이메일 유효성 검사
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]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | 이메일 주소 (예: sample.user@gmail.com) |
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) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds meaningful behavioral context: it explains that the tool performs MX lookups and disposable-domain detection, and it discloses the per-call point cost. This goes beyond the schema and annotations without contradicting them.
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 compact, front-loaded with the action and purpose, and includes a cost note. The bilingual repetition is justified given the Korean title and likely user base, and no filler or unnecessary detail is present.
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 one-parameter tool with readOnlyHint and openWorldHint annotations, the description provides enough information to select and invoke it correctly. The only minor gap is that the return value format is not described, but this is mitigated by the clarity of the validation checks listed.
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 description coverage is 100%, and the schema already documents the single 'email' parameter with an example. The tool description adds general context about what is validated but does not add new parameter-level detail 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 names a specific verb ('Validate') and a precise resource (email), and enumerates the exact checks performed: syntax, MX availability, and free/disposable domain status. This clearly distinguishes it from sibling tools like check_phone_valid or 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 makes the tool's context clear: use it when email deliverability/validity checks are needed. However, it does not explicitly mention when not to use it or name alternative tools, so the usage guidance is implied rather than explicit.
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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