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

Annotations already declare it is safe and read-only. The description adds important behavioral context beyond annotations: it returns interim progress while running and a full report when complete, indicating the response changes over the job lifecycle. It does not cover rate limits or polling cadence, but provides solid extra value.

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 sentences with zero waste, front-loading the action and then clarifying the return behavior. Every sentence earns its place.

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 read-only status tool with no output schema, the description summarizes what is returned at different stages. It could mention more about authentication or polling strategy, but given the rich annotations and complete schema descriptions, it is largely sufficient.

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 both jobId and customerId are already documented in the schema. The description adds no parameter-specific semantics beyond what is already provided, making the baseline of 3 appropriate.

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?

States a specific verb ('Poll') and resource ('model optimization job status and results'), clearly describing the tool's function. It does not explicitly distinguish itself from sibling tools like get_optimization_details, but the name and description together are unambiguous.

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 word 'Poll' implies the tool is used after starting an optimization job to check on it, but there is no explicit guidance on when to use this versus get_optimization_details or other status-related siblings, nor any stated exclusions.

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