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damientilman

Mailchimp MCP

list_segments

Retrieve audience segments and tags with member counts and types. Use to discover segment IDs for campaign targeting or membership management.

Instructions

List segments and tags for an audience with member counts and types.

Use to discover segment IDs for campaign targeting or membership management. Returns both static (tags, manual) and dynamic (saved, auto-updated) segments. Use get_segment for full details including filter conditions.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry.

Args: list_id: Audience/list ID (10-char alphanumeric, e.g. 'abc123def4'). Obtain from list_audiences. count: Segments to return (1-1000, default 20). offset: Pagination offset. Use when total_items exceeds count.

Returns: JSON with total_items and segments array. Each: id (use as segment_id), name, member_count, type ('static'/'saved'), created_at, updated_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_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 covers authentication (API key), concurrency limits (max 10), and idempotency (read-only, safe to retry), along with return format.

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?

Concise yet comprehensive; each sentence adds value. Structured with purpose first, then guidelines, behavior, parameter details, and return format.

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?

Complete coverage given 3 parameters and no annotations: includes purpose, usage, behavior, parameter specifications, and return format. No gaps.

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?

Adds significant meaning beyond schema: list_id format and source, count range with default, offset usage explanation. Compensates for 0% schema description coverage.

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 lists segments and tags for an audience with member counts and types, and explicitly distinguishes from get_segment by noting that get_segment provides filter details.

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?

Provides explicit use case: 'discover segment IDs for campaign targeting or membership management.' Also directs to get_segment for full details, offering a clear alternative.

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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