google_ads_get_optimization_score

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

Although no annotations are provided, the description discloses it is a read operation ('Get'), explains the score calculation basis (recommendations, priority, impact), and mentions the return value includes a breakdown. This provides good behavioral context beyond a simple 'get'.

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 structured with a clear first sentence, bullet points for explanation, and an example. It is front-loaded but includes some redundancy (e.g., repeating the score meaning). Generally efficient.

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 low complexity (single parameter) and presence of an output schema (context signals), the description adequately covers the purpose, return value, and usage. The example further clarifies invocation.

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 only parameter, customer_id, is described as 'Customer ID (without hyphens)' in the Args section, which adds format guidance beyond the schema (which just says 'string'). Schema coverage is 0%, so the description compensates well.

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 the account's optimization score (0-100%), explaining what it represents. The name and description distinguish it from sibling tools like google_ads_get_recommendations or google_ads_apply_recommendation, as it focuses solely on the numeric score.

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?

No explicit guidance on when to use this tool versus alternatives (e.g., when to use get_recommendations instead). The description does not provide when-to-use or when-not-to-use context, leaving the agent to infer based on tool names alone.

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