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damientilman

Mailchimp MCP

get_campaign_unsubscribes

Retrieve members who unsubscribed from a sent campaign along with their reasons and timestamp. Use for detailed unsubscribe analysis.

Instructions

Retrieve members who unsubscribed from a specific sent campaign, with reasons.

Use get_campaign_report for aggregate unsubscribe count instead.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry. Returns 404 error if campaign_id is invalid. Returns empty array for unsent campaigns.

Args: campaign_id: Campaign ID (e.g. 'abc123def4'). Must be a sent campaign. count: Records to return (1-1000, default 20). offset: Pagination offset. Use when total_items exceeds count.

Returns: JSON with total_items and unsubscribes array. Each: email_address, reason (string or null), timestamp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYes
countNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully handles behavioral traits: states read-only, safe to retry, authentication via API key, concurrent request limit, and specific error/empty responses for edge cases (invalid campaign_id, unsent campaigns).

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 efficiently structured with sections (overview, alternative, traits, args, returns). Every sentence provides unique, relevant information with no redundancy. It is front-loaded with the core purpose.

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 the tool has 3 parameters, no annotations, and an output schema, the description covers all necessary aspects: purpose, usage context, behavioral constraints, parameter details, and return format. It is complete and leaves no gaps for an AI agent.

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

Parameters5/5

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

Schema coverage is 0%, so description must explain all parameters. It does: campaign_id with example and requirement that it's a sent campaign, count with range and default, offset with usage guidance. Also documents return structure, adding value beyond schema.

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 retrieves members who unsubscribed from a specific sent campaign, with reasons. It distinguishes from sibling get_campaign_report by mentioning aggregate count, and the verb 'retrieve' plus resource 'unsubscribes' is specific.

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

Usage Guidelines5/5

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

The description explicitly tells when to use this tool vs get_campaign_report for aggregate counts. It also notes prerequisites (campaign must be sent), error handling (404 for invalid), and rate limits (max 10 concurrent). This coverage is thorough.

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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