google_ads_budget_recommendations

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states the tool 'generates' recommendations, implying a read-only analysis, but does not explicitly confirm that it does not modify any data. It also does not mention permissions, rate limits, or potential side effects.

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 bullet points and an Args/Returns/Example section, making it easy to scan. While it is slightly verbose, it efficiently conveys the tool's purpose, parameters, and return value. The main purpose is front-loaded.

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 moderate complexity (2 parameters, one required) and the presence of an output schema (as indicated by context signals), the description is complete. It explains both parameters, describes the return value, and includes an example. No additional information is needed.

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 input schema has 0% description coverage, but the tool's description provides detailed explanations for both parameters: customer_id format (10 digits, no hyphens) and allowed date_range values (LAST_7_DAYS, LAST_30_DAYS, LAST_90_DAYS). This fully compensates for the schema gap and adds value beyond the 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's purpose: 'Generate AI-powered budget reallocation recommendations.' It then details the types of campaigns it identifies (budget-constrained, underperforming, high ROAS) and that it provides prioritized recommendations. This distinguishes it from sibling tools like google_ads_budget_pacing and google_ads_get_recommendations, which focus on different aspects of budget management.

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 the tool is for analyzing campaigns to inform budget reallocation, but it does not explicitly state when to use it versus alternatives (e.g., google_ads_budget_pacing for pacing, google_ads_recommendations for broader recommendations). There is no guidance on prerequisites or when not to use it.

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