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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely new context the annotations cannot: the response progresses (progress while running) and matures into a full report on completion, which matters when there is no output schema. It stops short of stating terminal/error states or polling cadence.

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?

Two short sentences, no filler, and the core action (poll for status) is front-loaded. The second sentence earns its place by describing the two-stage return behavior.

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 no output schema, the description must carry return-value meaning and it does so at a high level: progress during execution, full report after completion. It is nearly complete for a polling tool, though failure/terminal-state handling and expected call cadence remain unstated.

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%: jobId is documented as the value returned by optimize_model and customerId as a superadmin-only target. The description adds nothing about either parameter, so the baseline 3 is correct given the schema carries the full load.

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 states a specific verb and resource: poll a model optimization job for status and results. It is clear what the tool does, but it does not distinguish itself from near-siblings such as get_optimization_details, get_training_job, or get_simulation_status, which an agent might otherwise confuse with it.

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?

"Poll" implies repeated invocation until the job finishes, which is useful implied guidance. However, it names no alternatives and gives no explicit when-to-use/when-not-to-use conditions (e.g., versus get_optimization_details or get_training_job), leaving routing to inference.

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