mailchimp_get_audienceGet a single audience (list) by id, including subscriber stats, default from-name/email and settings. REST: GET /lists/{list_id}.
| Name | Required | Description | Default |
|---|---|---|---|
| list_id | Yes | The audience (list) id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, signaling a safe read-only operation. The description adds the REST method GET and the included fields, but does not disclose additional behavioral traits like auth requirements, rate limits, or error scenarios. This is adequate given the annotation coverage but not above baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the action, and includes the REST endpoint for additional clarity. Every sentence provides useful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-resource GET with one parameter and no output schema, the description provides sufficient context by naming key returned fields and the REST endpoint. It slightly under-specifies the full return structure, but is complete enough for this straightforward operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with 'list_id' described as 'The audience (list) id', and the description reiterates the use of an id. Since the schema carries the full parameter meaning, the description adds little beyond what is already structurally available, matching the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get a single audience (list) by id', specifying the verb, resource, and unique selection by id. It also lists the returned content (subscriber stats, default from-name/email, settings), which distinguishes it from sibling tools like mailchimp_list_audiences that list multiple audiences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear this tool is for fetching one specific audience by id, which provides clear context for when to use it. It does not explicitly mention alternatives or exclusions, but the wording 'single audience' versus the sibling 'list_audiences' implies the appropriate use case.
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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Each tool targets a distinct resource-action pair, with clear distinctions between get/list/search for members and between add/update/archive for member changes. There is no meaningful overlap that would confuse an agent.
All tools follow the consistent mailchimp_verb_noun pattern in snake_case, making the action and resource predictable from the name. Deviation is minimal and stylistic.
With 18 tools, the count is slightly above the typical 3-15 range, but each tool covers a distinct Mailchimp resource (audiences, members, campaigns, reports, templates, automations, segments), so the breadth is justified.
The surface is heavily read-focused; write operations exist only for members (add, update, archive). Core workflows like creating or updating audiences, campaigns, templates, and segments are missing, which would hinder agents from performing typical Mailchimp tasks.