google_ads_cost_increase_investigate

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states the tool is read-only, discloses the hardcoded 7-day comparison window, and lists the detailed return structure including change history events and negative keyword candidates. This goes beyond minimal disclosure and sets clear expectations for the agent.

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 front-loaded with the purpose and method. The long enumeration of return fields is necessary because there is no output schema, but it could be slightly overwhelming. Overall it is efficiently structured with no wasted words.

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?

For a complex investigative tool with no output schema, the description is remarkably complete. It details the return object, the hardcoded window, read-only behavior, and explicitly names alternative tools. The only minor gap is not explaining the meaning of each return field, but the field names are self-explanatory and the output schema is absent, so this is acceptable.

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 100%, with both campaign_id and customer_id fully described in the input schema. The tool description itself does not add additional parameter semantics beyond what the schema provides, so the baseline score of 3 is appropriate.

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: 'Investigate the root cause of a Google Ads cost spike or CPA deterioration' with a specific method (comparing last 7 days vs prior 7 days). This distinguishes it from sibling tools like google_ads_performance_analyze and google_ads_monitoring_cpa_goal, which are explicitly named as alternatives.

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 explicitly provides usage guidance: use this tool for cost spike/CPA deterioration root-cause investigation, and points to google_ads_performance_analyze for broader diagnostics and google_ads_monitoring_cpa_goal for CPA-vs-target monitoring. This gives clear when-to-use and alternative tool guidance.

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