identi_card_image2Verify the authenticity of a Korean driver license from an image or PDF file. 운전면허증 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 and openWorldHint=true, and the description does not contradict this. The description adds behavioral context by disclosing the per-call cost (60 points) and the legal requirement for processing personal data. These are valuable traits not in the annotations, though details about data handling or return behavior are not provided.
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 the core purpose front-loaded in the English/Korean first sentence. It includes the cost and legal note without redundancy. There is minimal waste, though the Korean repetition of the same idea adds a bit of duplication, preventing a top score.
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 does not explain what the response looks like (e.g., success/failure indicator, confidence score, or extracted fields). Since the agent cannot infer the return format from annotations or an output schema, this is a notable gap. The purpose is clear, but the missing behavioral outcome reduces completeness.
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 description for image_url already covers format, URL requirements, and size limit (100% coverage). The tool description adds no additional meaning beyond restating that an image or PDF file is accepted. With full schema coverage, baseline 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 states a specific action (verify authenticity) and resource (Korean driver license) with input type (image/PDF). It is clear what the tool does. However, it does not differentiate from many similar sibling tools like identi_card_image1, identi_card_image3, etc., so it does not fully distinguish itself from alternatives.
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 gives usage context: file-only input (no text), legal requirement of consent, and cost per call. It does not say when to use this tool instead of the many sibling identity/OCR tools, nor does it mention exclusions or alternative tools. The guidance is helpful but lacks comparative selection criteria.
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.