google_ads_btob_optimizations

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

With no annotations, the description takes full responsibility for behavioral disclosure. It explicitly states 'Read-only' and provides detailed algorithmic rules for each suggestion category (e.g., 'Device fires MEDIUM when Mobile CPA > Desktop CPA * 1.3'), plus the return structure. This exceeds typical transparency.

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 dense but every sentence serves a purpose: it summarizes the checks, specifies the return object, gives trigger conditions, declares read-only, and states when to use alternatives. It is front-loaded and free of padding.

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 tool has no output schema, but the description fully specifies the return structure and value domains. It explains all three check categories, their triggers, and usage context. Combined with the detailed input schema, the description is complete for an agent to invoke and interpret results.

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 description does not discuss parameters directly, but schema coverage is 100% with rich descriptions (e.g., period usage guidance, campaign_id format, customer_id fallback). Per the rubric, baseline is 3 for high schema coverage; the description adds no additional parameter meaning 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 uses a specific verb ('Run') with a clear resource ('B2B-specific optimization checks against a Google Ads campaign') and enumerates the exact checks (schedule, device CPA disparity, informational-query ratio). It distinguishes itself from generic diagnosis tools by explicitly naming google_ads_performance_analyze as an alternative.

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 states exactly when to use this tool ('when the advertiser self-identifies as B2B') and provides an explicit alternative for general cases ('For general campaign diagnosis use google_ads_performance_analyze'). This gives the agent both a clear trigger and a fallback.

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