genderize_predict

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

With no annotations provided, the description carries the full burden. It discloses that the result includes a probability score, which is useful output context, but it does not state that the operation is read-only, nor does it describe confidence interpretation, rate limits, or error behavior. For a simple prediction tool this is adequate but not rich.

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, front-loaded sentence with no redundant or filler content. It communicates the core action and the key return detail compactly.

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 low-complexity, two-parameter prediction tool with full schema coverage and no output schema, the description is nearly complete. It says what is predicted and that a probability score is returned, though it does not explain the output shape further or provide usage routing.

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 both the required name parameter and optional country_id are fully documented in the schema. The description adds no parameter-level meaning beyond what the schema already says, which matches the baseline of 3 when the schema does the heavy lifting.

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 action (predict gender) on a specific resource (a first name) and even mentions the output includes a probability score. It does not, however, distinguish itself from the sibling tool genderize_name or other prediction siblings, so an agent may need to inspect the schema to be sure which to 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?

There is no explicit when-to-use guidance, no mention of alternatives such as genderize_name, and no prerequisites or exclusions. The agent must infer usage from the purpose alone.

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