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

Beyond the read-only and idempotent annotations, the description discloses quota cost, the two independent checks performed, and the fact that it catches stale-address failures that standard verifiers miss. It does not fully explain the returned fields, but the guidance about presenting recommended action and reason adds useful behavioral context.

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 front-loaded with the core decision, then moves logically through what it answers, why it matters, cost, usage relative to a sibling, and output guidance. Every sentence earns its place and there is no filler.

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 three-parameter, read-only tool with no output schema, the description covers purpose, workflow placement, cost, and high-level return guidance. It could be slightly stronger on what the returned recommendation includes, but it is complete enough for correct invocation.

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%, and the schema already documents the email, enrich, and deliverability parameters in detail. The description reinforces the two-layer model but does not add syntax, format, or flag-specific meaning beyond what the schema provides.

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 states a specific decision-oriented purpose: deciding whether an email address is worth contacting before drafting anything. It distinguishes itself from a named sibling, analyze_contact, and explains the distinct value of catching stale addresses that verifiers miss.

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 gives explicit when-to-use guidance: run before analyze_contact when the address might be dead, and skip it on trusted contacts where it adds a redundant request. It also states the cost relative to an analysis, making the tradeoff concrete.

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