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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable operational context beyond annotations: live site reading, 5-25s latency, per-call pricing, x402 payment method, and that failed or empty calls are never charged. It does not contradict the 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 dense but front-loaded: it first defines the returned data, then tier behavior, then the sibling alternative, then price, latency, and payment mechanics. Every sentence adds decision-relevant information, and nothing is redundant against the schema or annotations.

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?

There is no output schema, so the description carries the burden of explaining return values; it does so by enumerating the company attributes returned and the additional LinkedIn fields for tier=max. It also covers latency, pricing, payment, and failure behavior, which are important for an open-world paid enrichment call.

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%, so the schema already documents both parameters. The description adds meaningful semantics for tier=max, namely LinkedIn company page enrichment and email verification, which goes beyond the schema's brief 'Default standard.' The domain parameter remains straightforward and is adequately covered by the schema example.

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 verb and resource ('Company enrichment from a domain') and enumerates the exact data returned: name, description, size hints, address, phones, emails, socials, website platform, email provider, security, and SaaS stack. It also distinguishes the max tier from the standard tier, so an agent can tell what this tool uniquely provides versus siblings.

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 explicitly names the alternative for a narrower use case: 'For only email checks use email_verify.' It also explains what tier=max adds, giving clear selection guidance between the two tiers. No significant usage ambiguity remains.

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