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Snouzy

@m6b9/mcp-mailchimp

by Snouzy

list_conversations

Retrieve Mailchimp inbox conversations with filters by audience, campaign, or unread status. Supports pagination.

Instructions

List conversations (inbox messages)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of results (default 10)
offsetNoPagination offset
list_idNoFilter by audience ID
campaign_idNoFilter by campaign ID
has_unread_messagesNoFilter to only unread conversations
Behavior2/5

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

With no annotations, the description must carry the behavioral disclosure burden. It only states 'List conversations (inbox messages)' and does not disclose pagination behavior, sort order, default count, or the meaning of 'inbox messages' in relation to conversation threads. This is a minimal description that adds little beyond the tool's name.

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 a single, focused sentence with no filler or redundancy. It is appropriately concise for a simple list operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no annotations or output schema, and the description does not explain return values, pagination behavior, or typical use cases. While the schema documents parameters well, the description lacks the contextual depth needed for an agent to confidently invoke this tool among many similar list operations.

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

Parameters3/5

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

All five parameters are fully described in the input schema (100% coverage), so the schema handles parameter semantics. The description adds no additional meaning to the parameters, but the baseline of 3 is appropriate because the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists conversations and clarifies them as inbox messages. It distinguishes from the sibling 'get_conversation' (single item vs. list) but does not explicitly differentiate from 'list_conversation_messages' (which lists messages within a conversation).

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as 'list_conversation_messages' or 'search_members'. The schema includes filter parameters like campaign_id and has_unread_messages, but the description does not explain when to apply them or what scenarios they address.

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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