name_rrn_authVerify that a Korean name and resident registration number (RRN) match a real registered person. 성명과 주민등록번호의 일치 여부(실명 존재 여부)를 확인합니다. name, rrn1(앞 6자리), rrn2(뒤 7자리)를 모두 입력해야 합니다. 정보주체의 동의 등 적법한 처리 근거를 확보한 경우에만 사용하십시오. [호출당 50포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | 한글 성명 | |
| rrn1 | Yes | 주민등록번호 앞 6자리 숫자 | |
| rrn2 | Yes | 주민등록번호 뒤 7자리 숫자 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, but the description adds substantial behavioral context beyond that: the requirement for a legal processing basis, the mandatory presence of all three fields, and a per-call cost of 50 points. It does not describe failure/error behavior, but for a simple read-only verification this is acceptable.
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 short and front-loaded with the core purpose in English, followed by Korean equivalent and a few usage notes. The bilingual repetition makes it slightly longer than necessary, but every sentence conveys useful information (inputs, legal basis, cost) without excessive verbosity.
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 read-only verification tool with strong annotations and full schema coverage, the description is complete: it specifies the purpose, all required inputs, the legal precondition, and the cost. The Korean phrase '일치 여부' explicitly implies a boolean match result, setting adequate expectations even without an output schema.
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 describes all three parameters (name, rrn1, rrn2) with Korean explanations, and description coverage is 100%. The tool description only re-states the parameter names and their positional meaning, adding no new semantic detail beyond the schema, so the baseline score 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?
Clearly states the tool verifies whether a Korean name and RRN belong to a real registered person, using the specific verb 'Verify' and naming the resource ('name and resident registration number'). The bilingual description reinforces the purpose and distinguishes it from sibling document-image verification tools by focusing on raw name/RRN data.
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?
Provides a clear usage context: it requires all three inputs and mandates a legal basis (consent) before calling, which is important for privacy-sensitive identity verification. It does not explicitly name alternative sibling tools, but the unique required parameters and the explicit legal condition make the intended use case well understood.
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.