biz_detailLook up general status information of a Korean business by its 10-digit business registration number. 사업자등록번호로 해당 사업자의 일반 현황 정보(대표자, 주소, 직원수, 설립일, 업종, 업태, 종목, 연락처, 사업자상태, 과세유형 등)를 조회합니다. [호출당 50포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| biz_no | Yes | 사업자등록번호 (숫자 10자리, 하이픈 제외, 예: 4398700761) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds value by disclosing the call cost ('[호출당 50포인트]') and enumerating the specific data fields returned (representative, address, employee count, etc.), which enhances transparency beyond 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but slightly redundant, repeating the same information in English and Korean. It is front-loaded with the English purpose and includes the cost note, which is useful. Minor redundancy prevents a perfect score.
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 simple read-only lookup with one parameter and no output schema, the description provides a comprehensive list of returned fields, which helps an agent understand the tool's output. It lacks guidance on edge cases or alternative tool selection, but overall it is complete for its complexity.
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 input schema fully documents the single parameter 'biz_no' with format and example, achieving 100% schema description coverage. The description adds no additional parameter semantics, so the baseline score of 3 is appropriate.
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 tool 'Look[s] up general status information of a Korean business by its 10-digit business registration number.' The verb 'look up' and the resource 'business registration number' are specific, and the word 'general' distinguishes it from specialized siblings like venture_biz_info.
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 implies when to use the tool (when a business's general status is needed) but does not explicitly state exclusions or alternatives. It does not mention when not to use it, such as for venture-specific information, leaving the distinction to the reader.
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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Most tools target distinct resources and actions, but there is potential overlap between biz_detail and venture_biz_info, and the PCCC tools (req_pccc, get_pccc, check_pccc) require careful reading. Descriptions are clear enough to avoid major misselection.
Tool names mix verb-led patterns (check_*, get_*, req_*, search_*) with noun-phrase patterns (biz_detail, holiday_info, land_rt_price, parcel_tracking). This inconsistency makes it less predictable than a uniform verb_noun scheme, though names remain readable.
With 16 tools, the set is slightly above the typical 3-15 range, but the broad scope of the API—spanning business info, personal validation, car history, parcel tracking, and address search—justifies the count. No tool feels redundant.
The API covers its core verification workflows, but notable gaps exist: no tool for listing parcel carriers despite being referenced in parcel_tracking, no business search by name, and car history only covers flooding and scrap, missing general accident records. These gaps could limit agent workflows.