ip_historyLook up the historical IP address changes of a domain. 도메인에 대한 IP 주소 변경 이력 정보를 조회합니다. 최상위 도메인 기준으로 조회되며 하위 도메인은 추적되지 않습니다. [호출당 100포인트]
| 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 include readOnlyHint and openWorldHint, so the description adds useful context beyond those: the operational scope (top-level domain only, subdomains excluded) and the per-call point cost. This enhances transparency without contradicting 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 brief and front-loaded with the main purpose, followed by scope constraints and cost. It includes a bilingual repetition (English and Korean), which adds a bit of redundancy but each part is meaningful for the intended audience.
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?
This is a simple read-only tool with one parameter, no output schema, and helpful annotations. The description covers the essential information: what it does, scope limitations, and cost. It doesn't detail the return structure, but for such a straightforward lookup, the description 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?
The input schema has 100% coverage for the single 'domain' parameter, including an example. The description does not add additional parameter details beyond what the schema provides, so a baseline score of 3 is appropriate.
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: looking up historical IP address changes for a domain. It includes the specific constraint of top-level domain scope, which distinguishes it from sibling tools like nslookup (current IP lookup) and reverse_ip.
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 provides a clear use case and explicitly states that subdomains are not tracked, which serves as a when-not condition. It does not explicitly name alternative tools, but the context of siblings and the constraints given are adequate for selection.
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.