nslookupResolve a domain name to its currently registered IP addresses (DNS lookup). 도메인에 현재 등록된 IP 주소 목록을 조회합니다. 도메인 형식이 아닌 값은 오류로 응답합니다. [호출당 1포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | 검색할 도메인 (예: apick.app) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is known. The description adds extra behavior: error on non-domain input and the cost of 1 point per call, which is useful context beyond the 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 short and front-loaded with the key action in English. The Korean sentence is a translation and somewhat redundant, but the clean structure with error behavior and cost keeps it efficient.
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 tool with good annotations and no output schema, the description covers purpose, input format constraint, and cost. Return format is not detailed, but for a simple DNS lookup it's reasonably understandable. The sibling list includes related tools like whois and reverse_ip, which helps 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?
Schema coverage is 100% with a helpful description for 'domain' (e.g., apick.app). The tool description adds validation semantics ('non-domain values return an error'), going slightly beyond the schema.
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 action: 'Resolve a domain name to its currently registered IP addresses (DNS lookup)'. This clearly distinguishes it from sibling tools like whois or reverse_ip, and the verb 'resolve' plus resource 'domain name to IP' 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?
The description implies when to use it (DNS lookup of a domain) and explicitly states that non-domain values return an error. It does not explicitly mention alternatives or exclusions, but the simple purpose and error condition provide clear context.
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.
Most tools have clearly distinct purposes; even within families like identi_card1-5 vs identi_card_image1-5, the text-input vs image-input distinction is clear. However, the sheer number of tools and some near-synonyms (e.g., ocr_identi1 vs identi_card_image1) could cause occasional misselection, but descriptions mitigate this.
Naming follows a loose verb-first pattern (check_, crawl_, download_, draw_, etc.) but includes significant deviations: bare nouns (bank_code, location, whois), numbered variants (identi_card1, identi_card_image1), and mixed prefixes (ocr_, identity_, etc.). The inconsistency is noticeable but still readable and predictable within functional clusters.
80 tools is far above the typical 3-15, but the server is a broad API aggregator covering many independent domains (banking, ID verification, media conversion, search, LLM, etc.), so the high count is somewhat justified. Still, the sheer number makes the toolkit feel unwieldy and hard to navigate, placing it at the high end of acceptable.
Within its stated purpose as a general-purpose utility API, the toolset covers a wide array of common task families: identity document verification (text and image), OCR field extraction, media conversion, web/search, domain/IP lookup, and LLM chat. Most operations have both get and act variants (e.g., set/get watermark, parcel_tracking/auto), with few obvious dead ends for typical use cases.