request_verification

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal insight. It implies a mutation (requesting verification likely sends an email), but doesn't specify permissions required, rate limits, whether it's idempotent, what happens on success/failure, or the response format. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits undocumented.

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 a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Request email verification') without unnecessary elaboration. Every word earns its place, making it easy to parse quickly.

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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error handling), response expectations, and usage context. While concise, it doesn't compensate for the missing structured data, leaving the agent under-informed about how and when to use this tool effectively.

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 description coverage is 100%, so the schema fully documents both parameters ('email' and 'collection'). The description adds no parameter-specific information beyond what the schema provides—it doesn't explain why 'collection' defaults to 'users' or how these parameters interact. Baseline 3 is appropriate when the schema handles all parameter documentation.

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 ('Request') and resource ('email verification'), making the tool's purpose immediately understandable. It distinguishes itself from siblings like 'confirm_verification' by focusing on the initiation rather than completion of verification. However, it doesn't specify what type of verification (e.g., initial account verification, re-verification) or the mechanism (e.g., sends verification link/code).

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., unverified email state), exclusions (e.g., already verified emails), or related tools like 'confirm_verification' for completing the process. The agent must infer usage from the name alone, which is insufficient for optimal tool selection.

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