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Opus Growth, Ad Platforms MCP Connector

Read Custom Conversion Goals

list_custom_conversion_goals
Read-onlyIdempotent

Lists the CUSTOM conversion goals of a Google Ads account — the named bundles of conversion actions that campaigns can optimise for, with the actions inside each one and the campaigns using it.

This is what to check when Google refuses to delete a conversion action with "cannot be removed because it is used by one or more of your custom goals": the blocking goal is in this list, and the action has to leave the goal (update_custom_conversion_goal) before the action can be deleted. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the trailing 'Read-only' is largely redundant. What the description adds beyond the structured fields is the shape of the result (member actions per goal plus the campaigns using each goal) and the operational scenario that makes the output actionable — useful context for a read tool.

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?

Two sentences, scoped statement first, usage scenario second — well front-loaded. The quoted error string is long but earns its place by defining the trigger; overall there is little waste.

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?

With an output schema present, the description does not need to spell out return values, yet it still sketches the result structure. Annotations cover the safety profile and the description covers scope and use case, so an agent has everything needed to call it correctly.

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 0% and the description never mentions the single customer_id parameter. Because the sole parameter is self-evidently named and typed, this is a minor gap rather than a blocking one, but no syntax, format or sourcing guidance is added 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 (Lists) and resource (CUSTOM conversion goals of a Google Ads account), then defines what they are — named bundles of conversion actions with their member actions and the campaigns using them. The repeated emphasis on 'CUSTOM' cleanly separates it from the sibling list_conversion_goals.

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?

It gives an explicit, concrete trigger: check this when Google refuses to delete a conversion action because it is used by a custom goal, and it names the follow-up tool (update_custom_conversion_goal). It stops short of explicitly contrasting against list_conversion_goals/list_conversion_actions, but the usage context is clear.

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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