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itallstartedwithaidea

google-ads-mcp

get_campaign_performance

Retrieve campaign performance metrics for a specified look-back period (7, 14, 30, or 90 days). Use this to analyze ad effectiveness and optimize your Google Ads campaigns.

Instructions

Return campaign performance metrics for the last N days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook-back window — 7, 14, 30, or 90. Defaults to 30.
customer_idYesGoogle Ads account ID (digits only).
login_customer_idNoOptional MCC ID.

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 carries full burden for behavioral disclosure. It only says 'return metrics'; it does not disclose that this likely returns data for all campaigns under the customer (no campaign ID parameter), any data aggregation behavior, authentication requirements, or pagination limits. Critical behavioral traits are absent.

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, focused sentence with no filler or redundant information. Every word carries meaning; it is appropriately concise for a simple read-only metrics tool.

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

Completeness3/5

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

An output schema is present, so return format need not be described. However, given the rich sibling context (many performance tools), the description lacks contextual completeness around scope (e.g., all campaigns vs single campaign) and how it relates to get_pmax_performance. Still, for a basic metrics tool with full schema and output schema, it is minimally adequate.

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 100%: each parameter (customer_id, days, login_customer_id) has a clear description in the schema. The tool description adds no extra parameter meaning beyond what the schema already provides, 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 action ('Return') and resource ('campaign performance metrics'), and scopes it with 'for the last N days'. This distinguishes it from sibling tools like get_device_performance or get_geo_performance, but it doesn't specify what metrics are included (e.g., impressions, clicks) or clarify differentiation from get_pmax_performance.

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 provides no guidance on when to use this tool versus alternatives like get_pmax_performance or get_keyword_performance. There is no mention of exclusions, prerequisites, or context such as 'use for all-campaign overview' vs 'use other tools for breakouts'. Usage is only implied by the name and generic phrasing.

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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