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

With no annotations, the description carries the full burden. It discloses the batch behavior, the maximum count, and the high-level return format. However, it does not mention error handling, side effects, or any constraints beyond the count limit, leaving room for more transparency.

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?

Two crisp sentences, front-loaded with the action and resource. Every word adds value without redundancy.

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 single-parameter tool with no output schema or annotations, the description covers the core behavior, constraints, and return summary. It lacks details on error representation or edge cases, but is reasonably complete given the tool's simplicity.

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 description adds no new insight beyond what the schema already provides for the 'emails' array. The description reinforces the max 100 but does not explain parameter meaning in more depth.

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 the specific verb 'validate' and resource 'email addresses', and adds 'Batch' to distinguish from sibling tools like validate_email. Mentions the limit of 100 and the output of individual results plus summary stats, making the purpose unambiguous.

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?

Implies usage for validating multiple email addresses at once, but does not explicitly compare with sibling tools or state when not to use it. The phrase 'at once' gives some context, but no clear alternative/exclusion guidance is provided.

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