List Marketing Audiences
list_marketing_audiencesList reusable marketing audiences owned by the API-key account.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_marketing_audiencesList reusable marketing audiences owned by the API-key account.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -{
- "additionalProperties": false,
- "properties": {
- "text": {
- "type": "string"
- }
- },
- "required": [
- "text"
- ],
- "type": "object"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful scoping context ('owned by the API-key account') beyond the annotations, but does not disclose pagination, ordering, or return format. Given the strong annotation coverage, this is adequate but not rich.
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?
One short, front-loaded sentence with no filler or repetition. Every word contributes either the action, the resource, or the scope.
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 parameterless list operation with strong annotations describing safety and idempotence, the description is complete. The scoping phrase removes ambiguity about which audiences are returned, and no output schema is needed to convey that a list is the result.
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 zero parameters, so there are no parameter meanings to convey. The description compensates by clarifying the implicit filter of the operation ('owned by the API-key account'), which is the only semantic an agent needs.
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 states a specific verb ('List'), a precise resource ('reusable marketing audiences'), and an ownership scope ('owned by the API-key account'). It clearly distinguishes this from sibling list tools like list_marketing_brands and list_marketing_campaigns by naming the resource type explicitly.
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 clearly indicates this tool is for listing audiences belonging to the API-key account, providing clear context for when it applies. It does not explicitly name alternatives or exclusion criteria, but the resource and scope are specific enough that an agent can infer the appropriate use.
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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