verify_email

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 describes the core functionality and business purpose well, but lacks details about error handling, rate limits, authentication requirements beyond the API key parameter, or what happens when the API key isn't provided. The description doesn't contradict any annotations since none exist.

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 well-structured and appropriately sized. It begins with the core purpose, adds business context, then provides clear sections for Args and Returns. Every sentence earns its place, with no redundant information or fluff.

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 tool with 2 parameters, no annotations, and no output schema, the description does a good job covering the essentials. It explains what the tool does, provides parameter semantics, and describes the return structure. However, it could benefit from more behavioral context about error cases or performance characteristics given the lack of annotations.

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?

With 0% schema description coverage, the description fully compensates by providing clear semantic explanations for both parameters. It explains that 'email' is 'The email address to verify' and that 'api_key' is the 'AtData API key' with fallback behavior to environment variable. This adds significant value beyond the bare schema.

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 specific action ('verify an email address'), identifies the resource ('email address'), and specifies the external service ('AtData's SafeToSend API'). It distinguishes from the sibling tool 'batch_verify_emails' by being for single email verification rather than batch processing.

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 provides clear context about when to use this tool ('to filter out invalid and high-risk ones, which results in higher open rates, clicks, and conversions'), but doesn't explicitly mention when NOT to use it or provide detailed alternatives. The sibling tool 'batch_verify_emails' is implied as an alternative for batch operations, but not explicitly called out.

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