Microburbs Australian Property Data

LGA · Occupation

lga_area_stats_occupation

Read-onlyIdempotent

What working residents do: managers, professionals, trades, community and personal service, clerical, sales, machinery operators and labourers, as counts and shares of employed residents for every suburb and council area.

Coverage: About 8,800 suburbs and localities and 540 council areas across Australia, in all states and territories (areas with too few people or homes for reliable figures are left out); one snapshot at 10 August 2021. Current to 2021-08-10. Full description, field list and method: /v1/datasets/occupation.

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": {
      "lga_name": "<lga_name>"
    },
    "name": "lga_area_stats_occupation"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last period to include, same formats as `from`.
`from`	No	First period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
`fields`	No	Comma-separated subset of: total_employed, managers_count, managers_pct, professionals_count, professionals_pct, technicians_and_trades_count, technicians_and_trades_pct, community_and_personal_service_count, community_and_personal_service_pct, clerical_and_administrative_count, clerical_and_administrative_pct, sales_count, sales_pct, machinery_operators_and_drivers_count, machinery_operators_and_drivers_pct, labourers_count, labourers_pct, occupation_not_stated_count, occupation_not_stated_pct. Omit for all.
`lga_name`	Yes	Council (LGA) name exactly as /v1/lga/list returns it, e.g. `Lake Macquarie`.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive safety, but the description adds genuinely useful behavioral context: a fixed 10 August 2021 snapshot, coverage of ~8,800 suburbs and 540 councils, exclusion of areas with too few people for reliable figures, and a 5¢ per-call charge. Pricing and data-quality exclusions are not visible anywhere in structured fields, making this a real contribution beyond the annotations.

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?

Purpose comes first, followed by a clearly separated coverage block, snapshot date and price — front-loaded and scannable. The opening sentence is long and enumerates categories at more length than needed, but no sentence is truly wasted.

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 filtered-statistics endpoint with a fully described schema (no output schema needed), the definition supplies the essentials an agent cannot get elsewhere: cost per call, temporal coverage, geographic coverage and a docs pointer. The only shortfall is not telling the agent to resolve lga_name via /v1/lga/list, despite requiring an exact match.

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 coverage is 100% — from/to formats, the fields enumeration and the lga_name format rule are all documented in the schema. The description's list of occupation categories loosely mirrors the `fields` options but adds no format, default, or interaction guidance beyond that, so baseline 3 applies.

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?

Names the specific measures (counts and shares of employed residents by occupation category) and the reporting geography, so an agent knows exactly what data comes back. The phrase 'for every suburb and council area' blurs the LGA-only scope implied by the name and by the sibling suburbs_area_stats_occupation, which is the one real ambiguity.

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 rather than stated: an agent can infer it should call this for occupation breakdowns of council areas. There is no explicit when-to-use / when-not-to-use, no contrast with suburbs_area_stats_occupation or labour_force, and no statement of prerequisites such as fetching lga_name from /v1/lga/list first.

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 tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?