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johnoconnor0

Google Ads MCP Server

by johnoconnor0

google_ads_shopping_performance

Get performance metrics for Shopping campaigns including ROAS to optimize ad spend. Specify customer ID and date range.

Instructions

Get performance metrics for Shopping campaigns.

Provides detailed performance data including ROAS (return on ad spend), which is critical for shopping campaign optimization.

Args: customer_id: Google Ads customer ID (10 digits, no hyphens) campaign_id: Optional specific shopping campaign ID date_range: Date range (LAST_7_DAYS, LAST_30_DAYS, LAST_90_DAYS)

Returns: Shopping campaign performance metrics

Example: google_ads_shopping_performance( customer_id="1234567890", date_range="LAST_30_DAYS" )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
campaign_idNo
date_rangeNoLAST_30_DAYS

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations exist, so the description must cover behavioral traits. It describes the tool as retrieving read-only metrics but lacks details on rate limits, authentication, or any side effects. It is a simple retrieval, but more transparency would be beneficial.

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?

Description is front-loaded with purpose, includes args and a clear example. While efficient, it could be slightly more concise without the example, but overall well-structured.

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 presence of an output schema, the description adequately explains the function. It covers all three parameters and gives a high-level return type. For a read tool with simple parameters, this is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage, but the description adds valuable meaning: customer_id format (10 digits, no hyphens), campaign_id as optional, and date_range with example values. This compensates well for the schema gap.

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?

Description explicitly states 'Get performance metrics for Shopping campaigns' and highlights ROAS, clearly differentiating from other performance tools like google_ads_campaign_performance and google_ads_account_performance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description indicates critical use for Shopping campaign optimization, providing clear context. However, it does not explicitly mention when not to use or list alternative tools for other campaign types.

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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