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

Annotations already mark this as read-only, idempotent, open-world, and non-destructive, so the description doesn't need to restate safety. It adds valuable behavioral context: the result includes a 0-99 score and AI-generated risk analysis, it checks deliverability and disposable addresses, and it is a premium paid API costing $0.25 USDC via x402. 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?

The description is three short sentences with no filler. The primary action and key output are front-loaded, followed by useful validation behaviors and pricing. Every sentence contributes information an agent needs.

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 one-parameter read-only lookup with no output schema, the description gives enough to call it correctly: the score range, the nature of the analysis, the validations performed, and the cost. Nothing critical for selecting or invoking this tool is missing.

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 has 100% documentation coverage for the single parameter, and the schema's description already explains that 'lookup' is the email address to score. The tool description does not add meaningful parameter-level detail beyond that, so the baseline score of 3 applies.

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 concrete verb and resource: 'Get an email trust score (0-99)' along with the AI-risk-analysis output. This clearly identifies what the tool does and sets it apart from the many interzoid_* sibling tools, none of which target email trust or deliverability.

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 makes the intended use obvious through 'email trust score', 'validates deliverability', 'identifies disposable addresses', and 'assesses legitimacy'. It does not explicitly name an alternative or say when not to use it, but the scope is clear enough that an agent can route email-validation tasks here without confusion.

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