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damientilman

Mailchimp MCP

get_automation_email_queue

Read-only

Retrieve the queue of subscribers scheduled to receive a specific automation email, including email address and next send time.

Instructions

Retrieve the queue of subscribers about to receive a specific automation email, with scheduled send times.

Use to see who is waiting to receive a particular email in a workflow. Use get_automation_emails first to find email_id values within the workflow.

Args: automation_id: The automation workflow ID (e.g. 'auto123'). Obtain from list_automations. email_id: The specific email ID within the automation. Obtain from get_automation_emails.

Returns: JSON with total_items (int) and queue array. Each entry: email_address (string), next_send (ISO 8601 timestamp of scheduled send).

Example: get_automation_email_queue(automation_id="auto123", email_id="email456") -> {"total_items": 12, "queue": [{"email_address": "jane@co.com", "next_send": "2025-06-02T10:00:00Z"}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
email_idYes
automation_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description is consistent. It adds context that the tool returns scheduled send times and an example response, which is valuable beyond the annotations. No contradictions.

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: one sentence for purpose, one for usage, then Args, Returns, Example sections. Every sentence adds value. No redundancy.

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

Completeness4/5

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

For a read tool with 3 parameters and an output schema, the description is nearly complete. It explains how to obtain parameter values, describes the return format, and gives an example. The only minor gap is the undocumented account parameter.

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 description coverage is 0%, so the description must compensate. It explains automation_id (obtain from list_automations) and email_id (obtain from get_automation_emails), and provides example values. However, the optional 'account' parameter is not mentioned, leaving it undocumented.

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 it retrieves the queue of subscribers about to receive a specific automation email with scheduled send times. It uses a specific verb ('Retrieve') and resource ('queue of subscribers'), and distinguishes from sibling tools like get_automation_emails and add_automation_queue_subscriber.

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 use get_automation_emails first to obtain email_id values, and states 'Use to see who is waiting to receive a particular email in a workflow.' This provides clear sequential context. It does not specify when not to use, but for a read-only tool, exclusions are less critical.

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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