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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds one genuinely new behavioral trait: this is an asynchronous queue operation that requires polling. It does not mention credit consumption, auth, or how kind-dependent params behave.

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 tightly written sentences, front-loaded with the action and followed by the follow-up step. No filler, no redundancy.

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?

This is a complex, nested-param, 4-required-param mutation tool with no output schema and zero parameter coverage, so the description carries the full burden and falls well short. It omits how params depend on kind, what idempotencyKey guarantees, and where modelKey values come from (list_studio_models).

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% and six parameters are undocumented at the top level (modelKey, params, idempotencyKey, influencerId, prompt). The description's mention of image/video/talking-head merely restates the 'kind' enum and adds no syntax, format, or dependency meaning for the other parameters.

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 ('Queue') and resource ('AI generation'), and enumerates the three output kinds (image, video, talking-head) that match the sibling namespace. It is clear on its own, though it doesn't differentiate itself from other create_* job tools like create_clip_job or create_content_job.

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?

It gives a concrete next step ('Poll with get_studio_generation'), which is useful workflow routing. However, it offers no when-to-use-vs-alternative guidance or prerequisites, so usage is only implied rather than stated.

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