get_training_runs

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

With no annotations, the description suggests a read-only 'Get/Shows' behavior and summarizes the output fields. However, it does not disclose ordering, defaults beyond the schema, possible pagination, or side effects, so behavioral transparency is only basic.

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 two short, focused sentences with no filler. The action and resource are front-loaded, and the second sentence concisely describes the result 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?

For a simple optional-parameter list retrieval, the description is mostly adequate, and the schema covers the input arguments. But because there is no output schema and no sibling differentiation, it leaves ambiguity about ordering, scoping, and how this tool compares with get_pipeline_runs or get_mlflow_runs.

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 description does not need to explain the limit or flowName parameters. The description only adds general output context, not parameter-level meaning.

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 names a specific resource ('Metaflow ML training pipeline runs') and the informational fields returned ('training status, parameters, and duration'). It is clear, but it does not explicitly differentiate this tool from siblings like get_pipeline_runs or get_mlflow_runs.

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 usage guidance is given. The description does not say when to choose this tool over get_pipeline_runs, get_mlflow_runs, or get_pipeline_summary, and there are no exclusions or alternative references.

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