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Look up an Australian postcode or suburb

lookup_au_postcode

Resolve an Australian postcode to its suburbs and state, or a suburb name to its postcode. Works in both directions. Use it to validate an address before quoting, or when a suburb name is ambiguous because the same name exists in several states.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesAn Australian postcode such as 3000, or a suburb name such as Carlton.
stateNoOptional state filter: NSW, VIC, QLD, SA, WA, TAS, NT or ACT. Supply it when a suburb name exists in more than one state.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose the key behavioral trait: the tool is bidirectional and can return plural suburbs plus state. It does not say what happens on an unknown postcode/suburb or how multiple matches are ordered, which is a modest gap for a low-risk read lookup.

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?

Three short sentences, front-loaded with the core capability and then the use cases; nothing is padded. 'Works in both directions' is mildly redundant with the bidirectional phrasing in the first sentence.

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?

No output schema exists, so the description must cover return values; it partially does by naming suburbs and state. It leaves open error/empty-match behavior and ordering of multiple matches, but for a simple two-parameter lookup this is close to sufficient.

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 both parameters are already documented in the schema, including the state code list and examples. The description adds only the rationale for supplying state (ambiguity across states), which the schema also states, so baseline 3 applies.

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 precise verb (Resolve) and resource (Australian postcode/suburb) and explicitly covers both directions of the mapping, so an agent knows exactly what it gets back. It is clearly distinct from the sibling quoting and weight-calculation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete when-to-use contexts: validating an address before quoting, and disambiguating a suburb name that exists in several states. No explicit when-not or named alternative tool is given, but the usage conditions are specific and actionable.

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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