get_pcccRetrieve a Korean Personal Customs Clearance Code (PCCC) using the auth key and SMS verification code. req_pccc Tool 호출로 받은 auth_key와 문자(SMS)로 수신한 인증번호 6자리를 입력해 개인통관고유부호를 조회합니다. [호출당 30포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| answer | Yes | 문자(SMS)로 발송된 인증번호 6자리 | |
| auth_key | Yes | req_pccc(개인통관고유부호 인증 요청) 응답의 인증 키 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral details beyond annotations by disclosing the cost ('[호출당 30포인트]') and the dependency on an SMS verification code from a prior step. This complements the annotations (readOnlyHint=false, openWorldHint=true) 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 concise, with an English lead sentence followed by Korean details and a cost note. It is slightly redundant due to bilingual repetition, but remains compact and front-loaded with the core purpose.
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 tool is simple with two parameters and no output schema. The description covers the purpose, input prerequisites, and the retrieval flow, implying the result is the PCCC. It is complete enough for an agent to invoke correctly, though it does not describe the return format or error handling.
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 100% coverage with clear descriptions for both parameters (auth_key from req_pccc response, answer as the 6-digit SMS code). The description largely restates these semantics without adding new parameter-specific meaning.
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: 'Retrieve a Korean Personal Customs Clearance Code (PCCC)' with a specific verb and resource. It also references the req_pccc tool as the source of auth_key, distinguishing this retrieval step from the authentication request step.
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?
It provides explicit prerequisite context: the auth_key is obtained from calling the req_pccc Tool, and the answer is the 6-digit SMS verification code. This indicates when to use the tool, though it does not explicitly state alternatives or exclusions (e.g., check_pccc).
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.