google_ads_recommendations_list
List Google Ads recommendations for one customer.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| customer_id | Yes | 10-digit Google Ads customer id. | |
| include_dismissed | No | ||
| recommendation_type | No |
List Google Ads recommendations for one customer.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| customer_id | Yes | 10-digit Google Ads customer id. | |
| include_dismissed | No | ||
| recommendation_type | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'List... recommendations' and gives no information about pagination, default behavior, whether dismissed recommendations are included by default, or what the response looks like. The include_dismissed parameter hints at behavior but the description doesn't explain it.
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 a single, short sentence with no wasted words. It is front-loaded with the verb and resource. However, it is so brief that it misses opportunities to add value.
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 list tool with 4 parameters, no output schema, and no annotations, the description is incomplete. It doesn't explain the meaning of limit, include_dismissed, or recommendation_type, nor does it describe the return format or default behavior. An agent would need to inspect the schema and guess at semantics.
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?
Schema description coverage is only 25% (only customer_id has a description). The description adds no parameter-level meaning beyond the schema. With 4 parameters and 3 undocumented, the description should compensate but doesn't.
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') and resource ('Google Ads recommendations') and scopes it to one customer. It is clear enough to distinguish from the many sibling tools, though it doesn't explicitly name a sibling alternative.
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 gives no guidance on when to use this tool versus alternatives like google_ads_recommendation_apply_prepare or google_ads_recommendation_dismiss_prepare. The 'for one customer' scope is a mild usage hint, but there is no when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.