Campaign conversions against Analytics

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

Annotations indicate read-only and non-destructive behavior, and the description aligns perfectly by focusing on analysis and reporting without mentioning any side effects or data modifications. No contradiction exists.

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 concise and well-structured, using a clear title and two short paragraphs. Every sentence adds value—no fluff 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?

The description covers the core functionality, outputs, and even mentions the GDPR indicator and non-paid channel context. While it does not elaborate on the output schema, the description is sufficient for an agent to understand the tool's purpose and decide when to invoke it.

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 provides some parameter semantics by specifying the date format and default behavior for date_range_start/end, but it does not explain customer_id, property_id, or campaign_name. Since schema coverage is 0%, more explanation would be expected, but the provided details are helpful.

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: 'Campaign clicks → GA4 conversions mapping — the real cost-per-conversion.' It specifies the data sources (Google Ads and GA4) and the outputs (click-to-session ratios, conversion comparison, cost-per-GA4-conversion). This distinct purpose differentiates it from sibling tools like get_campaign_performance or run_ga4_report.

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 outlines the intended use case, such as revealing GDPR indicators and comparing Ads vs GA4 conversions, but it does not explicitly name alternative tools or state when to use this over others. However, the specificity of the function makes the usage clear.

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