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itallstartedwithaidea

google-ads-mcp

get_recommendations

Retrieve Google Ads optimization recommendations for an account, with optional filtering by recommendation type to find improvement opportunities.

Instructions

Return Google's optimization recommendations for the account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYesGoogle Ads account ID.
login_customer_idNoOptional MCC ID.
recommendation_typeNoOptional filter — e.g. 'KEYWORD', 'BID', 'TARGET_CPA_OPT_IN', 'ENHANCED_CPC_OPT_IN', 'MOVE_UNUSED_BUDGET', 'SITELINK_ASSET', 'CALL_ASSET', 'CALLOUT_ASSET'. Leave None for all types.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It only states the basic action without mentioning that it is read-only, any required permissions, or the structure of the response. This lack of detail is a notable gap.

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, clear sentence with no unnecessary words. It is concise and to the point, earning a perfect conciseness score.

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?

An output schema exists, so return values are already documented. The description is minimal but sufficient for a simple getter; it doesn't mention filtering, but the schema covers that. The main slight gap is not conveying the value or variety of recommendations, though this does not detract significantly.

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 three parameters are fully described in the input schema, including the filter values. The description adds no parameter-specific meaning, but the schema coverage is 100%, so the baseline of 3 is appropriate.

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 returns optimization recommendations for the account, using a specific verb and resource. It doesn't explicitly reference sibling tools, but the resource is distinct enough that the purpose is unambiguous.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or contexts where other tools would be more appropriate. It is a statement of function without usage direction.

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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