suburbs_lifestyle_summaryPOI category breakdown, terrain scalars, nearest train/shop and beach/hospital flags.
| Name | Required | Description | Default |
|---|---|---|---|
| suburb_name | Yes |
Changes observed during successful MCP inspections.
Output 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": "POI category breakdown, terrain scalars and landmark flags.",
- "example": {
- "area_level": "suburb",
- "area_name": "Belmont North",
- "has_beach": true,
- "has_hospital": true,
- "nearest_beach_km": 1.5,
- "nearest_hospital_km": 1.4,
- "nearest_shop": {
- "category": "Supermarket",
- "dist_km": 1.2,
- "name": "Coles"
- },
- "nearest_train": {
- "dist_km": 1.4,
- "name": "Jewells railway station"
- },
- "poi_categories": [
- {
- "category": "Education",
- "count": 9,
- "top_subtypes": [
- {
- "count": 5,
- "label": "School"
- },
- {
- "count": 3,
- "label": "Childcare"
- },
- {
- "count": 1,
- "label": "Preschool"
- }
- ]
- }
- ],
- "terrain": {
- "aspect_compass": "SE",
- "avg_aspect_deg": 149,
- "median_elevation_m": 26,
- "median_slope_deg": 5.6,
- "n_flat": 698,
- "n_moderate": 830,
- "n_properties": 1759,
- "n_steep": 231,
- "pct_steep": 13
- },
- "total_pois": 43
- },
- "properties": {
- "area_level": {
- "description": "Always 'suburb' for these endpoints.",
- "title": "Area Level",
- "type": "string"
- },
- "area_name": {
- "description": "Suburb (SAL) name.",
- "title": "Area Name",
- "type": "string"
- },
- "has_beach": {
- "description": "A beach exists within ~50 km.",
- "title": "Has Beach",
- "type": "boolean"
- },
- "has_hospital": {
- "description": "A hospital exists within ~50 km.",
- "title": "Has Hospital",
- "type": "boolean"
- },
- "nearest_beach_km": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Distance to the nearest beach (km); null when none within ~50 km.",
- "title": "Nearest Beach Km"
- },
- "nearest_hospital_km": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Distance to the nearest hospital (km); null when none within ~50 km.",
- "title": "Nearest Hospital Km"
- },
- "nearest_shop": {
- "anyOf": [
- {
- "additionalProperties": true,
- "description": "Nearest major shop / shopping centre to the suburb centroid.",
- "properties": {
- "category": {
- "description": "Shop category (e.g. 'Supermarket').",
- "title": "Category",
- "type": "string"
- },
- "dist_km": {
- "description": "Straight-line distance (km).",
- "title": "Dist Km",
- "type": "number"
- },
- "name": {
- "description": "Shop name (e.g. 'Coles').",
- "title": "Name",
- "type": "string"
- }
- },
- "required": [
- "name",
- "category",
- "dist_km"
- ],
- "title": "NearestShop",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "Nearest major shop."
- },
- "nearest_train": {
- "anyOf": [
- {
- "description": "Nearest train station to the suburb centroid.",
- "properties": {
- "dist_km": {
- "description": "Straight-line distance (km).",
- "title": "Dist Km",
- "type": "number"
- },
- "name": {
- "description": "Station name.",
- "title": "Name",
- "type": "string"
- }
- },
- "required": [
- "name",
- "dist_km"
- ],
- "title": "NearestTrain",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "Nearest train station."
- },
- "poi_categories": {
- "description": "Per-category POI counts, largest first.",
- "items": {
- "additionalProperties": true,
- "description": "One L1 POI category with its top subtypes.",
- "properties": {
- "category": {
- "description": "Friendly category name (e.g. 'Food Drink').",
- "title": "Category",
- "type": "string"
- },
- "count": {
- "description": "Total POIs in this category.",
- "title": "Count",
- "type": "integer"
- },
- "top_subtypes": {
- "description": "Most common subtypes inside the category.",
- "items": {
- "description": "One L2 subtype count inside a POI category.",
- "properties": {
- "count": {
- "description": "Number of POIs of this subtype.",
- "title": "Count",
- "type": "integer"
- },
- "label": {
- "description": "Subtype label, title-cased (e.g. 'Restaurant').",
- "title": "Label",
- "type": "string"
- }
- },
- "required": [
- "label",
- "count"
- ],
- "title": "PoiSubtypeCount",
- "type": "object"
- },
- "title": "Top Subtypes",
- "type": "array"
- }
- },
- "required": [
- "category",
- "count",
- "top_subtypes"
- ],
- "title": "PoiCategoryBreakdown",
- "type": "object"
- },
- "title": "Poi Categories",
- "type": "array"
- },
- "terrain": {
- "anyOf": [
- {
- "additionalProperties": true,
- "description": "Pre-aggregated terrain scalars across the suburb's properties.",
- "properties": {
- "aspect_compass": {
- "description": "Average aspect as a compass point (e.g. 'SE').",
- "title": "Aspect Compass",
- "type": "string"
- },
- "avg_aspect_deg": {
- "description": "Average aspect (compass degrees, 0 = N).",
- "title": "Avg Aspect Deg",
- "type": "integer"
- },
- "median_elevation_m": {
- "description": "Median elevation (metres).",
- "title": "Median Elevation M",
- "type": "number"
- },
- "median_slope_deg": {
- "description": "Median block slope (degrees).",
- "title": "Median Slope Deg",
- "type": "number"
- },
- "n_flat": {
- "description": "Properties on flat blocks.",
- "title": "N Flat",
- "type": "integer"
- },
- "n_moderate": {
- "description": "Properties on moderate slopes.",
- "title": "N Moderate",
- "type": "integer"
- },
- "n_properties": {
- "description": "Properties with terrain data.",
- "title": "N Properties",
- "type": "integer"
- },
- "n_steep": {
- "description": "Properties on steep slopes.",
- "title": "N Steep",
- "type": "integer"
- },
- "pct_steep": {
- "description": "Share of properties on steep slopes (%).",
- "title": "Pct Steep",
- "type": "integer"
- }
- },
- "required": [
- "n_properties",
- "median_slope_deg",
- "median_elevation_m",
- "avg_aspect_deg",
- "aspect_compass",
- "n_steep",
- "n_moderate",
- "n_flat",
- "pct_steep"
- ],
- "title": "TerrainSummary",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "Terrain scalars; null when no terrain data."
- },
- "total_pois": {
- "description": "Total POIs across all categories.",
- "title": "Total Pois",
- "type": "integer"
- }
- },
- "required": [
- "area_name",
- "area_level",
- "total_pois",
- "poi_categories",
- "has_beach",
- "has_hospital"
- ],
- "title": "LifestyleSummary",
- "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[LifestyleSummary]",
- "type": "object",
- "x-fastmcp-top-level-schema": "ApiResponse_LifestyleSummary_"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe read-only nature is provided structurally. The description adds the data categories returned but not behavioral details such as how the flags are computed, whether some values can be absent, or whether the breakdown is exhaustive. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that front-loads the tool's main output categories and contains no filler. Every word adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read-only summary, the description names the main output categories and is sufficient to attempt a call. But with no output schema, it leaves the response shape and types vague, and the large sibling family means an agent would benefit from clearer routing guidance. It is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single required parameter, suburb_name, is self-explanatory by name and fits the tool's subject, so an agent can reasonably supply a suburb identifier. However, schema description coverage is 0% and the description does not add format, normalization, or accepted-value guidance, so the parameter handling relies mostly on the property name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource scope (suburb) and enumerates the exact output content: POI category breakdown, terrain scalars, and nearest train/shop and beach/hospital flags. It therefore lets an agent know what data this tool provides. However, it lacks an explicit verb such as 'returns' or 'summarizes' and does not sharply distinguish it from the nearby lifestyle siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance about when to use this tool instead of suburbs_lifestyle_pois, suburbs_lifestyle_landmarks, suburbs_lifestyle_livability, or suburbs_lifestyle_narrative. The intended usage is only implied by the listed output categories, which is weak given how many lifestyle siblings exist.
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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