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

The description adds value beyond annotations by disclosing that an invalid email still results in a successful call with valid=false, and that each call costs 1 credit. This helps the agent predict failure semantics and cost, which annotations alone do not convey.

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 compact and front-loaded: the core action is stated first, followed by the key behavioral detail and the cost note. Every sentence earns its place without 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?

For a simple two-parameter validation tool, the description is nearly complete. It covers purpose, the main validation behavior, the invalid-email success case, and cost. The only missing element is explicit return-shape detail, but the mention of valid=false gives enough signal in the absence of an output schema.

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 input schema already documents both 'email' and 'check_mx' parameters. The description adds useful context about the MX check and the default behavior, but it does not materially expand on parameter meaning 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 and resource: 'Validate an email address.' It clearly distinguishes itself from sibling validation tools like validate_iban and validate_phone by naming the exact object being validated and by specifying exactly what is checked (format and MX records).

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 what the tool does but gives no explicit guidance about when to choose it over alternatives such as validate_iban or validate_phone. While the resource type makes the selection fairly obvious, the description does not state any exclusions or conditions for use.

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