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Brands in a brand list

get_brand_list_brands
Read-only

List the brands inside a brand list.

Returns the brands and their total. Each entry carries brand.entity_id (the Commercial KG MID that suggest_brands returns as id), the display name, primary URL, status and a criterion_id — the latter is what remove_from_brand_list needs.

Google Ads API: https://developers.google.com/google-ads/api/docs/start

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "shared_set_id": "<shared_set_id>"
    },
    "name": "get_brand_list_brands"
  }
}

Input Schema

NameRequiredDescriptionDefault
customer_idNoAds account ID. Defaults to the configured account.
shared_set_idYesNumeric list ID from get_brand_lists (shared_set.id).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds real value beyond that by enumerating the return shape (entity_id, display name, primary URL, status, criterion_id) and the cross-tool identity of entity_id. It says nothing about pagination or limits, but against these annotations that is a minor gap.

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 purpose is front-loaded in the first sentence, followed by tightly packed return-field detail and a link. Every sentence carries information an agent needs; nothing is wasted.

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?

For a two-parameter read tool with full schema coverage, an output schema, and safety annotations, the description supplies the remaining workflow context (field meanings and the link to remove_from_brand_list). Nothing needed to invoke it correctly is missing.

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%, so both parameters are already documented in the schema, including that shared_set_id comes from get_brand_lists. The description adds no format, syntax, or defaulting detail beyond that, so the baseline 3 is correct.

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?

States a specific verb and resource ('List the brands inside a brand list') and implicitly distinguishes itself from the sibling get_brand_lists, which lists the lists themselves. It also ties the returned brand.entity_id back to suggest_brands' id, so an agent can place it precisely in the brand-list workflow.

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?

Context is clear through cross-references: criterion_id is flagged as what remove_from_brand_list needs, and shared_set_id is sourced from get_brand_lists, giving an agent natural use conditions. It stops short of an explicit when-to-use/when-not statement or naming alternatives as choices, so it does not reach full routing guidance.

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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