transfer_1wonSend a 1 KRW verification deposit to a Korean bank account and return the 4-character verification code printed on the transaction. 대한민국 은행 계좌로 1원을 입금해 적요에 표시되는 인증코드를 반환합니다. 계좌 실소유 확인(1원 인증) 절차에 사용합니다. bank_code 또는 bank_name 중 하나는 입력해야 합니다. [호출당 60포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| bank_code | No | 은행 코드 (bank_code Tool로 조회 가능, 예: 004) | |
| bank_name | No | 은행명 (예: 국민). bank_code 대신 입력 가능 | |
| account_num | Yes | 계좌번호 (숫자만, 하이픈 제외) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description adds operational details such as the per-call cost ('[호출당 60포인트]'), the need to supply either bank_code or bank_name, and that the verification code appears on the transaction. These details enhance the agent's understanding of side effects and constraints without contradicting 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 concise and front-loaded, starting with the core action. The bilingual repetition (English and Korean) adds some length but is not excessive, and all key elements—action, return value, usage, requirement, and cost—are efficiently presented.
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?
The description covers the tool's purpose, return value (4-character code), usage context, parameter requirements, and cost. It omits explicit error/failure behavior, but for a simple financial verification tool with no output schema, it provides sufficient context for correct 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 provides thorough descriptions for all three parameters, including examples and formatting rules. The description adds the crucial mutual exclusivity constraint that one of bank_code or bank_name must be provided, which is not captured in the schema itself.
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 specific action: sending a 1 KRW deposit to a Korean bank account and returning the 4-character verification code from the transaction. It also distinguishes the tool by referencing the '계좌 실소유 확인(1원 인증)' procedure, setting it apart from sibling verification tools.
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 clear usage context, indicating it is for account ownership verification via a 1-won deposit. It also includes a practical guideline that either bank_code or bank_name must be provided, helping the agent decide how to invoke it, though it does not explicitly mention alternatives or exclusions.
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.