google_ads_get_recommendations

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

No annotations are present, so the description carries full burden. It discloses the read-only nature, describes possible recommendation types, and mentions output formatting options. However, it does not address pagination, rate limits, or default behavior when no 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?

The description is well-structured with sections (overview, Args, Returns, Example, Common Types). Every sentence adds value, no fluff. Information is front-loaded with clear purpose.

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 moderate complexity and presence of output schema, the description provides sufficient context: purpose, parameter details, return value description, and example. The common types list further clarifies the scope of recommendations.

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 compensates fully by explaining each parameter: customer_id format, recommendation_types as optional list with common values, campaign_id as optional filter, and response_format options. Provides example and common types list.

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 retrieves optimization recommendations from Google Ads. It explains that recommendations are specific optimizations like keywords, budgets, bid strategies, distinguishing it from sibling tools that apply or dismiss recommendations.

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 usage for fetching current recommendations but does not explicitly state when to use this tool vs alternatives like google_ads_get_recommendation_history or google_ads_budget_recommendations. No exclusions or comparison with sibling tools provided.

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