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konkomaji

Google Marketing MCP

by konkomaji

ads_add_negative_keywords

Prevent wasted ad spend by adding negative keywords to an ad group, blocking irrelevant search queries from triggering your ads.

Instructions

Add negative keywords to an ad group (block wasteful queries).

Args: customer_id: 10-digit account id. ad_group_id: target ad group id. keywords: negative keyword text list. match_type: EXACT | PHRASE | BROAD. confirm: must be true to apply (else dry-run).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNo
keywordsNo
match_typeNoPHRASE
ad_group_idNo
customer_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It explicitly discloses the confirmation gate: 'confirm: must be true to apply (else dry-run).' This is a key side-effect disclosure. It does not cover duplicate handling or other edge behaviors, but the most important behavioral trait is present.

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 short and well-structured: a one-line purpose followed by a clean argument list. Every sentence adds value, and there is no filler or redundant restating of the tool name.

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

Completeness5/5

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

All five parameters are explained with meaningful semantics, and the dry-run/apply behavior is explicitly documented. Since an output schema exists, return values do not need description coverage. For a write tool of this complexity, nothing essential is missing.

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?

Schema description coverage is 0%, so the description is essential. It compensates fully by defining every parameter: customer_id format, ad_group_id target, keywords as a list, match_type allowed values, and confirm semantics. This goes well beyond the sparse JSON schema.

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 the action ('Add negative keywords to an ad group') and the resource it operates on. The parenthetical 'block wasteful queries' further clarifies intent and distinguishes it from the sibling tool ads_add_keywords.

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 gives clear context for when to use the tool: to block wasteful queries with negative keywords. However, it does not explicitly mention the alternative ads_add_keywords or state when not to use it, so it stops short of a 5.

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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