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APICK Identity

by app.apick

[Text] 운전면허증 진위 확인

identi_card2
Read-only

Verify the authenticity of a Korean driver license using text input. 운전면허증의 기재 정보를 입력해 진위 여부를 확인합니다. birth_y, birth_m, birth_d, name과 면허번호 4구획(licen_no0~licen_no3)은 모두 필수이며, ghost_num(식별번호)과 rrn1, rrn2는 선택 입력입니다. 정보주체의 동의 등 적법한 처리 근거를 확보한 경우에만 사용하십시오. [호출당 40포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes성명
rrn1No주민등록번호 앞 6자리 (선택)
rrn2No주민등록번호 뒤 7자리 (선택)
birth_dYes생년월일 - 일 (예: 01)
birth_mYes생년월일 - 월 (예: 01)
birth_yYes생년월일 - 년 (예: 2000)
ghost_numNo식별번호 (면허증 우측 표기, 예: 8H1X3Y)
licen_no0Yes면허번호 1구획 (예: 21)
licen_no1Yes면허번호 2구획 (예: 19)
licen_no2Yes면허번호 3구획 (예: 174133)
licen_no3Yes면허번호 4구획 (예: 01)

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, and the description adds context such as required vs optional fields, a per-call cost, and the need for legitimate processing basis. These go beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two succinct sentences plus a legal note and cost indicator. It is front-loaded with the purpose and avoids unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

It provides essential context: tool purpose, required/optional parameters, legal usage constraint, and cost. It does not describe the return value/response format, which is a gap given there is no output schema, but overall it is sufficient for selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all 11 parameters. The tool description repeats the required/optional distinction and parameter groups but does not add new semantic meaning beyond the schema, so it stays at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Verify the authenticity of a Korean driver license using text input,' with a specific verb, resource, and input mode. This distinguishes it from image-based sibling tools and other document types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It indicates 'using text input' as the context and lists required/optional fields, plus a legal prerequisite for consent. However, it does not explicitly name alternatives or state when not to use, leaving some ambiguity compared to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation5/5

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 Consistency4/5

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.

Tool Count4/5

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.

Completeness4/5

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.

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