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주민등록증 개인정보 마스킹

identity_document_id_card
Read-only

Extract key fields from a Korean resident registration card image and mask the last 6 digits of the RRN. 주민등록증 이미지에서 지정 정보를 추출하고 주민등록번호 뒷자리 6자리를 마스킹한 이미지를 함께 반환합니다. PNG 또는 JPEG 이미지 파일 하나만 전달하면 되며, 마스킹된 이미지는 JSON 응답의 masked_image 필드에 base64로 포함됩니다. 정보주체의 동의 등 적법한 처리 근거를 확보한 경우에만 사용하십시오. [호출당 30포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlYes다운로드 가능한 https URL (허용 형식: image/jpeg, image/png) (최대 50MB)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description explains the output format (masked_image field with base64), input limits (PNG/JPEG, single file), legal processing requirements, and per-call cost. There is no contradiction with the annotations.

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

Conciseness4/5

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

The description is compact and front-loaded: purpose first, then input requirements, output behavior, and legal caveat. The bilingual repetition is mild but does not hurt clarity.

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

Completeness3/5

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

It covers invocation well, but there is no output schema and the description does not enumerate which key fields are extracted or how they appear in the JSON response beyond masked_image. For a document-extraction tool, that is a meaningful gap, though enough information is present for basic use.

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 already fully documents image_url with allowed MIME types and the 50MB size limit. The description restates PNG/JPEG and single-file requirements but adds no genuinely new parameter semantics, so the schema-coverage baseline of 3 applies.

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 uses a specific verb ('Extract') and a clear resource: Korean resident registration card images. It also states the exact masking behavior (last 6 digits of the RRN), which distinguishes it from sibling tools like identity_document_passport or identity_document_driver_license.

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 clearly communicates when to use the tool: when a user has a single PNG/JPEG image of a Korean resident registration card and needs key fields plus a masked RRN image. It also includes important legal-consent guidance and input format constraints, though it does not explicitly name alternative tools or when not to use this one.

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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