email_count

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

With readOnlyHint=true already covering safety, the description adds valuable behavioral context: the tool returns no addresses and can filter by address type. It also clarifies that the query target is a domain or company. No contradiction with annotations exists.

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?

A single, front-loaded sentence that conveys purpose, scope, optional filtering, and a critical behavioral constraint without redundant words.

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 count tool with read-only annotations and no output schema, the description sufficiently covers the invocation intent. The only minor gap is the absence of any statement about required parameters or expected return format.

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 0%, so the description must explain parameters. It covers 'domain'/'company' as the target and 'type' as an optional personal/generic filter, but it does not state that exactly one of domain or company is likely required, nor clarify the relationship between the two parameters.

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 ('Count'), names the resource ('Hunter email coverage'), specifies the scope ('domain/company'), and explicitly states the output exclusion ('without returning addresses'). This clearly distinguishes it from address-returning siblings like email_finder and email_verifier.

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?

It conveys a clear use case: obtain counts of email coverage, optionally filtered by personal or generic addresses. The phrase 'without returning addresses' implicitly warns against using this tool when actual addresses are needed, though it does not name a specific alternative tool.

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