AdLoop: Google Ads, Reddit Ads & GA4

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Draft dismissing recommendations

draft_dismiss_recommendations

Preview dismissals for Google Ads recommendations you will not act on, so they stop reappearing in get_recommendations. No account changes; confirm the plan with confirm_and_apply.

Instructions

Dismiss Google Ads recommendations — returns a PREVIEW.

Turns down recommendations you will not take (e.g. "add broad match" on a deliberately narrow account) so they stop reappearing in get_recommendations. Nothing in the account changes, and Google can show a dismissed recommendation again later, so a single confirmation is enough.

Each ID must be an active recommendation: unknown or already dismissed IDs are refused by name. The preview lists each one's type, campaign and estimated improvement, so the user sees what they are turning down.

DismissRecommendation has no validate-only mode: the dry run re-reads the account and checks every recommendation is still active instead of sending the call to Google. The returned plan_id is applied with confirm_and_apply.

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

Input Schema

Name	Required	Description	Default
`customer_id`	No	Ads account ID. Defaults to the configured account.
`recommendation_ids`	Yes	`recommendation.id` values from get_recommendations, or full resource names (customers/{customer_id}/recommendations/{id}). Duplicates are collapsed.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.37.0Oct 28, 2026

TDQS

A4.8/5.0

Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: nothing in the account changes, Google may show a dismissed recommendation again later, one confirmation is enough, and the dry run re-reads the account instead of using a validate-only API mode. It also describes preview contents and validation failures by name.

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 and well structured, with the preview behavior and confirm_and_apply workflow prominent. It is somewhat long, but nearly every sentence carries workflow, safety, or validation information; the API link is useful but not essential.

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?

Given the output schema, full input schema coverage, and annotations, the description is complete for an agent to call the tool correctly. It covers the preview/confirm workflow, validation behavior, and the fact that dismissal is not permanent from Google's side.

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?

Schema coverage is 100%, so the schema already documents both parameters. The description adds meaningful semantics by requiring every recommendation_id to be active and by explaining that unknown or already dismissed IDs are rejected, though it does not add further detail on customer_id 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: dismiss Google Ads recommendations, and immediately clarifies that it returns a preview. It also distinguishes the action from get_recommendations by explaining that dismissed recommendations stop reappearing there.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains when to use the tool: to turn down recommendations the user will not take. It also states prerequisites and flow, including that IDs must be active, unknown or already dismissed IDs are refused, and the returned plan_id is applied with confirm_and_apply.

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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