v1_holidaysPublic holidays: Public holidays for a country & year. Source: Nager.Date. $0.005 per call · GET /v1/holidays
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Year (default current). Example: '2026'. | |
| country | Yes | ISO-3166 alpha-2. Example: 'US'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context beyond annotations: source (Nager.Date), cost ($0.005 per call), and the HTTP endpoint, but it does not disclose response format or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, with source, cost, and endpoint appended efficiently. Minor redundancy exists: 'Public holidays' is repeated in the title and the description prefix, wasting a few characters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter, read-only tool with full schema coverage and informative annotations, the description is largely complete: resource, scope, source, cost, and endpoint are all present. The absence of any detail about the returned holiday list shape is a minor gap given no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for year and country, so the schema already carries the parameter meaning. The description simply restates that holidays are for a country and year, adding no new parameter-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the resource as public holidays for a country and year, and the endpoint 'GET /v1/holidays' signals retrieval. It is distinguishable from siblings like v1_business_days by the 'country & year' scope, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied: call this when public holidays for a country and year are needed. However, there is no explicit when-to-use, when-not-to-use, or comparison against sibling tools such as v1_business_days.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct resource or operation—geocoding, weather, DNS, VIN, stock quotes, etc.—with no meaningful overlap in purpose. Even the location- and finance-related tools are clearly separated by their descriptions.
All tools follow the same v1_<resource>[_modifier] snake_case pattern, such as v1_air_quality, v1_reverse_geocode, and v1_validate_email. Although the names are not verb-based, the convention is perfectly consistent across all 31 tools.
31 tools exceeds the 25+ threshold and creates a heavy selection burden for agents, even though the server's stated purpose is broad. Many endpoints are small single-purpose lookups that could be grouped into fewer combined tools without losing clarity.
As a general public-data utility, the set covers a wide range of common lookup categories: location, weather, finance, legal, health, business, internet, and reference data. It has minor gaps like historical financial time series or phone-number validation, but no obvious dead ends since all tools are self-contained read-only lookups.