predict

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

With no annotations provided, the description implies a read-only operation (generating predictions) but does not explicitly state safety or side effects. It does not disclose error conditions, data requirements, or performance implications.

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 extremely concise, consisting of two short sentences that convey the core purpose and list modes. There is no redundant or extraneous information.

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 9 parameters, no output schema, and no annotations, the description lacks essential context: return value format, prerequisite that estimator must be fitted, handling of missing data, and mode selection guidance. It is inadequate for an agent to use reliably.

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 already documents all parameters. The description adds only a mention of modes, which is redundant with the enum. No additional semantic explanation is provided beyond the schema.

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 verb 'generate predictions' and the resource 'fitted estimator', distinguishing it from siblings like 'fit' (which trains) and 'evaluate_estimator' (which evaluates). It lists supported modes, adding specificity.

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?

No guidance is provided on when to use this tool versus alternatives such as 'evaluate_estimator' or 'get_fitted_params'. The description does not indicate prerequisites (e.g., estimator must be fitted) or when not to use each mode.

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