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. The description adds meaningful behavioral context: the operation requires a legal basis (consent), and there is a per-call cost (60 points). It also clarifies the input is a single file with no text input. No contradiction with annotations; it goes beyond the structured data.
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 and front-loaded: it states the core purpose in the first clause, then provides the practical requirement (file only), the legal condition, and the cost. Every sentence adds value with no redundancy. Well structured for quick parsing.
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 simple one-parameter tool with no output schema and read-only annotations, the description covers the key usage aspects: what it does, the input format, the legal prerequisite, and the cost. It does not specify the return format (e.g., true/false vs. detailed report), but that is not strictly necessary given the lack of an output schema and the simplicity of the task.
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%, so the single parameter (image_url) is fully documented in the schema. The description adds the fact that only a file is needed ('no text input'), but that is largely implied by having just one parameter. No extra syntax or format details beyond the schema are provided, so 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 verb ('verify'), a clear resource ('Korean driver license authenticity'), and the input type ('image or PDF file'). This clearly distinguishes it from sibling tools like identi_card1 (likely text-based) and other identity document verifiers. The purpose is immediately clear and unambiguous.
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 via file upload without text input, which helps when the agent has an image/PDF rather than textual data. However, it does not explicitly name alternatives or state when not to use this tool versus the many sibling tools. The legal-consent requirement is a usage context, but no comparison or exclusion is given.
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.
Each tool has a distinct purpose: masking (hide_rrn), text-based verification (identi_cardN), image-based verification (identi_card_imageN), extraction with masking (identity_document_*), and name/RRN matching (name_rrn_auth). Within each group, the document type is clearly specified, so there is no ambiguity between tools.
Naming follows clear patterns: identi_card* for verification (with _image for image-based), identity_document_* for extraction, and descriptive names like hide_rrn and name_rrn_auth. While the prefixes differ across functional groups, each group is internally consistent and the names are readable and predictable.
16 tools is on the higher end but appropriate for the server's scope, covering five document types with two verification modes (text and image), four extraction/masking tools, a generic masking tool, and a name/RRN auth check. Each tool fills a needed role, though the number is slightly elevated due to the text/image split.
The server covers the core operations for identity document verification and extraction across all major Korean ID types. A minor gap is the lack of an extraction/masking tool for the resident registration certificate (identi_card4), but this is not a critical omission given the existing verification and masking capabilities.