Validate whether one or more email addresses are deliverable. For a single email use 'email'. For bulk (up to 50) use 'emails' array. Checks MX records, identifies disposable/role addresses.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Single email address to validate | ||
| emails | No | List of email addresses for bulk validation (up to 50) |
Changes observed during successful MCP inspections.
Input schema / properties / email / descriptionPrevious value: -"Email address to validate"New value: +"Single email address to validate"Input schema / properties / emailsAdded value: +{
+ "description": "List of email addresses for bulk validation (up to 50)",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+}Input schema / requiredRemoved value: -[
- "email"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds behavioral detail about checking MX records and identifying disposable/role addresses, which reveals the tool's internal checks. It also states the bulk limit, which is a useful constraint beyond the schema.
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 three short sentences, front-loaded with the core purpose. Every sentence provides distinct information: purpose, parameter selection, and validation checks. No filler or redundancy.
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?
Given the tool's simplicity (two optional params, no output schema), the description covers the essential behavioral aspects: what it validates, the batch limit, and the type of checks performed. It could mention the response format, but that is not critical for selection. Overall, it is sufficient for an agent to decide when to use 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 already documents both parameters (email and emails), so baseline is 3. The description adds the distinction between single and bulk usage and reinforces the 50-email limit, clarifying when to use each parameter. This adds semantic value beyond the schema's descriptions.
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 uses the verb 'Validate' with a clear resource ('email addresses') and specifies 'deliverable', making the tool's purpose unmistakable. It also distinguishes between single and bulk usage, which aligns with the two parameters. This clearly separates it from sibling tools like find_email or enrich_contact.
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 explicitly says 'For a single email use email. For bulk (up to 50) use emails array', providing concrete guidance on parameter selection. It implies the use case (checking deliverability) but does not explicitly contrast with alternatives like find_email. A clear alternative statement would elevate this, but the guidance is sufficient.
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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