identi_card_image1Verify the authenticity of a Korean resident registration card from an image or PDF file. 주민등록증 이미지 또는 PDF 파일을 업로드하면 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 already declare readOnlyHint=true, so the read-only nature is known. The description adds valuable context about the cost per call (60 points) and the requirement for a legal processing basis, which are not in the annotations. However, it does not disclose any potential side effects, privacy implications, or what happens if verification fails, leaving some gaps.
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 compact, using two sentences and a short bilingual text. It is front-loaded with the main purpose and quickly covers constraints. There is no unnecessary verbosity, though the bilingual repetition could be trimmed.
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 has no output schema, and the description does not specify what the response looks like (e.g., a boolean, status, or error details). It also fails to differentiate itself from the many sibling tools, which is important given the large set of similar ID verification tools. The legal basis and cost notes help, but the absence of output behavior and sibling differentiation makes it incomplete.
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 schema fully documents image_url with allowed formats and size limit (100% coverage). The description reinforces that only one file is accepted and no text input is needed, adding mild value. Since the schema already does the heavy lifting, a baseline 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 verifies the authenticity of a Korean resident registration card from an image or PDF. The verb and resource are specific. However, it does not differentiate itself from many similar siblings like identi_card_image2..5, so it doesn't reach a 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 by stating that only a single file is needed and no text input is required. It also mentions the legal basis requirement. However, it provides no explicit guidance on when to use this tool versus alternatives like the other identi_card_image variants or identity_document_id_card.
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.