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

Beyond the readOnly/idempotent annotations, the description adds concrete behavioral details: how role_address is detected (admin@, info@), that Gmail-style +tag is stripped before classification, free_provider semantics for B2B detection, rate limits (30/hr free, 500/hr Pro), and the ethical decision to omit mailbox enumeration. This provides a full transparency picture without contradicting 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 information-dense but every clause serves a purpose: functionality, usage timing, exclusions, behavior details, rate limits, and return fields. It is front-loaded with the main purpose and flows logically, earning a high score for efficiency and structure.

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?

Given the tool has one parameter and an output schema (which covers return values), the description covers all necessary context: when to use, what it does, what it deliberately excludes, rate limits, and the exact output fields. No critical gaps remain for an agent to correctly select and invoke the tool.

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 already fully documents the 'email' parameter with examples and the requirement for '@'. The description adds a bit of behavior context (e.g., +tag stripping) but does not fundamentally add new parameter-level semantics beyond what the schema provides. With schema coverage at 100%, 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 immediately states the tool validates emails by combining syntax checks, MX records, disposable detection, role-address detection, and free-provider classification. It explicitly distinguishes itself from sibling tools by noting it replaces email_mx + email_disposable + manual role parsing, making the purpose highly specific and well-differentiated.

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 gives clear usage contexts: 'Use BEFORE adding an email to a contact list, sending an outbound message, or auditing a lead-list dump.' It also explicitly states what the tool does NOT do (SMTP RCPT TO deliverability probing) and points to alternative external services for that case, providing both when-to-use and when-not-to-use guidance.

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