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Health NZ public waiting lists

public_waitlist
Read-onlyIdempotent

New Zealand only. Public-system waiting lists from Health NZ by district and specialty (latest month and the same month a year earlier): people waiting for a first specialist assessment (FSA) and for planned treatment (surgery), and the share waiting over 120 days. Use it when the person is weighing public against private, or which district is faster. Give specialty and/or district. Free.

Input Schema

NameRequiredDescriptionDefault
districtNoHealth NZ district, e.g. 'Auckland', 'Canterbury', 'Capital and Coast'. Part of a name also matches (Canterbury includes South Canterbury); a city or region is read as its district (Wellington → Capital and Coast, Dunedin → Southern), shown in district_read_as.
specialtyNoe.g. 'Orthopaedic', 'ENT', 'General Surgery', 'eye'. An exact name is matched first, then names containing each word, then the same without words like 'surgery' and with common plain words mapped (eye → Ophthalmology, heart surgery → Cardiothoracic, cardiologist → Cardiology, internal medicine → General Medicine), then part of a name; both of Health NZ's names for the same specialty are returned (e.g. Orthopaedics and Orthopaedic Surgery).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
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 non-obvious context beyond that: geographic restriction to NZ, that the data spans the latest month and the same month a year earlier, and that access is free.

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 the most important constraint (New Zealand only) and a parenthetical that scopes the time range without a separate sentence. It is dense but every clause carries information; no 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?

With no output schema, the description correctly takes on the burden of describing returns: both waiting-list types, the 120-day share, and the two comparison months. Combined with the rich schema descriptions for district/specialty matching, an agent has what it needs; only response formatting/pagination is unstated.

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?

With 100% schema coverage the baseline is 3, but the description adds a meaningful usage note for a zero-required-parameter tool: "Give specialty and/or district" clarifies that either or both may be supplied and that at least one is expected in practice, which the schema alone does not state.

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 verb+resource (public waiting lists from Health NZ) plus the exact metrics returned (FSA, planned treatment, share waiting over 120 days) and a scope constraint (New Zealand only). This clearly separates it from siblings like search_doctors and get_doctor, which cover a different domain.

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?

"Use it when the person is weighing public against private, or which district is faster" gives a concrete decision context, and "Give specialty and/or district" tells the agent how to invoke it. It stops short of naming alternatives to prefer in adjacent cases, but the when-to-use is unambiguous.

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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