check_phone_validValidate and format a phone number with local numbering metadata. 전화번호의 국가, 형식 유효성, 국내 010 모바일 여부를 외부 API 없이 분석합니다. [호출당 10포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | 전화번호 (예: 01012341234, 해외는 +국가코드 형식) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds valuable context: internal processing without external API, specific checks performed (country, format, 010 mobile), and the cost of 10 points per call. It does not cover edge-case behavior for invalid input but still goes 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 two sentences, with the core purpose and key attributes (validation, formatting, local metadata, cost) front-loaded. Bilingual duplication is minor but does not 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?
For a simple single-parameter read-only tool, the description covers the main functionality, the exact checks performed, the no-external-API behavior, and the per-call cost. It does not detail the return structure, but the description enumerates the output dimensions (country, format validity, 010 mobile) sufficiently for an agent to infer it.
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 provides 100% coverage for the single 'number' parameter with examples and format hints. The description reinforces what is validated but does not add significant new parameter semantics beyond the schema. Baseline 3 is appropriate given the high schema coverage.
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 it validates and formats a phone number with local numbering metadata, and specifies concrete analysis aspects: country, format validity, and domestic 010 mobile status. This distinguishes it from sibling tools like check_email_valid and check_spam_number.
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 usage for phone number validation/formatting and mentions it works without an external API, but it does not explicitly provide when-to-use vs alternatives or exclusions. Guidance is implied rather than stated.
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 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.