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Microburbs Australian Property Data

by au.com.microburbs
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Postcode · Rooftop solar and home batteries

postcodes_environment_solar_installations
Read-onlyIdempotent

Small-scale rooftop solar systems installed and their capacity in kW per postcode for every financial year from 2011-12 to 2025-26, the running total, and home batteries installed in 2025-26.

Coverage: About 2,630 postcodes in every state and territory; financial years 2011-12 to 2025-26; batteries 2025-26 only. Current to 2026-06-30. Full description, field list and method: /v1/datasets/solar-installations.

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": {
      "postcode": "<postcode>"
    },
    "name": "postcodes_environment_solar_installations"
  }
}

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: solar_installations, solar_capacity_kw, solar_installed_total, solar_capacity_total_kw, battery_installations, battery_capacity_kwh. Omit for all.
postcodeYesFour-digit postcode, e.g. `2026`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the description is not required to restate safety. It does add genuinely useful behavioral context the annotations cannot convey: geographic coverage (~2,630 postcodes across all states/territories), temporal coverage limits (batteries only for 2025-26), a currency date (2026-06-30), 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with what the tool returns, then coverage, then cost — a sensible order and mostly dense. Minor waste: the financial-year range and the 'installed/capacity in kW' phrasing are effectively stated twice across the first paragraph and the coverage line.

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?

With no output schema, the description carries the burden of describing returns, and it does list the measures returned (installations, capacity kW, running totals, batteries) plus coverage and currency, with the full field list delegated to the schema and the referenced dataset page. An agent could call this correctly, though it doesn't state units or row shape (one row per postcode-period).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 adds real meaning beyond the schema by fixing the period semantics as financial-year data spanning 2011-12 to 2025-26, which bounds the otherwise open-ended `from`/`to` parameters (the schema illustrates quarterly/daily formats that do not exist in this dataset) and tells the agent the `fields` metrics available.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (small-scale rooftop solar installations, capacity in kW, running totals, home batteries) with a specific granularity (per postcode, per financial year). The metric names and the geography/period scope make it clearly distinguishable from sibling postcode datasets such as demographics or economy tables.

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 coverage statement rather than stated: an agent can infer this is the tool for postcode-level solar/battery uptake, and the pointer to `/v1/datasets/solar-installations` offers further documentation. However there is no explicit when-to-use/when-not guidance and no named alternative for related questions (e.g. area-level rather than postcode-level solar data).

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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