도메인으로 IP 조회
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]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | 검색할 도메인 (예: apick.app) |
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, but the description adds valuable context: 'currently registered' aligns with openWorldHint (live data), non-domain input returns an error, and a per-call point cost is disclosed. These behavioral traits go 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 compact and front-loaded with the primary purpose, followed by error behavior and cost. It is bilingual, creating slight redundancy, but every element earns its place without unnecessary verbosity.
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 one-parameter tool with no output schema, the description covers the purpose, expected input format, error handling, and cost. It clearly communicates the return type (list of IP addresses), making it complete for effective selection and 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?
The input schema already describes the 'domain' parameter with an example (apick.app), so baseline is 3. The description adds meaning by clarifying that non-domain values will cause an error, which is a validation rule not present in the schema. This extra context raises the score above baseline.
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 tool's function: 'Resolve a domain name to its currently registered IP addresses (DNS lookup).' It specifies the verb and resource, and the input validation note distinguishes it from sibling tools like reverse_ip (IP-to-domain resolution).
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 use for domain-to-IP resolution but does not explicitly mention when to use it over alternatives such as reverse_ip or whois. The note about non-domain input returning an error provides some usage context, but no explicit when-not-to-use guidance is given.
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.
Each tool targets a distinct action or resource: YouTube has crawl and download; Google has three separate search modes; URL tools cover HTML fetching, screenshots, and similarity; and network tools are all unique lookups. No two tools overlap in purpose, making selection unambiguous.
The naming is generally readable but mixes conventions: some use verb_noun (crawl_youtube, reverse_ip), others use noun_noun with brand prefixes (google_search, url_screenshot), and a few are single conventional words (location, whois, nslookup). While not chaotic, there is no uniform verb_noun pattern across the set.
With 13 tools, the server is well-scoped for a web research/investigation toolkit. Each tool covers a distinct aspect of web data collection and DNS/IP analysis, and none feel redundant or unnecessary.
The toolkit provides comprehensive coverage for web research: searching (web, image, reverse image), YouTube data collection, URL content analysis, and a full suite of DNS/IP/WHOIS tools. There are no obvious dead ends or missing operations for its intended purpose.