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

Annotations already cover read-only, idempotent, open-world, non-destructive semantics, so the description adds real value beyond them: the $0.25 USDC x402 cost and the 0-99 output range with AI-generated reasoning. It doesn't mention rate limits or error behavior for invalid addresses, which keeps it below a 5.

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?

One dense sentence for the core behavior, one for use cases, one for cost — every sentence earns its place and the capability is front-loaded. No filler or repetition of the schema.

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?

With no output schema, the description compensates by disclosing the 0-99 score range and the reasoning component. Cost is disclosed, which matters for a paid call. Response structure beyond the score is still only sketched, so it's solid but not exhaustive.

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 description coverage is 100%: both the required 'lookup' email and the optional 'language' enum are fully documented in the schema. The description adds no parameter-level detail such as format expectations or language behavior, so the baseline 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?

States a specific verb and resource — scores an email address 0-99 and flags disposable addresses, suspicious patterns, and deliverability risk. An agent can tell what it produces. It doesn't explicitly contrast with the sibling interzoid_email_domain_type, so sibling differentiation is left implicit.

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?

Lists concrete use contexts (signup fraud prevention, lead quality scoring, list cleaning, trial abuse detection), which gives the agent a clear trigger for calling it. It stops short of exclusions or naming an alternative tool for adjacent needs like domain-type classification.

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