validate_email

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

No annotations are provided, so the description must disclose behavioral traits. It lists the checks performed but omits return format, error handling, network side effects, or rate limits—critical behavioral information for an API that may perform MX lookups.

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 a single sentence, front-loaded with the primary action and resource, and lists features succinctly without any redundant wording.

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 tool is simple with one parameter, but there is no output schema or annotations. The description covers what validations are performed but not the structure of the result or error behavior, leaving the AI agent partially in the dark for invocation.

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 schema covers 100% of the parameter with a clear description ('Email address to validate'), so the baseline is 3. The description adds tool-level features but no additional parameter-specific semantics beyond what the schema already states.

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 opens with a specific verb+resource ('Validate an email address') and enumerates distinct validation aspects (syntax, MX records, disposable detection, typo suggestions), clearly differentiating it from sibling tools like validate_ip or test_regex.

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?

Usage is implied: the tool is meant for validating email addresses. The description does not provide explicit when-to-use or alternative guidance, but the sibling context makes its purpose clear. No exclusions or prerequisites are mentioned.

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