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Data To Agents

nz-public-holidays

New Zealand public holidays: national holidays (Waitangi, Matariki, Anzac, etc. with observed-date shifts) plus regional anniversary days. Verified against Employment NZ. Unknown years return an explicit notice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoCalendar year (default: current year)
regionNoNZ region for anniversary day, or ALL (default): Northland, Auckland, Waikato, Bay of Plenty, Gisborne, Hawke’s Bay, Taranaki, Manawatu-Whanganui, Wellington, Tasman/Nelson, Marlborough, West Coast, Canterbury, Otago, Southland, Chatham Islands

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral context. It discloses that observed-date shifts are included, that regional anniversary days are covered, that data is verified against Employment NZ, and that unknown years return an explicit notice. It does not mention response format, date ranges, or any limits, so transparency is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

Two well-structured sentences deliver the core purpose, scope, data source, and an important edge-case behavior. Every clause adds value and the most identifying information is front-loaded.

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 simple lookup tool with two optional parameters and no output schema, the description covers the essential context: what holidays are included, regional handling, accuracy, and unknown-year behavior. It omits an explicit description of the return shape, but that is a minor gap given the tool's low complexity.

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 the parameters year and region are already documented in structured form. The description adds context about observed-date shifts and regional anniversary days, which helps interpret the region parameter, but it does not add detailed semantics beyond the schema. Baseline 3 is appropriate.

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?

The description clearly identifies the resource (New Zealand public holidays) with specific examples (Waitangi, Matariki, Anzac) and distinguishes national holidays from regional anniversary days. It differentiates from sibling tools such as au-public-holidays and nz-school-terms by focusing on NZ public holidays specifically.

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?

The description implies when to use the tool: whenever New Zealand public holidays are needed for a year and region. It does not explicitly state when not to use it or name alternatives like nz-school-terms or au-public-holidays, leaving the boundary to inference rather than explicit guidance.

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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TDQS

A3.6/5.0
Disambiguation5/5

Every tool maps to a clearly distinct dataset or lookup, with country prefixes and topic names separating overlapping domains. Even similar tools like au-abs-building-activity and au-abs-building-approvals are unambiguously differentiated by their descriptions.

Naming Consistency4/5

The data tools follow a consistent country/topic hyphenated pattern (au-*, nz-*), making resource selection predictable. The meta tools (get_catalog, list_services, health) break this pattern with imperative/underscore names, but this is a minor and understandable deviation.

Tool Count3/5

At 26 tools, the set is on the heavy side and slightly exceeds the typical comfortable range. However, each tool represents a genuinely distinct data service, and the clear grouping by country and topic keeps the surface navigable.

Completeness4/5

The server covers a broad range of common agent data needs for Australia and New Zealand: demographics, income, building, labour, weather, time, holidays, school terms, and place resolution. Minor gaps exist, such as no NZ building data or broader international coverage, but core workflows are well supported.

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