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

Annotations already establish this as a read-only, non-destructive operation. The description adds substantive behavioral context by specifying the three output categories and the criteria for each, plus the presence of optimization suggestions. The only minor gap is that 'significantly over target' is not precisely quantified, but the categorization logic is still meaningfully disclosed.

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 a single, front-loaded sentence that begins with the action and then enumerates the output categories efficiently. Every phrase contributes meaning: the categorization criteria and the inclusion of suggestions are both stated with no filler or redundancy.

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?

With no output schema, the description does explain the return shape at a conceptual level: categorized campaigns plus optimization suggestions. However, it leaves key parameter semantics unaddressed and does not clarify ambiguity around thresholds or how date-related parameters interact. It is adequate for a basic understanding but not fully complete for confident 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 description coverage is only 43%, so the description must compensate for undocumented parameters. It aligns with min_spend and target_acos by mentioning 'spending' and 'target ACoS', but it does not clarify limit, start_date, end_date, or period_days. An agent would not understand how to set date ranges or limit the analysis from either the schema or the description.

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 function: analyze campaigns and categorize them into top performers, running hot, and wasted spend, while providing optimization suggestions. It uses a specific verb ('Analyze') and a specific resource ('campaigns'), and the category definitions add useful detail. It does not explicitly distinguish itself from siblings like ppc_bid_recommendations or ppc_campaign_details, so it stops short of a 5.

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 this tool is for understanding campaign performance relative to target ACoS and generating optimization suggestions, but it gives no explicit guidance on when to choose it over related ppc_* analysis tools. No exclusions, prerequisites, or alternative recommendations are provided, leaving the invocation decision mostly to inference.

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