get_training_job_status

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

Beyond the readOnly/idempotent/non-destructive annotations, the description adds a precise state machine: IN_QUEUE → RUNNING → STOPPED (finished or preempted), FAILED (with error explaining why), or CANCELED. This gives the agent actionable expectations about observable behavior without contradicting the annotations.

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 compact and front-loaded: the action is stated first, followed by a useful endpoint reference and a concise lifecycle list. Every sentence earns its place with no filler.

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 single-parameter polling tool with rich annotations, the description is nearly complete: it defines the purpose, endpoint, and all terminal states. It could go slightly further by describing the shape of step-progress data or advising on polling intervals, but those are minor gaps given the lifecycle is fully specified.

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?

The schema only provides job_id as a required string, and the description adds minimal extra meaning by placing job_id in the backed endpoint path and referring to 'a training job's status.' However, it does not explain how to obtain job_id, its format, or any constraints, so it only partially compensates for the sparse 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 opens with a specific verb and resource: 'Poll a training job's status and step progress.' It also gives the backed endpoint and a full lifecycle, making the tool's role clear and distinguishable from siblings like get_training_job_result and get_model_request_status.

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 clearly conveys that this tool is for polling status and step progress, and the lifecycle states tell the caller when a job has reached a terminal state. It does not explicitly enumerate alternatives or exclusions, but the polling context is unmistakable.

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