identi_card_image4Verify the authenticity of a Korean resident registration certificate from an image or PDF file. 주민등록등본 이미지 또는 PDF 파일을 업로드하면 문서확인번호 등 기재 정보를 자동 인식해 진위 여부를 확인합니다. 텍스트 입력 없이 파일 하나만 전달하면 됩니다. 정보주체의 동의 등 적법한 처리 근거를 확보한 경우에만 사용하십시오. [호출당 60포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| image_url | Yes | 다운로드 가능한 https URL (허용 형식: image/jpeg, image/png, application/pdf) (최대 50MB) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true and openWorldHint=true, covering safety and external data access. The description adds the per-call cost of 60 points and the legal compliance condition, which are not in annotations. It does not contradict 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 bilingual and repeats the same purpose in English and Korean, which adds redundancy. It is not excessively long, but could be more compact by dropping the duplicate sentence. The key points are front-loaded.
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 single-parameter tool with no output schema, the description explains the input and the verification action, and includes cost and legal guidance. However, it does not describe the return value (e.g., boolean, details of verification) or potential error conditions, which leaves some ambiguity for the agent.
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 coverage is 100% and the parameter description already specifies URL type, allowed formats (jpeg/png/pdf), and 50MB limit. The description adds minimal semantic value beyond restating that a file is passed, which is already implied by the schema.
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 action (verify authenticity) and resource (Korean resident registration certificate) and specifies input as image or PDF file. It distinguishes itself from text-based identi_card tools by explicitly requiring a file, but does not differentiate among the image-based siblings (identi_card_image1-3,5).
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 usage when a file is available ('text input 없이 파일 하나만 전달하면 됩니다') and includes a legal prerequisite (consent). However, it does not explicitly compare with other image verification tools or list exclusions, leaving the agent to infer which identi_card_image variant to choose.
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.