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damientilman

Mailchimp MCP

verify_verified_domain

Complete domain verification by submitting the code sent to the verification address, enabling authenticated sending.

Instructions

Complete domain verification by submitting the code emailed to the verification address.

Run create_verified_domain first to trigger the email, then pass the received code here. Once verified, the domain can authenticate and be used as a sending address.

Args: domain_name: The sending domain being verified (e.g. 'mail.example.com'). Obtain from list_verified_domains. code: The verification code emailed to the address from create_verified_domain.

Returns: JSON with domain, verified (boolean), authenticated (boolean), verification_status, authentication_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
accountNo
domain_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint=false, idempotentHint=false, destructiveHint=false, so the description correctly implies a non-idempotent mutating operation. The description adds context about the step-by-step process (email, code submission) and the post-verification behavior (domain can authenticate). This provides useful behavioral insight 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a one-line purpose, a usage guideline, then parameter explanations labeled 'Args', and a 'Returns' section listing output fields. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists (context signals indicate true), the description lists all return fields (domain, verified, authenticated, verification_status, authentication_status). It covers prerequisites, inputs, and expected outputs completely. No obvious gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description adds meaning for two required parameters: domain_name (e.g., 'mail.example.com' and source list_verified_domains) and code (emailed code from create_verified_domain). However, the optional 'account' parameter is not mentioned, leaving a gap. The description compensates partially but not fully for the missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Complete domain verification by submitting the code emailed to the verification address.' It specifies the verb 'verify' and resource 'domain', and distinguishes it from create_verified_domain (which triggers the email) and list_verified_domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to run create_verified_domain first, then pass the received code here. It also explains the outcome: 'Once verified, the domain can authenticate and be used as a sending address.' While it doesn't state when not to use it, the context is clear and provides strong guidance.

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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