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by com.getadloop
OverviewDiscussionsAdmin

Auto-apply recommendation subscriptions

get_recommendation_subscriptions
Read-only

List the recommendation types Google applies automatically (auto-apply).

A subscription makes Google apply every new recommendation of its type without asking, so changes reach the account with no preview. Returns each subscription's type, status (ENABLED or PAUSED), create_date_time and modify_date_time. A type that is not listed is not auto-applied. insights[] names every ENABLED type and flags one modified in the last 30 days, so a recurring audit can catch auto-apply being switched on.

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

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_recommendation_subscriptions"
  }
}

Input Schema

NameRequiredDescriptionDefault
customer_idNoGoogle Ads customer ID, digits with or without dashes (e.g. "123-456-7890"). Defaults to the configured ads.customer_id.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so safety is covered. The description still adds real context beyond them: what a subscription actually does (Google applies every new recommendation of that type without a preview), the ENABLED/PAUSED status vocabulary, the rule that an unlisted type is not auto-applied, and the 30-day-modified flag in insights[] for audits.

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 purpose is front-loaded in the first sentence and the follow-on detail about no-preview behavior and the unlisted-type rule each earn their place. The trailing Google Ads API documentation URL is boilerplate that adds little, and the sentences are broken across lines mid-clause, which slightly hurts scanability.

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?

For a one-optional-parameter read tool with an output schema and read-only annotations, the description covers what the agent needs to interpret results, including the negative case (unlisted type means not auto-applied). The remaining gap is routing: it does not mention the draft tool that modifies these subscriptions.

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?

There is a single optional parameter and schema description coverage is 100%, with the schema already explaining the dashed-digits format and the configured default. The description adds nothing about customer_id, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence gives a specific verb and resource: list the recommendation types Google applies automatically. It clearly describes a read of auto-apply subscription state, which is distinct from get_recommendations (individual recommendations). However, it never names the sibling that changes subscriptions (draft_recommendation_subscriptions), so the agent must infer the boundary itself.

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 rather than stated: the description explains that a subscription applies changes with no preview and that insights[] supports a recurring audit, which hints at when to call it. It never says when NOT to use it, nor points to draft_recommendation_subscriptions for enabling or pausing auto-apply, so the write counterpart is left undiscovered.

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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