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

With no annotations at all, the description carries the full burden and does it well: it discloses the payment model and exact cost ($0.006 USDC per call via x402), the partial-failure contract ('bad items return per-item errors, not a failed call'), the item cap, and the per-item check list. These are exactly the traits an agent cannot infer from the schema.

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?

Front-loaded with the core purpose, cost, and cap before the mechanics. Every clause carries information (checks, failure mode, price, example). The inline JSON example output is long but justifies itself by substituting for the missing output schema; only the label 'Example output:' feels slightly tacked on at the end.

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?

No output schema exists, yet the description supplies a concrete response example showing count/succeeded/failed and the per-item result shape including deliverable_guess values. Combined with the cost, cap, and error semantics, an agent has everything needed to call this correctly and interpret the response.

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 single parameter already documents '1 to 10 email addresses' with maxItems. The description adds the request envelope shape ({emails:[...]}) and the semantics of the response items (ok, result, deliverable_guess), which is modestly useful, but parameter meaning itself is fully covered by the schema. 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?

Opens with a specific verb+resource+scope: 'Batch email validation for list cleaning: up to 10 addresses per call'. It enumerates the exact checks performed, so an agent knows precisely what it gets. It mentions '10 single calls' generically but never names the actual siblings email_check / email_check_full, so differentiation is implied rather than explicit.

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 '40% cheaper than 10 single calls' framing implies the batch-vs-single tradeoff, and 'list cleaning' implies the use case. But there is no explicit 'use this instead of X when Y' statement, and no guidance on which of email_check, email_check_full or this tool to pick for a one-off address. Usage is inferable, not stated.

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