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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds real workflow behavior the annotations cannot: this is a polling endpoint for a job created elsewhere, and terminal states are success or failure. It stops short of describing retry cadence, timeout, or what a completed job returns.

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, zero filler. The job-id form is front-loaded and the polling rationale follows immediately.

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 no output schema, the description covers identity, origin, and polling intent well. It would be stronger if it sketched the success/failure result or told the agent how long/how often to poll, but nothing essential to calling it correctly is missing.

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 coverage is 100% and the schema already documents job_id plus its origin. The description reinforces the 'j_…' prefix convention, which is mildly useful, but adds no format or validation detail beyond the schema. Baseline 3 applies.

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 (check) and resource (async generation job), and pins the identifier form ('j_… id'). It also distinguishes itself from siblings by explaining why a job exists at all — slow models return one instead of an image.

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?

Gives clear conditional context: use it for slow models whose mode is 'async' in list_models, and poll repeatedly until success or failure. It doesn't explicitly state when not to use it or name a stop condition (backoff/timeout), but the trigger condition is unambiguous.

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