google_ads_bulk_apply_recommendations

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

No annotations are provided, so the description carries the full burden. It warns that applying changes is destructive ('This will make changes to your account') and advises reviewing recommendations. It also describes the return value. However, it does not disclose behavior on partial failures or idempotency, which would enhance transparency.

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 well-organized with sections for purpose, usage, arguments, returns, example, and warning. Each sentence adds value and there is no redundancy. It is concise yet comprehensive, earning its place.

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 the tool's complexity and the presence of an output schema, the description covers the core functionality and return value. However, it omits details like maximum number of recommendations per batch and does not differentiate from sibling tools like google_ads_apply_recommendations_by_type, which could be improved for completeness.

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 coverage is 0%, so the description must add meaning. It explains the customer_id format ('without hyphens') and that recommendation_resource_names are resource names, supplemented with a concrete example. This fully compensates for the lack of schema descriptions, making the parameters clear and usable.

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 'Apply multiple recommendations at once' and provides an example with multiple resource names, effectively distinguishing it from single-recommendation tools like google_ads_apply_recommendation. The verb+resource and efficiency mention make the purpose specific and unambiguous.

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 explains when to use (applying several recommendations efficiently) but lacks explicit guidance on when not to use it, such as for individual application or type-based filtering. It does not mention alternatives like google_ads_apply_recommendation or google_ads_apply_recommendations_by_type, which would help an agent choose correctly.

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