get_training_status

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

With no annotations, the description fully discloses behavior: default immediate return, wait mode with polling intervals and timeouts, response fields including status, trainingTimeSeconds, modelVersionId, and timed_out flag. No contradictions.

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 structured with clear sections, front-loading the primary purpose and then detailing parameters and response fields. Every sentence adds value, no wasted words. It is appropriately sized for the tool's complexity.

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 the presence of an output schema (not shown), the description still explicitly lists response fields and their meanings. It covers default behavior, wait option, timeout handling, and references sibling tools (submit_training_job, list_model_versions). The tool is fully documented for reliable invocation.

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 0%, but the description explains each parameter's purpose (job_id is required, wait enables blocking, timeout_seconds sets max wait, poll_interval_seconds sets poll frequency) with defaults and behavior, fully compensating for the lack of schema descriptions.

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 tool checks a training job by job_id, with specific verb+resource. It distinguishes itself by explaining that if the tool is unavailable, list_model_versions should be used instead, which effectively differentiates from siblings.

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 explicitly explains when to use the optional wait parameter, details polling behavior, timeouts, and defaults. It also provides a fallback method (polling list_model_versions) in case the tool is not available, giving clear context and alternatives.

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