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

Annotations already declare readOnlyHint=true, so the description doesn't need to repeat that. It adds valuable behavioral context: explains the meaning of each verdict, notes that 'unknown' is not billed, and mentions that rows include provider statements and credit costs. This goes beyond the structured data, providing insight into the response content. No contradiction with annotations.

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?

Two sentences with no fluff. The first sentence states the core output and defines verdicts; the second explains the filter. All information is pertinent, and the most important details are front-loaded. Efficient and structured.

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 list tool with no output schema, the description covers what the response contains (one row per address, verdict, provider statements, credit cost) and how to filter. Pagination is standard and self-explanatory via schema. It also clarifies the 'deliverable' filter's meaning, which is crucial for correct usage. No significant gaps for an agent to call it correctly.

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%, so all parameters are documented. The description adds semantic depth for the 'result' parameter by explaining what each enum value means and defining 'deliverable' as a combination. It also hints at the output rows carrying provider details and credit costs, which indirectly informs the 'page' and 'size' usage. The added meaning elevates it above the baseline 3.

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 states a specific verb ('Returns one row per address') and clearly identifies the resource (email verification results). It enumerates the verdict values and explains the 'deliverable' filter, distinguishing it from sibling tools like list_email_verification_jobs (lists jobs) and get_email_verification_job (single job). The purpose is unambiguous and actionable.

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 explains how to use the 'result' filter, clarifying that 'deliverable' means valid plus catch-all, which is what campaigns send to. This guides the agent on when to use this filter. However, it does not explicitly state when to choose this tool over alternatives (e.g., get_email_verification_job for aggregate stats), though the sibling names imply it. Slight gap in exclusions, but the core usage is clear.

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