IP geolocation
v1_ip_geolocationIP geolocation: IP address → location, ASN, ISP. Source: ipwho.is / ip-api. $0.005 per call · GET /v1/ip-geolocation
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IPv4 or IPv6 address. Example: '8.8.8.8'. |
v1_ip_geolocationIP geolocation: IP address → location, ASN, ISP. Source: ipwho.is / ip-api. $0.005 per call · GET /v1/ip-geolocation
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IPv4 or IPv6 address. Example: '8.8.8.8'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only, idempotent, non-destructive, and open-world, so the description's main responsibility is adding beyond those hints. It does add useful context: the upstream source (ipwho.is / ip-api), pricing, and HTTP route. However, it does not disclose potential failure modes, data freshness, or whether results may vary between the two sources.
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 extremely compact and front-loaded, leading with the core transformation and then adding only high-value details: source, cost, and endpoint. Every phrase earns its place, and there is no redundant prose. It is a model of concise tool documentation.
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 single-parameter, read-only tool with rich annotations, the description covers the essential facts: what it does, the output categories, the upstream service, the cost, and the route. There is no output schema, but the description names the expected result fields well enough. It could add a note about possible error cases or the difference between the two data sources, but nothing critical is missing for basic invocation.
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%, and the schema already explains the ip parameter format with an example. The description adds that the IP maps to location, ASN, and ISP, which indirectly clarifies what the parameter produces but does not explain restrictions such as public vs private addresses. Baseline 3 is appropriate because the description does not need to compensate for missing schema fields.
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 (IP address) and the result (location, ASN, ISP), which distinguishes it from sibling geocoding tools that operate on street addresses or places. The arrow notation is a concise substitute for a verb, making the operation obvious. It could be slightly stronger with an explicit 'look up' or 'resolve' verb, but the intent is unambiguous.
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?
There is no guidance about when to prefer this tool over alternatives such as v1_geocode, v1_reverse_geocode, v1_country, or v1_timezone. The description mentions the source and cost but does not state the intended use case or exclude scenarios where another sibling would be more appropriate. An agent must infer usage solely from the tool name and the IP-specific input.
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.