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Microburbs Australian Property Data

by au.com.microburbs
OverviewDiscussionsAdmin

Suburb · Health services nearby

suburbs_amenities_health_services
Read-onlyIdempotent

GPs and medical centres, pharmacies, dentists, hospitals and vets: counts in the suburb, rates per 1,000 residents and distance from the suburb centre to the nearest of each.

Coverage: All Australian suburbs and localities. Current to 2026-10-01. Full description, field list and method: /v1/datasets/health-services.

Price: 5¢ per call.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "suburb_name": "<suburb_name>"
    },
    "name": "suburbs_amenities_health_services"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLast period to include, same formats as `from`.
fromNoFirst period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
fieldsNoComma-separated subset of: count_gps, per_1000_gps, nearest_km_gps, count_pharmacies, per_1000_pharmacies, nearest_km_pharmacies, count_dentists, per_1000_dentists, nearest_km_dentists, count_hospitals, per_1000_hospitals, nearest_km_hospitals, count_vets, per_1000_vets, nearest_km_vets, count_total, per_1000_total, per_km2_total. Omit for all.
suburb_nameYesSuburb name exactly as /v1/suburbs/list returns it, e.g. `Bondi` or `St Kilda (Vic.)`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context that annotations cannot convey: geographic coverage, the currency date (2026-10-01) and a per-call price of 5¢, which matters for an agent deciding whether to call.

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 payload is front-loaded in the first sentence, followed by short coverage/currency and pricing lines, with a pointer to the full dataset documentation. Every sentence carries information an agent needs; nothing is redundant.

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

Completeness4/5

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

For a read-only metrics tool with no output schema, the description adequately explains what comes back (counts, per-1,000 rates, nearest distances), the universe covered, currency and cost. The one gap is that the from/to parameters imply a historical range while the text only mentions a single currency date, leaving the time-series behavior slightly ambiguous.

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 description coverage is 100%, so the baseline is 3. The description does add one useful clarification beyond the schema – that nearest_km_* is measured from the suburb centre to the nearest facility – which the field names alone do not make explicit, but it says nothing about the from/to period semantics.

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 names the exact resource (GPs and medical centres, pharmacies, dentists, hospitals, vets) and the three measures returned (suburb counts, rates per 1,000 residents, distance to nearest). It implicitly distinguishes itself from the area-stats and health-conditions siblings by covering service supply, but it never names an alternative, so the differentiation is inferential rather than stated.

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?

Coverage scope ('All Australian suburbs and localities') and data currency are given, which helps an agent decide the tool is appropriate for Australian suburb-level queries. There is, however, no explicit when-to-use/when-not-to-use statement and no routing to siblings such as suburbs_amenities_services or suburbs_area_stats_health_conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Microburbs Australian Property Data toolsInspect
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