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jonathan-politzki

Smartlead Simplified MCP Server

smartlead_auto_generate_mailboxes

Generate mailboxes automatically for specified domains using provided personal details to support email marketing campaigns and outreach activities.

Instructions

Auto-generate mailboxes based on the domain name and personal details provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainsYesList of domains and associated mailbox details
vendor_idYesID of the vendor from whom you want to purchase the domains and mailboxes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'auto-generates mailboxes' but fails to clarify critical aspects like whether this is a creation/mutation operation, what permissions or vendor relationships are required, potential side effects (e.g., costs, rate limits), or the expected output format. This leaves significant gaps for an AI agent to understand the tool's behavior.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness2/5

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

For a tool that appears to create or configure mailboxes (implied by 'auto-generate'), the description is inadequate given the lack of annotations and output schema. It doesn't explain what 'auto-generate' entails operationally, what the result looks like, or any dependencies like vendor setup. This leaves the AI agent with insufficient context to use the tool effectively.

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?

The input schema has 100% description coverage, clearly documenting the two parameters ('domains' and 'vendor_id') and their nested structures. The description adds minimal value beyond this, as it only vaguely references 'domain name and personal details' without providing additional context or syntax details not already in the schema.

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

Purpose4/5

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

The description clearly states the action ('auto-generate mailboxes') and the required inputs ('based on the domain name and personal details provided'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'smartlead_place_order_mailboxes' or 'smartlead_get_mailbox_summary', which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, such as 'smartlead_place_order_mailboxes' or other mailbox-related tools in the sibling list. It lacks any mention of prerequisites, exclusions, or specific contexts for application.

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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