google_ads_keyword_forecast_metrics

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

The description adds rate limit (1 QPS) and access requirements (Basic Access) beyond the annotations. It also outlines the return structure, which is not in annotations. Since annotations already declare readOnlyHint=true, the description adds complementary behavioral context without contradicting them.

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 into purpose, args, returns, and rate limit sections. It is not overly verbose, though it includes a fair amount of detail. The structure is logical and front-loads the 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?

The description covers all essential aspects: what it does, how to structure both parameters, what it returns, and operational limits. An output schema exists, so return format details are additionally covered, making the description sufficient for correct 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?

Schema coverage is 0%, so the description fully compensates. It explains customer_id as a 10-digit string and provides a detailed example of campaign_spec with required fields, types, and an illustrative snippet. This is far more informative than 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 a specific verb (Forecast) and resource (KPIs for a proposed keyword plan). It distinguishes from siblings by focusing on forecasting metrics, but it does not explicitly mention alternatives like keyword_ideas or keyword_historical_metrics, so it lacks explicit differentiation.

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 through its purpose but does not state when to use it over alternatives or when not to use it. There is no explicit guidance on context or exclusions, leaving the agent to infer based on the tool's name and purpose.

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