v1_dnsDNS lookup: Resolve DNS records via DNS-over-HTTPS. Source: Google / Cloudflare DoH. $0.005 per call · GET /v1/dns
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Hostname. Example: 'example.com'. | |
| type | No | Record type (default A). Example: 'MX'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds meaningful operational context beyond annotations: it identifies the upstream sources (Google/Cloudflare DoH), the HTTP method, and the cost per call, which helps an agent understand external dependencies and side effects.
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 a single front-loaded sentence containing the purpose, source, cost, and HTTP method. Every element earns its place, and there is no redundant filler or repetition of schema details.
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 tool with full schema coverage and strong safety annotations, the description provides enough for an agent to invoke it correctly. It lacks explicit return-value details, but the phrase 'Resolve DNS records' makes the expected output reasonably clear, and the source/cost/endpoint information adds useful context.
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?
The input schema already describes both parameters with examples and defaults, achieving 100% schema description coverage. The description does not add further parameter-level meaning beyond saying that DNS records are resolved, so the baseline score 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 uses a specific verb and resource: 'Resolve DNS records via DNS-over-HTTPS.' It also names the source and endpoint, making the tool's function unmistakable and clearly distinct from every sibling tool, none of which are DNS record lookups.
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 usage for DNS resolution but provides no explicit when-to-use guidance, exclusions, or alternatives. An agent can infer the context from the name and description, but the tool does not help differentiate it from similar-looking network or lookup tools.
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.