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

Annotations already declare idempotent, non-destructive, closed-world semantics, so the bar is lower; the description still adds real value by disclosing the async job-ID return, the polling path to the PNG, that model/size are surfaced in service status, and that there is no external AI fallback.

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?

Four compact sentences, front-loaded with the action and immediately followed by the independence constraint and the polling path. The model-configuration and no-fallback notes are slightly tangential but earn a few words.

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 correctly explains the return (a job ID) and how to retrieve the result, plus where model/size metadata shows up. Enough for an agent to call and follow through; only the idempotency-key retry contract is left unexplained.

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 75% and prompt/consent/access_token are documented in the schema, so baseline is 3. The description adds only the 'complete scene description' framing for prompt and says nothing about idempotency_key or how the free-tier consent requirement interacts with retries.

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 and resource ('Queue a free text-to-image task') and clarifies scope with 'Each task is independent, not an edit of a previous image', which cleanly separates it from the sibling submit_chat_job and submit_compute_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?

Gives a clear use context (full scene description, independent generation, not an edit) and an explicit follow-up workflow via get_studio_job then get_studio_image. It does not explicitly contrast with submit_chat_job, so the when-to-use-this-vs-that guidance is implicit rather than stated.

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