google_ads_recommendation_apply_confirm
Confirm an apply-recommendation draft.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| draft_id | Yes | ||
| customer_id | Yes | 10-digit Google Ads customer id. |
Confirm an apply-recommendation draft.
| Name | Required | Description | Default |
|---|---|---|---|
| draft_id | Yes | ||
| customer_id | Yes | 10-digit Google Ads customer id. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavior. It only says 'Confirm', which suggests a mutating action but gives no details about what changes occur, whether it is reversible, or what the response is. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler or redundancy. It is not bloated, though it lacks any structural elements like contextual cues or examples. Every word earns its place, but it is minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, no output schema, and a bare-bones description, the definition is very incomplete. It doesn't explain the confirm step's role in the prepare/confirm flow, what constitutes a draft, or what the agent should know before invoking it. An agent has to rely on the sibling naming pattern to guess usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information. The schema covers only customer_id with a description; draft_id is undocumented in both schema and description. There's no explanation of how draft_id is obtained or its relationship to the apply-recommendation flow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Confirm') and resource ('apply-recommendation draft'), which distinguishes it from sibling confirm tools like google_ads_recommendation_dismiss_confirm. However, it does not explain what a 'draft' is or what applying a recommendation entails, so it is clear but not fully elaborated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool. It doesn't mention that it should be called after google_ads_recommendation_apply_prepare, nor does it contrast with the dismiss/confirm alternative. An agent must infer usage from the sibling naming convention.
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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