AdCopilot

Google Ads: list auto-apply recommendation settings

list_auto_apply_subscriptions

Read-onlyIdempotent

Lists the account's auto-apply recommendation subscriptions.

An ENABLED subscription lets Google apply that type of recommendation to
the account without asking. The Google Ads API covers only some of the
types the Google Ads UI can auto-apply: the answer names the rest in
ui_only_types, and only the Google Ads UI can see or change those. Never
tell the user auto-apply is fully off on the strength of this list alone.

Args:
    customer_id: The Google Ads customer ID (numbers only, no hyphens).

Returns:
    Dictionary with subscriptions (type, ui_label, status, dates),
    enabled_types, api_subscribable_types, ui_only_types and
    coverage_note.

Tools revision: d80f65c0.

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": {
      "customer_id": "<customer_id>"
    },
    "name": "list_auto_apply_subscriptions"
  }
}

Input Schema

Name	Required	Description	Default
`customer_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the read-only annotations, the description explains that an ENABLED subscription lets Google apply recommendations automatically, that the API covers only some auto-apply types, and that ui_only_types can be seen only in the Google Ads UI. It also gives a crucial caution about not overstating whether auto-apply is disabled.

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 purpose and behavior, then uses clear Args and Returns sections. It is somewhat longer than necessary because the Returns section partly duplicates the output schema, but the extra context is useful and not bloated.

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?

The tool has one required parameter, an output schema, and read-only annotations. The description supplies the missing customer_id format, explains the key API-vs-UI coverage limitation, and warns against misinterpreting the result, so an agent has enough context to call and interpret it 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 has 0% description coverage for customer_id, but the description compensates by specifying that it is the Google Ads customer ID with numbers only and no hyphens. This adds meaningful formatting guidance beyond the 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 states a specific verb and resource: it lists the account's auto-apply recommendation subscriptions. This clearly distinguishes it from sibling tools such as list_recommendations and pause_auto_apply_subscription.

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?

Usage is implied by the tool's purpose, and the description gives an important interpretation warning: never tell the user auto-apply is fully off based on this list alone. However, it does not explicitly say when to choose this tool versus alternatives such as list_recommendations.

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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