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Microburbs Australian Property Data

by au.com.microburbs
OverviewDiscussionsAdmin

Suburb · Aircraft overflights

suburbs_environment_flight_paths
Read-onlyIdempotent

How often aircraft pass low over a suburb: recorded passes per week, the busiest hour of the day and how well we could hear the place. From nine days of our own aircraft recording, September 2026. Modelled estimates.

Coverage: About 7,100 suburbs and localities in every state and territory where aircraft were recorded; 9 days, 8 to 24 September 2026. Current to 2026-09-24. Full description, field list and method: /v1/datasets/flight-paths.

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_environment_flight_paths"
  }
}

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: passes_per_week, busiest_hour, busiest_hour_passes_per_day, coverage_class. 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

A3.7/5.0
Behavior4/5

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

Annotations already declare this a safe, read-only, idempotent, non-destructive lookup, so the description's job is to add context — and it does: modelled estimates caveat, source (own recording), exact coverage window, currency date, and a 5¢ per-call price. The remaining gap is return shape and any per-call limits, which are not addressed.

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?

Well front-loaded: the first sentence says what you get before the coverage and pricing detail. The coverage/price sentences are justified for a paid, modelled dataset. Minor waste in duplicated temporal detail ('nine days of our own aircraft recording' repeated in 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 results and does so at a metric level plus a modelled-estimates warning and a pointer to the dataset endpoint for the full field list and method. Only the response format/pagination behavior remains unstated.

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%, so from/to/fields/suburb_name are already fully documented in the schema, and the description adds little syntax-level meaning. It does implicitly enumerate the metric family that the fields parameter can select (passes_per_week, busiest_hour, coverage_class via 'how well we could hear'), but it never explicitly maps that to the fields parameter.

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 concrete resource and its metrics: recorded low overflights per suburb, passes per week, busiest hour, and an audibility/coverage class. That is far more specific than a title restatement. It stops short of explicitly distinguishing itself from the nearby aircraft-noise siblings, since 'how well we could hear the place' overlaps conceptually with a noise dataset.

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: you call it when you want overflight frequency for a named suburb, and the coverage paragraph tells you the data is nine days in September 2026. There is no explicit when-to-use versus the aircraft-noise tools, no when-not guidance, and no note that the from/to filters are of limited value against a nine-day window.

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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