ocr_identi1Extract key fields from a Korean resident registration card (jumin card) image via OCR. 주민등록증 사진에서 이름, 주민등록번호, 주소, 발급일자 등 주요 정보를 추출해 구조화된 결과와 원문 텍스트(raw_text)를 반환합니다. 정보주체의 동의 등 적법한 처리 근거를 확보한 경우에만 사용하십시오. [호출당 12포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| image_url | Yes | 다운로드 가능한 https URL (허용 형식: image/png, image/jpeg) (최대 50MB) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so read-only behavior is covered. The description adds valuable context: it returns structured fields and raw_text, and it discloses the cost (12 points per call). It does not contradict annotations and provides enough behavioral detail for a read-only OCR tool, though it omits details on error handling or invalid-image behavior.
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 core purpose in the first sentence. However, it repeats the same information in Korean and English, which adds slight redundancy. The cost and legal note are useful and not excessive. All sentences earn their place, though the bilingual duplication could be tightened.
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 single-parameter OCR tool with no output schema, the description adequately explains the output (structured results + raw_text) and the input (image URL). It also highlights the legal prerequisite, which is critical context. The only missing piece is explicit differentiation from sibling OCR tools, but the specific card-type reference largely compensates.
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 only parameter, image_url, has a full schema description (allowed formats, max 50MB). The tool description adds no additional parameter semantics or constraints. With 100% schema coverage, the baseline of 3 applies; the description does not augment or clarify the parameter beyond the schema.
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 clearly states the specific verb ('Extract key fields') and the exact resource ('Korean resident registration card' / 주민등록증), and lists the extracted fields (name, resident registration number, address, issue date). It also specifies the output (structured results and raw text). This specificity naturally distinguishes it from sibling OCR tools aimed at other document types, even without an explicit comparison.
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?
The description provides no guidance on when to use this tool versus sibling tools (ocr, ocr_identi2-5). The only usage note is a legal requirement ('use only when you have legitimate processing basis'), which is about compliance, not tool selection. There is no mention of alternative tools or conditions that would steer an agent toward this specific OCR variant.
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 clearly distinct purpose: the generic `ocr` handles any image, while `ocr_identi1` through `ocr_identi5` are each tied to a specific document type (resident card, driver license, passport, certified copy, alien card). There is no ambiguity about which tool to use for a given input.
All tools follow a consistent `ocr` prefix with snake_case, and the specific ones use `ocr_identi` + numeric suffix. While the pattern is predictable, the numeric suffixes are not descriptive of the document type, which reduces self-documentation slightly.
Six tools is well-scoped for an OCR server. The generic tool handles broad use cases, and the five specific tools cover common identity documents without redundancy or bloat.
The server provides both a general OCR tool and structured extraction for the most common Korean ID documents. There are no obvious dead ends; the domain is fully covered for typical OCR and identity-document needs.