ads.recommendations.listList active Google Ads recommendations with their estimated conversion and cost impact to identify optimization opportunities and prioritize account changes.
Active Google Ads recommendations with their estimated conversion/cost impact.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| types | No | ||
| customer_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.10.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so safety is covered. The description adds two useful behavioral facts beyond that: only active recommendations are returned, and each carries estimated conversion/cost impact. It does not mention pagination, result ordering, or what happens when no active recommendations exist.
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?
A single short sentence with no filler and the key qualifier ('active') front-loaded. It is efficient, though so terse that it borders on under-specification rather than well-structured brevity.
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?
An output schema exists, so return values need not be explained, but the description leaves all three input parameters unexplained and provides no usage context for a tool sitting among many similar ads.* list/report siblings. For a 3-parameter listing tool, more guidance is needed.
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?
Schema description coverage is 0% and the description supplies no meaning for any of the three parameters. In particular, 'types' (a free-form string array of recommendation type names) and 'limit' (default 100) are completely undocumented, and the description does not explain that customer_id scopes the account. The description does not compensate for the coverage gap.
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?
Names the specific resource (Google Ads recommendations) and scopes it to active ones with estimated conversion/cost impact, which distinguishes it from the mutation siblings ads.recommendations.apply and ads.recommendations.dismiss. It is a noun phrase rather than a verb-led statement, so the read/list action is only implied by the name and annotations.
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?
There is no when-to-use guidance, no prerequisites (e.g. account access requirements), and no explicit routing to ads.recommendations.apply/dismiss or to ads.report.* alternatives. The agent must infer usage entirely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.