identity_document_passportExtract 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]
| Name | Required | Description | Default |
|---|---|---|---|
| image_url | Yes | 다운로드 가능한 https URL (허용 형식: image/jpeg, image/png) (최대 50MB) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description is not required to state it doesn't modify source data. The description adds valuable behavioral context: cost (30 points per call), output encoding (base64 in masked_image), and the legal usage condition. This goes beyond what annotations provide.
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 concise and front-loaded with the primary purpose. It includes essential operational details (input format, output field, cost, legal note) in two sentences without redundancy. The bilingual structure mirrors the intended audience and doesn't waste words.
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?
With no output schema, the description should list the extracted fields (e.g., name, date of birth, passport number) to set expectations, but it only says 'key fields' generically. It does mention the masked_image field and its encoding, which is helpful, but leaves the full output structure vague. Input requirements are clear, and the cost is noted, so it is adequate but not exhaustive.
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 schema description covers the image_url parameter fully (format, size, HTTPS requirement), so the baseline is 3. The description adds a suggestion about image content (MRZ lines visible) but that is a capture guideline rather than a parameter semantic. No additional meaning beyond the schema's structural details is provided.
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 explicitly states the action (extract key fields) and the resource (passport image) plus the specific operation of masking the passport number and MRZ area. This clearly distinguishes it from sibling tools like identity_document_driver_license and identity_document_id_card, which handle different document types.
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?
It provides concrete input requirements (single PNG/JPEG with both MRZ lines) and a legal condition (consent required), which is clear usage context. It does not explicitly compare to alternative document tools, but the document-type distinction in sibling names makes the intended use obvious.
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.
Most tools have clearly distinct purposes; even within families like identi_card1-5 vs identi_card_image1-5, the text-input vs image-input distinction is clear. However, the sheer number of tools and some near-synonyms (e.g., ocr_identi1 vs identi_card_image1) could cause occasional misselection, but descriptions mitigate this.
Naming follows a loose verb-first pattern (check_, crawl_, download_, draw_, etc.) but includes significant deviations: bare nouns (bank_code, location, whois), numbered variants (identi_card1, identi_card_image1), and mixed prefixes (ocr_, identity_, etc.). The inconsistency is noticeable but still readable and predictable within functional clusters.
80 tools is far above the typical 3-15, but the server is a broad API aggregator covering many independent domains (banking, ID verification, media conversion, search, LLM, etc.), so the high count is somewhat justified. Still, the sheer number makes the toolkit feel unwieldy and hard to navigate, placing it at the high end of acceptable.
Within its stated purpose as a general-purpose utility API, the toolset covers a wide array of common task families: identity document verification (text and image), OCR field extraction, media conversion, web/search, domain/IP lookup, and LLM chat. Most operations have both get and act variants (e.g., set/get watermark, parcel_tracking/auto), with few obvious dead ends for typical use cases.