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damientilman

Mailchimp MCP

delete_member_permanent

DestructiveIdempotent

Irreversibly delete an audience member's personal data permanently, preventing any future re-import into the audience.

Instructions

Permanently and irreversibly erase an audience member (GDPR-style deletion).

IRREVERSIBLE: this permanently deletes all personal data for the member and prevents that email from ever being re-imported into the audience. This differs from the archive-style delete_member (which only archives the member and can be re-added); use delete_member unless a true GDPR erasure is required.

Authenticated via API key. Max 10 concurrent requests. Respects read-only and dry-run modes.

Args: list_id: Audience/list ID (10-char alphanumeric, e.g. 'abc123def4'). Obtain from list_audiences. email_address: The member's email address. The subscriber hash is derived automatically. account: Optional account name (e.g. 'marketing') configured via MAILCHIMP_API_KEY_. Omit to use the default account. See list_accounts.

Returns: JSON confirming the permanent deletion, or an error object if the member is not found. On success the Mailchimp API returns an empty body (HTTP 204).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
list_idYes
email_addressYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already indicate destructive and idempotent hints. The description adds crucial behavioral details: irreversibility, permanent deletion of personal data, prevention of re-import, and differences from archive deletion. It also notes behavior under dry-run and read-only modes, exceeding annotation coverage.

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 well-structured: starts with a bold warning, then comparison, usage notes, parameter descriptions, and return value explanation. Every sentence adds value, no redundancy.

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?

Despite lack of schema descriptions and output schema details, the description provides complete context: purpose, behavioral traits, parameter guidance, return value (JSON confirmation/error, HTTP 204), and prerequisites (obtain list_id from list_audiences). Works well with annotations.

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 fully compensates: explains list_id format (10-char alphanumeric, example), email_address (hash derived automatically), and account (optional, configuration reference). This adds significant meaning beyond the schema's bare types.

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 permanently deletes an audience member, using the verb 'erase' and specifying 'GDPR-style deletion'. It distinguishes from the archive-style 'delete_member' tool, making the purpose unambiguous.

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 says when to use ('unless a true GDPR erasure is required') and when not to, referencing the alternative 'delete_member'. It also mentions authentication, concurrency limits, and dry-run mode, providing comprehensive usage 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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