google_ads_get_recommendation_insights

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

No annotations are provided, so the description carries full burden. It only states the output is aggregate insights, with no disclosure of side effects or auth requirements. The read-only nature is implicit but not stated, which is a gap.

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 concise and well-structured with sections for Args, Returns, and Example. It front-loads the purpose and quickly provides essential details. No redundant sentences.

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 an output schema exists, the description minimally explains return values. It covers the basics but lacks detail on the exact fields in 'aggregate recommendation insights'. Could mention what counts as 'potential impact'.

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 has 0% description coverage, but the description adds meaning: customer_id format ('without hyphens') and campaign_id as optional filter. The example reinforces usage. This adds value beyond the bare schema.

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 gets aggregate insights about recommendations with total projected impact, grouped by type. This distinguishes it from related tools like get_recommendations (individual details) or get_bid_recommendations. The purpose is specific and adequately described.

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 use when a high-level summary is needed, but does not explicitly differentiate from siblings like google_ads_get_recommendations. No guidance on when not to use this tool or when alternatives are better.

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