verify_email

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

With no annotations, the description carries the full burden. It details the decision outcomes and the 'suggestions' field for fixes. However, it does not disclose whether the tool has side effects (e.g., logging) or authorization requirements, leaving some behavior opaque.

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 extremely concise at two sentences, front-loaded with the most critical usage instruction. Every part is necessary and clear.

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?

Despite the absence of an output schema, the description explains the key return values and their meanings. A decision tool with multiple outcomes is adequately covered, though it could mention the format of 'suggestions' or any error conditions.

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 coverage is 100%, so the parameters are well-documented in the schema. The description does not add any extra semantics beyond what the schema provides. The baseline 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: to get permission before sending emails. It specifies the three possible return values (send, request_human_confirmation, do_not_send) and how the agent must obey. This distinguishes it from the sibling tool check_action_status, which is referenced for polling.

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?

Explicitly instructs to call this tool 'before sending ANY email', providing clear usage guidance. It also tells the agent what to do based on the response: obey the decision, and if not allowed, use suggestions to fix. It references the sibling tool for following up on human confirmation.

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