90%",
      -              "pct_per_year": 0
      -            },
      -            "n_microburbs": 77,
      -            "public_housing_basis": "microburb_downscale",
      -            "public_housing_pct": 6.6,
      -            "suburb": "Belmont North",
      -            "tier": "Mid",
      -            "welfare_dependency_pct": 16.2
      -          },
      -          "properties": {
      -            "growth_impact": {
      -              "additionalProperties": true,
      -              "description": "Capital-growth impact associated with the tier.",
      -              "properties": {
      -                "band": {
      -                  "description": "Plain-language name of the band the suburb landed in, suitable for display alongside the figure — e.g. 'Middle 90%', 'High unemployment', 'Low private-school share'. The wording differs per indicator; treat it as a label, not a shared enum.",
      -                  "title": "Band",
      -                  "type": "string"
      -                },
      -                "pct_per_year": {
      -                  "description": "The growth difference historically associated with this band, in percentage points per year on a percent scale — `-3.8` means 3.8 percentage points a year worse, `0.5` means half a point a year better, and `0.0` (the common case, for suburbs in the middle band) means no association either way. A relative difference, not a growth rate in its own right.",
      -                  "title": "Pct Per Year",
      -                  "type": "number"
      -                }
      -              },
      -              "required": [
      -                "pct_per_year",
      -                "band"
      -              ],
      -              "title": "GrowthImpact",
      -              "type": "object"
      -            },
      -            "n_microburbs": {
      -              "anyOf": [
      -                {
      -                  "type": "integer"
      -                },
      -                {
      -                  "type": "null"
      -                }
      -              ],
      -              "description": "Mesh blocks behind the public-housing rollup.",
      -              "title": "N Microburbs"
      -            },
      -            "public_housing_basis": {
      -              "anyOf": [
      -                {
      -                  "enum": [
      -                    "microburb_downscale",
      -                    "census_suburb"
      -                  ],
      -                  "type": "string"
      -                },
      -                {
      -                  "type": "null"
      -                }
      -              ],
      -              "description": "Which denominator produced public_housing_pct — 'microburb_downscale' (mesh-block tenure base, preferred) or 'census_suburb' (suburb census population share).",
      -              "title": "Public Housing Basis"
      -            },
      -            "public_housing_pct": {
      -              "anyOf": [
      -                {
      -                  "type": "number"
      -                },
      -                {
      -                  "type": "null"
      -                }
      -              ],
      -              "description": "Public-housing share of dwellings, as a percentage.",
      -              "title": "Public Housing Pct"
      -            },
      -            "suburb": {
      -              "description": "Canonical SAL name.",
      -              "title": "Suburb",
      -              "type": "string"
      -            },
      -            "tier": {
      -              "description": "Underclass concentration tier. High = welfare >= 20% or public housing >= 15%; Low = welfare < 10% and public housing < 2%.",
      -              "enum": [
      -                "High",
      -                "Mid",
      -                "Low"
      -              ],
      -              "title": "Tier",
      -              "type": "string"
      -            },
      -            "welfare_dependency_pct": {
      -              "description": "Share of working-age residents on JobSeeker / Disability Support / carer payments, as a percentage.",
      -              "title": "Welfare Dependency Pct",
      -              "type": "number"
      -            }
      -          },
      -          "required": [
      -            "suburb",
      -            "welfare_dependency_pct",
      -            "tier",
      -            "growth_impact"
      -          ],
      -          "title": "UnderclassDrag",
      -          "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[UnderclassDrag]",
      -  "type": "object",
      -  "x-fastmcp-top-level-schema": "ApiResponse_UnderclassDrag_"
      -}New value: +null
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds content-level context about tier categories and capital-growth impact but discloses no output shape, units, or missing-data behavior. Given the strong annotation coverage, the modest additional behavioral disclosure is acceptable.

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?

Two compact sentences with no filler; the first presents the core output and the second routes to a sibling tool. The slash notation is slightly cryptic, but the overall structure is efficient and 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?

With one simple parameter and no output schema, the description should clarify what the caller receives; it lists the relevant metrics but not their structure, units, or formatting. It gives enough topical context for a caller with a known suburb name, though behavior for unknown or invalid suburbs is left unspecified.

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 0%, and the description does not specify format, case sensitivity, or accepted values for `suburb_name`. The parameter name is self-explanatory, so heavy compensation is not required, but the description adds no semantic meaning beyond the schema.

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 enumerates the returned concepts: welfare-dependency share, public-housing share, the suburb's underclass tier (High/Mid/Low), and the associated capital-growth impact. It distinguishes this tool from the sibling cohorts tool by explicitly excluding regional and neighbour ranks. It lacks a direct verb like 'returns,' but the resource and scope are clear.

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?

It explicitly names `/demographics/cohorts` as the tool that serves regional and neighbour ranks for the same two metrics, giving an alternative for a common variation. It does not discuss when to prefer this over other demographics or market tools, but the metric-specific routing is clear enough.

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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