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Microburbs Australian Property Data

by au.com.microburbs
OverviewDiscussionsAdmin

Suburb · Electric vehicle charging

suburbs_transport_ev_chargers
Read-onlyIdempotent

Public EV charging sites per suburb, DC fast-charger counts, and the distance to the nearest fast charger, Australia-wide.

Coverage: Australia-wide, every suburb. DC fast sites are well covered; slower AC and unrated sites are partially mapped. Current to 2026-10-27. Full description, field list and method: /v1/datasets/ev-chargers.

Price: 3¢ 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_transport_ev_chargers"
  }
}

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: charging_sites_total, dc_fast_sites, dc_ultra_fast_sites, other_charging_sites, dc_fast_sites_within_10km, nearest_dc_fast_charger_m. 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 non-structured behavior: a data-quality caveat about partial AC/unrated site coverage, a currency date (2026-10-27), a per-call cost of 3¢, and a pointer to the full method and field list. It does not describe return shape or how the from/to period behaves in the response.

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 definition is three tight blocks: what the data is, coverage/currency/method pointer, and price. The most decision-relevant content (what it returns and the geographic scope) is front-loaded, and no sentence is filler.

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 data-retrieval tool with full schema coverage and no output schema, the description covers scope, currency, known data gaps, cost and a documentation escape hatch for the field list. The remaining gap is that presence of from/to implies a time series but the description never says observations are returned over time rather than a single snapshot.

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% and every parameter carries its own description, formats and field enumeration, so the schema does the heavy lifting and baseline 3 applies. The description's phrase 'per suburb' reinforces that suburb_name drives the query and 'Current to 2026-10-27' loosely bounds the `to` parameter, but it adds no syntax or format detail 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 names a specific resource and metric set: public EV charging sites per suburb, DC fast-charger counts, and distance to the nearest fast charger, plus an explicit Australia-wide scope. The topic is unmistakably distinct from the transport siblings (public transport, road crashes, speed cameras) without needing to name them, but no sibling is referenced or ruled out, so it stops short of full differentiation.

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?

Usage is implied by the resource description (per-suburb EV charging data) and the coverage note usefully warns that DC fast sites are well covered while slower AC and unrated sites are only partially mapped. However, there is no explicit when-to-use/when-not guidance, no statement of prerequisites such as obtaining a canonical suburb name from /v1/suburbs/list before calling, and no routing to alternatives.

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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