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Mailchimp MCP

delete_interest

Delete a single interest option from a category. Removes the option and its subscriber associations without affecting other options.

Instructions

Delete a single interest option from a category, keeping the category and other options intact.

Use to remove one specific option. The interest and its subscriber associations are removed. Use delete_interest_category instead to remove the entire category with all options at once.

Authenticated via API key. Subject to Mailchimp API rate limits (max 10 concurrent requests). This operation is irreversible. Respects read-only and dry-run modes.

Args: list_id: The Mailchimp audience/list ID (e.g. 'abc123def4'). Obtain from list_audiences. category_id: The interest category ID. Obtain from list_interest_categories. interest_id: The interest option ID to delete. Obtain from list_interests.

Returns: JSON with fields: status ("deleted"), interest_id. Returns error if interest does not exist.

Example: delete_interest(list_id="abc123", category_id="cat456", interest_id="int789") -> {"status": "deleted", "interest_id": "int789"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
category_idYes
interest_idYes

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 covers behavioral traits: irreversible operation, API key auth, rate limits, read-only/dry-run respect, return value, and error handling.

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?

Well-structured with purpose, usage, behavioral details, parameters, return format, and example. No unnecessary information; every sentence adds value.

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 no annotations and no structured output schema, the description is exceptionally complete, covering all needed context: purpose, alternatives, behavioral traits, parameter origins, returns, and error handling.

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?

Despite 0% schema description coverage, the description provides clear meaning for each parameter, including how to obtain the IDs (e.g., 'Obtain from list_audiences'), plus an example.

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 deletes a single interest option from a category, distinguishing it from delete_interest_category which removes the entire category. Specific verb and resource with sibling differentiation.

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 states when to use ('remove one specific option') and when not ('use delete_interest_category instead'), along with authentication and rate limit context.

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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