reverse_ipReverse IP lookup: list domains that have been hosted on a given IP address. 특정 IP에 등록된 도메인 이력 정보를 조회합니다. IP 주소 형식만 허용됩니다. [호출당 100포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | 검색할 IP 주소 (예: 121.140.146.38) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and open-world behavior, so the description adds value by disclosing a per-call cost ('[호출당 100포인트]') and the IP format restriction. These details go beyond the annotations without contradicting them.
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 but contains redundant bilingual text: 'list domains that have been hosted on a given IP address' is repeated in Korean. The cost note is useful, but the duplication could be trimmed for better conciseness.
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 clear annotations, the description covers the basic purpose, input constraint, and cost. However, it does not describe the output format or any examples of returned domains, which would be helpful given the lack of an output schema.
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% for the single 'ip' parameter, which already explains that it is an IP address with an example. The description adds little beyond stating that only IP address format is allowed, making the baseline 3 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 a specific verb and resource: 'Reverse IP lookup: list domains that have been hosted on a given IP address.' This unambiguously distinguishes the tool from siblings like nslookup or whois by focusing on hosted domain history for a given 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 implies when to use this tool (when you need domains hosted on an IP) but does not explicitly mention alternatives or when not to use it. The constraint 'IP 주소 형식만 허용됩니다' (only IP address format allowed) provides a usage restriction but no comparison with sibling 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.
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.