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여권 개인정보 마스킹

identity_document_passport
Read-only

Extract key fields from a passport image and mask the passport number and MRZ area. 여권 인적사항면 이미지에서 지정 정보를 추출하고 여권번호 및 MRZ 영역을 마스킹한 이미지를 함께 반환합니다. MRZ 2줄이 포함되도록 촬영한 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

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses meaningful behavior: the masked image is returned in the masked_image field as base64, the input must include both MRZ lines, and a legal basis such as consent is required. It also notes the per-call point 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 with the core purpose. The bilingual Korean sentence partially restates the English opener, creating minor redundancy, but every major item (input, output, legal basis, cost) is included without padding.

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?

For a single-parameter tool with no output schema, the description covers the input requirement, the output location (masked_image base64), and the legal prerequisite. It does not enumerate the 'key fields' that are extracted, which is a minor gap, but overall the agent has enough context to invoke it correctly.

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

Parameters4/5

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

The schema already covers image_url type, allowed MIME types, and size limit with 100% coverage. The description adds useful semantic guidance beyond the schema by specifying that exactly one image file should be passed and that it must include the two MRZ lines.

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 identifies the verb and resource: 'Extract key fields from a passport image and mask the passport number and MRZ area.' It is passport-specific and therefore distinguishable from sibling tools like identity_document_driver_license, identity_document_id_card, and identity_document_residence_card.

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?

The description gives clear usage context: pass a single PNG/JPEG image that includes two MRZ lines, and use only when lawful processing grounds exist. It does not explicitly mention alternatives or exclusion cases, but the context is sufficient for an agent to know when this tool is applicable.

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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