suburbs_market_growth_driversPer-indicator capital-growth attribution for the suburb.
Each row pairs the suburb's own value for an indicator with the capital-growth differential our matched studies attribute to it, in percentage points. Covers supply & demand pressure, market signals, environmental risks and demographic composition.
| 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": "Every capital-growth driver the v6 report attributes to a suburb.",
- "example": {
- "area_level": "suburb",
- "area_name": "Belmont North",
- "drivers": [
- {
- "band": "(0.999, 1.51]",
- "basis": "nat_rel",
- "category": "supply_demand",
- "direction": "positive",
- "horizon_years": 2,
- "impact_pct_per_year": 1.11,
- "indicator": "Months of Supply",
- "key": "prop_list_months_of_supply",
- "source": "thresholds_v3_prod",
- "unit": "months",
- "value": 1
- },
- {
- "band": "present",
- "basis": "matched_control",
- "category": "risks",
- "direction": "neutral",
- "horizon_years": 1,
- "impact_pct_per_year": -0.29,
- "indicator": "Contamination",
- "key": "contamination",
- "source": "dbyd_matched_cg",
- "unit": "%",
- "value": 18.19
- },
- {
- "band": "Top",
- "basis": "nat_bin",
- "category": "demographics",
- "direction": "positive",
- "horizon_years": 4,
- "impact_pct_per_year": 0.43,
- "indicator": "Cultural Integration",
- "key": "cultural_integration",
- "source": "cultural_integration_sal",
- "unit": "score_0_100",
- "value": 61.8
- }
- ]
- },
- "properties": {
- "area_level": {
- "description": "Always 'suburb' for this endpoint.",
- "title": "Area Level",
- "type": "string"
- },
- "area_name": {
- "description": "Suburb (SAL) name.",
- "title": "Area Name",
- "type": "string"
- },
- "drivers": {
- "description": "One row per indicator that carries an attributed impact. Indicators with no value for this suburb, or no matching band, are omitted rather than returned as zero.",
- "items": {
- "description": "One indicator and the capital-growth differential attributed to it.",
- "properties": {
- "band": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "The band the suburb's value fell into: a numeric interval for threshold-model drivers, 'present'/'absent' for risks, or the tier name for cultural integration.",
- "title": "Band"
- },
- "basis": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Control group the differential is relative to: 'nat_rel' (national), 'gccsa_rel' (capital-city region), 'nat_bin' (national tier), 'matched_control' (matched address pairs).",
- "title": "Basis"
- },
- "category": {
- "description": "Report section the driver belongs to: 'supply_demand', 'market', 'risks' or 'demographics'.",
- "title": "Category",
- "type": "string"
- },
- "direction": {
- "description": "'positive', 'negative' or 'neutral' — the tone the report gives the chip.",
- "title": "Direction",
- "type": "string"
- },
- "horizon_years": {
- "anyOf": [
- {
- "type": "integer"
- },
- {
- "type": "null"
- }
- ],
- "description": "Window the differential was measured over. Threshold-model studies run 2 or 4 years and the report presents the raw differential as an annual rate; the cultural-integration model annualises its 4-year figure first; risk coefficients are already per-year.",
- "title": "Horizon Years"
- },
- "impact_pct_per_year": {
- "description": "Capital-growth differential attributed to this indicator, in percentage points, exactly as the report renders it.",
- "title": "Impact Pct Per Year",
- "type": "number"
- },
- "indicator": {
- "description": "Human label, matching the report's row label.",
- "title": "Indicator",
- "type": "string"
- },
- "key": {
- "description": "Stable machine identifier for the indicator.",
- "title": "Key",
- "type": "string"
- },
- "source": {
- "description": "Model the row came from: 'thresholds_v3_prod', 'dbyd_matched_cg' or 'cultural_integration_sal'.",
- "title": "Source",
- "type": "string"
- },
- "unit": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Unit of `value` — e.g. 'months', 'fraction', 'AUD', '%', 'ANEF', 'score_0_100'.",
- "title": "Unit"
- },
- "value": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "The suburb's own value for this indicator (see `unit`).",
- "title": "Value"
- }
- },
- "required": [
- "category",
- "key",
- "indicator",
- "direction",
- "impact_pct_per_year",
- "source"
- ],
- "title": "GrowthDriver",
- "type": "object"
- },
- "title": "Drivers",
- "type": "array"
- }
- },
- "required": [
- "area_name",
- "area_level",
- "drivers"
- ],
- "title": "GrowthDrivers",
- "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[GrowthDrivers]",
- "type": "object",
- "x-fastmcp-top-level-schema": "ApiResponse_GrowthDrivers_"
-}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, covering safety. The description adds valuable context: the output structure (rows with value and differential), the source ('our matched studies'), and the covered categories. This goes beyond the annotations without contradicting them.
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 two concise paragraphs. The first sentence front-loads the core purpose, followed by a brief explanation of the output format and coverage. Every sentence adds value without unnecessary fluff.
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 read-only tool with a single parameter and no output schema, the description adequately explains the output structure and content. It does not mention error handling or pagination, but those are not critical for such a simple tool. It is complete enough for an agent to call it correctly.
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?
Schema description coverage is 0%, so the description must compensate for the single parameter, suburb_name. The parameter is self-evident from the tool's name and description ('for the suburb'), but the description does not explicitly state its format or any constraints. Since it is a simple string and the purpose is clear, the lack of explicit documentation is minor.
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 states a specific verb+resource: 'Per-indicator capital-growth attribution for the suburb.' It clearly defines the output as rows pairing the suburb's indicator value with the growth differential in percentage points, and lists the categories covered. This distinguishes it from generic market tools like suburbs_market_all or risk-specific ones like suburbs_risks_capital_growth_impact.
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?
No explicit guidance on when to use this tool versus alternatives. It does not mention any exclusions or alternatives, leaving the agent to infer from the description that it is for per-indicator attribution. Given the large sibling list, a brief note about when to prefer this over a broader market tool would be helpful.
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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