v1_countryCountry metadata: Name/ISO code → currency, capital, calling code, languages, flag. Source: ISO 3166 (edge dataset). $0.005 per call · GET /v1/country
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Country name or ISO alpha-2/alpha-3/numeric. Example: 'Japan'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds meaningful context beyond annotations by citing the ISO 3166 source, the 'edge dataset' nature, the $0.005 per-call cost, and the GET /v1/country endpoint. No contradictions, and the description reinforces an expected deterministic read-only 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 core purpose is delivered in a single front-loaded sentence, followed by three compact metadata tokens: source, cost, and endpoint. Every element contributes information and no words are wasted. The structure is easy to parse quickly for an agent.
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 one-parameter read-only lookup with thorough annotations, the description is complete. It states the input format, enumerates the returned fields, identifies the data source, and includes the endpoint and pricing. Although no output schema is present, the listed return fields mitigate that gap and give an agent enough information to invoke the tool correctly.
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 coverage is 100% and the schema already describes q as 'Country name or ISO alpha-2/alpha-3/numeric' with an example. The description's 'Name/ISO code' adds no new semantic detail beyond what the schema provides. Score remains at the baseline 3 because the schema carries the full parameter documentation burden.
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 clearly states the resource (country metadata) and the exact mapping from input to output: 'Name/ISO code → currency, capital, calling code, languages, flag.' This differentiates it from sibling tools like v1_geocode or v1_timezone by specifying the precise domain and what the lookup returns. The verb is implied but unambiguous for a GET endpoint.
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 description implies the tool should be used when country metadata is needed, but it does not explicitly state when to prefer it over alternatives or provide any exclusions. Sibling tools are not mentioned, so an agent must infer suitability from the country-specific focus. This meets the standard of implied usage only.
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.