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tolkozin

Google Ads MCP

by tolkozin

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Run GAQL queries against a Google Ads account to retrieve matching rows.

Instructions

Run a GAQL query against one account and return the matching rows.

Args: customer_id: Account id (dashes are stripped automatically). gaql: A Google Ads Query Language statement containing a SELECT clause. page_size: Max rows to return (default 1000). login_customer_id: Optional manager/login id for accounts not under the manager in google-ads.yaml. For a direct-access account, pass its own id here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gaqlYes
page_sizeNo
customer_idYes
login_customer_idNo
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses key behaviors: customer_id dashes are stripped, default page_size, and login_customer_id for manager accounts. However, it does not discuss auth, rate limits, or error responses.

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 is front-loaded with the main action and then lists arguments clearly. It is concise without extraneous information, though it could be slightly shorter by omitting redundant phrasing like 'Args:'.

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 4 parameters, no output schema, and no annotations, the description covers the parameters well and explains their usage. It lacks details on return format, pagination beyond page_size, and error handling, but is sufficient for a search tool.

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

Parameters5/5

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

The input schema has 0% description coverage (only titles), so the description adds essential meaning: customer_id is an account id with dashes stripped, gaql is a GAQL statement, page_size defaults to 1000, and login_customer_id is optional for manager accounts. This is critical for correct usage.

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 it runs a GAQL query against one account and returns matching rows. The verb 'run' and resource 'GAQL query' are specific, and it distinguishes from siblings like list_accessible_customers and describe_resource.

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?

The description explains when to use it (run GAQL queries) and provides context for parameters, but does not explicitly state when not to use it or mention alternatives. However, the purpose is clear enough for an agent to decide.

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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