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damientilman

Mailchimp MCP

list_interests

Retrieve interest options with subscriber counts for a specific category. Use these IDs when updating member interests via add_member or update_member.

Instructions

List interest options within a category, with subscriber counts per option.

Use after list_interest_categories to see individual options (e.g. "Tech", "Sports"). Interest IDs are needed when setting member preferences via add_member/update_member. Do not use to manage member preferences directly; set interests per-member via the API instead.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry. Returns 404 error if category_id is invalid.

Args: list_id: Audience/list ID (10-char alphanumeric, e.g. 'abc123def4'). Obtain from list_audiences. category_id: Interest category ID. Obtain from list_interest_categories. count: Number of interests to return (1-1000, default 50). offset: Pagination offset. Use when total_items exceeds count.

Returns: JSON with total_items and interests array. Each interest: id, name, subscriber_count, display_order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
category_idYes
countNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Despite no annotations, the description fully covers behavioral traits: authentication via API key, max 10 concurrent requests, read-only and safe to retry, and 404 error for invalid category_id. All necessary for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Well-structured into paragraphs with front-loaded purpose, but slightly verbose. Could merge some sentences without loss. Still efficient and clearly organized.

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 output schema exists, the description adds necessary context: auth, rate limiting, error, parameter details, and return format. Covers all aspects needed for correct tool usage.

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?

With 0% schema description coverage, the description compensates by explaining each parameter: list_id (source and format), category_id (source), count (default and range), offset (pagination use). Adds meaning far beyond the 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 'List interest options within a category, with subscriber counts per option.' It uses a specific verb and resource, and differentiates from siblings like list_interest_categories and list_audiences.

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?

Explicitly says to use after list_interest_categories, explains that interest IDs are needed for add_member/update_member, and warns against using to manage preferences directly. Provides clear context and alternatives.

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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