v1_airports_nearestNearest airports: Coordinates → nearest airports (IATA/ICAO) by distance. Source: OurAirports (edge dataset). $0.008 per call · GET /v1/airports/nearest
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude. Example: '40.71'. | |
| lon | Yes | Longitude. Example: '-74.0'. | |
| limit | No | Max results 1-25. Example: '5'. | |
| radius | No | Search radius km (default 500). Example: '300'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful context beyond annotations: the data source (OurAirports), per-call pricing, HTTP method, and the fact that results are ordered/determined by distance. No contradictions with annotations.
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 compact and front-loaded with the primary purpose. Every clause earns its place: purpose, data source, cost, and endpoint. There is no redundant filler.
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?
The description conveys the essential output type (nearest airports with IATA/ICAO identifiers by distance), and the schema fully documents required and optional parameters. Annotations cover the safety profile. It does not explicitly describe pagination or detailed result shape, but for a simple nearest-airport lookup the definition is sufficiently complete.
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 all four parameters documented and examples provided, including the radius default. The description adds no parameter-level meaning beyond 'Coordinates' and 'by distance', so the baseline of 3 applies.
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 states a specific transformation: Coordinates → nearest airports (IATA/ICAO) by distance. It clearly identifies the resource and result, and is distinct from sibling geospatial tools like v1_geocode or v1_reverse_geocode. It does not merely restate the tool name.
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 phrase 'Coordinates → nearest airports' makes the intended use case clear: when an agent needs airports near a latitude/longitude point. It does not explicitly mention alternatives or when-not-to-use, but no sibling tool covers airport proximity, so ambiguity is low.
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.