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johnoconnor0

Google Ads MCP Server

by johnoconnor0

google_ads_bulk_dismiss_recommendations

Dismiss multiple Google Ads recommendations in a single call to clean up your account and focus on actionable insights.

Instructions

Dismiss multiple recommendations at once.

Args: customer_id: Customer ID (without hyphens) recommendation_resource_names: List of recommendation resource names to dismiss

Returns: Success message with count of dismissed recommendations

Example: google_ads_bulk_dismiss_recommendations( customer_id="1234567890", recommendation_resource_names=[ "customers/1234567890/recommendations/12345", "customers/1234567890/recommendations/12346" ] )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
recommendation_resource_namesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions the action is mutation (dismiss) and returns a success message with count. However, it does not disclose potential side effects, idempotency, rate limits, or whether dismiss is reversible. The example partially compensates.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description uses a clear docstring format with Args, Returns, and Example sections. It is well-structured and not overly verbose. However, the Args section largely duplicates the schema, and some sentences could be merged.

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

Completeness4/5

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

Given the tool's simplicity (2 required params, no enums, output schema exists), the description provides a clear use case with an actionable example. It covers the essential information for an agent to invoke the tool correctly, though it lacks usage guidelines and deeper behavioral details.

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?

Schema description coverage is 0%, so the description must compensate. It provides format guidance for customer_id and recommendation_resource_names with examples, but does not explain the semantics beyond the names. The example clarifies usage, but full parameter meaning is still implicit.

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 'Dismiss multiple recommendations at once,' which is a specific verb+resource combination. It clearly distinguishes from siblings like google_ads_dismiss_recommendation (single) and google_ads_apply_recommendation (different action).

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?

The description does not provide guidance on when to use this tool versus alternatives like google_ads_dismiss_recommendation (single) or google_ads_apply_recommendation. It only implies bulk dismissal but lacks context on prerequisites or conditions.

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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