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google_ads_location_targeting_update

Update Google Ads campaign location targeting by adding geo-target constants or removing existing criterion IDs in a single mutate. Returns resource names for each operation executed.

Instructions

Add and/or remove location criteria on a Google Ads campaign in a single mutate. Returns [{resource_name}] — one entry per operation executed (adds first, then removes). Mutating — adds create new criteria, removes delete them by criterion_id. Reversible only by calling this tool again with the inverse operations. At least one of add_locations / remove_criterion_ids must be provided. Locations can be passed as bare numeric IDs or as full 'geoTargetConstants/' paths; bare IDs are auto-prefixed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.
add_locationsNoGeo target constants to add, either as numeric IDs (e.g. '2392' for Japan, '2840' for US) or as full resource paths ('geoTargetConstants/2392'). Bare IDs are auto-prefixed.
remove_criterion_idsNoExisting criterion_ids to remove (numeric strings, e.g. '30002'). Obtain via google_ads_location_targeting_list.
Behavior5/5

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

Even with no annotations, the description fully discloses the mutation behavior: adds create new criteria, removes delete by criterion_id, operations are executed with adds first then removes, and reversibility is only by calling the tool again with inverse operations. The return format (one entry per operation) is also specified, providing comprehensive behavioral context.

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 four sentences, each earning its place. It is front-loaded with the core purpose, then covers return format, mutation semantics, reversibility, constraints, and input format details—all without redundancy or filler.

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?

Given the absence of annotations and an output schema, the description is remarkably complete. It explains what the tool does, how operations are ordered, what the return value means, how to reverse changes, and how to format location IDs. Combined with the rich schema, the agent has everything needed to invoke the tool correctly.

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?

The input schema already documents all four parameters with 100% coverage, giving a baseline of 3. The description adds further value by clarifying the accepted ID formats for add_locations (bare numeric IDs or full paths, with auto-prefixing) and explains the relationship between parameters and the operations performed. This goes beyond the schema's individual property descriptions.

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 and/or remove location criteria on a Google Ads campaign in a single mutate.' It specifies the resource (Google Ads campaign location criteria) and distinguishes the tool from the related listing tool (google_ads_location_targeting_list) by focusing on the update/mutation capability.

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 provides clear guidance on when to use this tool by explaining the add/remove operations and the requirement that at least one of add_locations or remove_criterion_ids must be provided. It explicitly notes reversibility via inverse operations. While it doesn't name alternative tools explicitly, the schema references both google_ads_campaigns_list and google_ads_location_targeting_list for obtaining IDs, giving practical context.

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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