suburbs_lifestyle_livabilityLivability scores (0–100) per dimension, aggregated from mesh-block scores, with the SA4 benchmark.
| 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": "Suburb livability scores (mesh-block average) + regional benchmark.",
- "example": {
- "area_level": "suburb",
- "area_name": "Belmont North",
- "benchmark": {
- "n_suburbs": 149,
- "region": "Newcastle and Lake Macquarie",
- "scores": {
- "affluence": 66.9,
- "hip": 59.5,
- "lifestyle": 73.4,
- "safety": 84.8
- }
- },
- "n_mesh_blocks": 63,
- "scores": [
- {
- "key": "affluence",
- "label": "Affluence",
- "level": "Moderate",
- "value": 56
- },
- {
- "key": "lifestyle",
- "label": "Lifestyle",
- "level": "Moderate",
- "value": 72
- },
- {
- "key": "safety",
- "label": "Safety",
- "level": "High",
- "value": 76
- }
- ]
- },
- "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"
- },
- "benchmark": {
- "anyOf": [
- {
- "additionalProperties": true,
- "description": "SA4-region benchmark for comparing the suburb's scores.",
- "properties": {
- "n_suburbs": {
- "description": "Suburbs in the region.",
- "title": "N Suburbs",
- "type": "integer"
- },
- "region": {
- "description": "SA4 region name.",
- "title": "Region",
- "type": "string"
- },
- "scores": {
- "description": "Region-average scores.",
- "properties": {
- "affluence": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Region average affluence.",
- "title": "Affluence"
- },
- "hip": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Region average hip.",
- "title": "Hip"
- },
- "lifestyle": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Region average lifestyle.",
- "title": "Lifestyle"
- },
- "safety": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Region average safety.",
- "title": "Safety"
- }
- },
- "title": "LivabilityBenchmarkScores",
- "type": "object"
- }
- },
- "required": [
- "region",
- "n_suburbs",
- "scores"
- ],
- "title": "LivabilityBenchmark",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "SA4 benchmark; null when the region has no bench row."
- },
- "n_mesh_blocks": {
- "description": "Mesh blocks the scores aggregate over.",
- "title": "N Mesh Blocks",
- "type": "integer"
- },
- "scores": {
- "description": "One entry per dimension.",
- "items": {
- "additionalProperties": true,
- "description": "One livability dimension score (0–100).",
- "properties": {
- "key": {
- "description": "Dimension key — affluence | lifestyle | hip | convenience | family | safety | tranquility.",
- "title": "Key",
- "type": "string"
- },
- "label": {
- "description": "Human dimension label.",
- "title": "Label",
- "type": "string"
- },
- "level": {
- "description": "Human level — Very low / Low / Moderate / High / Very high.",
- "title": "Level",
- "type": "string"
- },
- "value": {
- "anyOf": [
- {
- "type": "integer"
- },
- {
- "type": "null"
- }
- ],
- "description": "Score 0–100; null when no data.",
- "title": "Value"
- }
- },
- "required": [
- "key",
- "label",
- "level"
- ],
- "title": "LivabilityScore",
- "type": "object"
- },
- "title": "Scores",
- "type": "array"
- }
- },
- "required": [
- "area_name",
- "area_level",
- "n_mesh_blocks",
- "scores"
- ],
- "title": "LifestyleLivability",
- "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[LifestyleLivability]",
- "type": "object",
- "x-fastmcp-top-level-schema": "ApiResponse_LifestyleLivability_"
-}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 operation's safety profile is covered. The description adds useful behavioral context beyond annotations: scores are 0–100, aggregated from mesh-block scores, and benchmarked against SA4. It does not, however, disclose missing-data behavior, response shape, or which dimensions are included.
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, tightly written sentence that front-loads the score range and output object before the aggregation detail. It contains no filler or redundant clauses, though it does closely echo the title rather than adding substantial new structure.
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 simple, read-only, one-parameter lookup, the description covers the essential purpose, scale, aggregation source, and benchmark. However, there is no output schema, so the description alone must convey what an agent receives; it does not list the dimensions, explain the SA4 benchmark shape, or indicate edge cases such as unavailable data.
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?
There is one required parameter, suburb_name, and the input schema provides only its type with no description. Schema description coverage is 0%, so the description should compensate, but it never mentions the parameter or its expected format. The parameter is self-explanatory from the tool and schema names, but the description adds no meaning beyond what the structured fields already show.
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 (suburb livability scores) and the output semantics: 0–100 scores per dimension, aggregated from mesh-block scores, plus an SA4 benchmark. It lacks an explicit verb like 'get' or 'return', and it does not explicitly distinguish itself from sibling tools such as suburbs_lifestyle_livability_map, but the 'per dimension' and 'SA4 benchmark' details make the core purpose concrete.
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 implies usage: call this when you want numeric livability scores for a suburb rather than a map or narrative. However, it never states when to prefer this over suburbs_lifestyle_livability_map, suburbs_lifestyle_narrative, or suburbs_lifestyle_summary, and it gives no exclusions or alternative guidance.
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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