ads_list_recommendations

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

With no annotations provided, the description carries the full burden. It discloses the output structure (resource_name + type) and implies a read-only listing operation. It also hints at the connection to apply_recommendation. It does not mention auth, rate limits, error behavior, or pagination, but for a simple listing tool these are minor omissions given the clear purpose.

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 efficient: one paragraph explains the purpose and output, another lists the two arguments with brief semantics. No unnecessary detail, and the purpose is front-loaded. It earns every sentence.

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?

Given it is a simple listing tool with only two parameters and an output schema (not shown but indicated), the description provides enough for an agent to call it correctly: it states what it does, the input parameters, and how the output relates to apply_recommendation. It lacks explicit error handling or auth notes, but these are not critical for a basic list operation.

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 meaning beyond the schema by explaining customer_id as a 10-digit account id and limit as max recommendations. This goes beyond the bare type definitions. It does not clarify that customer_id is optional (schema default null) or that limit has a default of 50, but the core semantics are covered.

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 clearly states the tool lists Google's optimization Recommendations for the account, explicitly tying it to the Ads UI Recommendations tab and giving concrete examples of recommendation types (keywords, budgets, bids, ad strength). It also notes that each result contains a resource_name and type, which directly distinguishes it from apply_recommendation and other list tools.

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 implies a workflow by stating that the returned resource_name and type can be passed to apply_recommendation, giving some context on when to use this tool. However, it does not explicitly state when to use it versus alternatives, nor does it mention exclusions or conditions. There is no comparison with sibling list tools like ads_list_accounts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.