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

The description goes beyond annotations by explaining the idempotent nature of the call and the behavior of the sandbox parameter (validate, apply rate limits, store nothing). This discloses side effects and testing behavior clearly.

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 concise—just two sentences—and front-loads the primary purpose, followed by the idempotency clarification. No redundant or filler content.

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?

Given the simple parameter set and no output schema, the description covers all essential usage aspects: the action, idempotency, sandbox mode, and parameter semantics. Nothing is missing for an agent to invoke this correctly.

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?

All parameters are described with meaningful context (e.g., email is 'Required so the record has a traceable origin', sandbox is 'Dry run'). The descriptions add nuance beyond the schema format, such as the purpose of the email and the sandbox's effect.

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 clearly states the action ('Reserves a seat on the waitlist'), the resource ('Cotal Cloud, the hosted Cotal mesh'), and the target audience ('for the user's email'). It is specific and distinct from sibling tools like subscribe_newsletter or request_call.

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 description provides practical usage guidance by noting idempotency ('calling again updates the optional details instead of adding a second seat') and the sandbox dry-run mode. It does not explicitly contrast with sibling tools, but the purpose is clear enough that an agent would infer when to use it.

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