check_email_validValidate email syntax, MX availability, and free or disposable domain status. 이메일 형식, MX 수신 가능 여부, 무료·일회용 메일 여부를 검사합니다. [호출당 10포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | 이메일 주소 (예: sample.user@gmail.com) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. The description adds value by detailing the specific checks (syntax, MX, free/disposable) and disclosing the per-call cost (10 points). It does not contradict 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 repeats the same content in English and Korean, which adds redundancy. However, it is short and front-loaded with the core purpose and cost, but the bilingual duplication prevents a higher 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 validation tool with one parameter and no output schema, the description covers the main checks and cost. It lacks explicit output format details, but the low complexity and good annotations make it sufficiently complete for selection.
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?
Schema coverage is 100% with a clear description for the email parameter. The tool description does not add extra semantics beyond the schema, but the baseline of 3 is appropriate when the schema already documents the parameter fully.
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 validates email syntax, MX availability, and free/disposable domain status. This specific verb+resource+scope distinguishes it from siblings like check_phone_valid and check_spam_number. The bilingual text reinforces the same purpose.
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 the tool is for email validation but does not explicitly state when to use it versus alternatives or when not to use it. No alternatives are mentioned, so the agent must infer context from the tool name and description.
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.