fit

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

No annotations provided. Description discloses the need for appropriate data handles or datasets depending on estimator type, and mentions run_async. However, it does not detail mutation behavior, prerequisites, or failure modes.

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?

Single sentence, front-loaded with main action, no unnecessary words.

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?

With 7 parameters, no output schema, and no return value description, the description is too minimal. Lacks details on async behavior, return format, and scitype-specific examples.

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% with descriptions for all parameters. The description adds value by tying the choice of X_handle/y_handle vs datasets to the estimator's scitype and referencing handles from load_data_source and instantiate_estimator.

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 (fit an estimator) and the resource (estimator on data). It distinguishes from sibling tools like predict or evaluate_estimator by specifying the need to provide handles or datasets depending on scitype.

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?

Provides context on when to use X_handle/y_handle vs datasets based on estimator scitype, but does not explicitly exclude alternatives or mention when not to use this tool.

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