Skip to main content
Glama
eneelkant

google-ads-mcp

by eneelkant

get_ad_group_performance

Read-only

Fetch ad group performance metrics for Google Ads, with optional campaign filtering and custom date ranges, to analyze key metrics and optimize campaign ROI.

Instructions

Get ad group performance metrics.

Args: customer_id: Google Ads customer ID. campaign_id: Optional -- filter to ad groups in this campaign. date_range: Date range (predefined or 'YYYY-MM-DD,YYYY-MM-DD'). limit: Max rows (default 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
date_rangeNoLAST_30_DAYS
campaign_idNo
customer_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds scoping behavior (campaign_id filter and accepted date_range forms) but does not disclose return shape, metric fields, pagination behavior, or failure modes.

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 definition leads with a one-sentence purpose then a tight Args list; no line is wasted. It is appropriately sized for a four-parameter read-only tool.

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?

Together with schema defaults and annotations, the description provides enough to construct a valid call: required customer_id, optional campaign_id filter, date_range format, and limit. The main missing context is the exact set of returned metrics and how this report differs from sibling performance tools, but the core invocation requirements are covered.

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?

With 0% schema description coverage, the Args section compensates by giving a meaningful explanation for customer_id, campaign_id, date_range, and limit, including the optional flag, accepted date formats, and default max rows. It does not enumerate the valid predefined date_range values, which would make it fully unambiguous.

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 opens with a clear verb and resource: 'Get ad group performance metrics,' so an agent immediately knows this is a read-only retrieval for ad-group-level metrics. It does not explicitly contrast itself with sibling tools such as get_campaign_performance or get_keyword_performance, so differentiation is left to the name.

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

Usage Guidelines3/5

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

The title and args make the basic use case obvious—fetch ad group metrics, optionally scoped by campaign_id—so usage is implied. However, there is no explicit statement of when to choose this tool over the many sibling performance/report tools, nor any exclusions or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.