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

Annotations only declare the write/openWorld/non-idempotent profile; the description adds substantial behavior beyond that: it charges credits, the 45 s wait window, that a pending result carries a job_id to feed get_job, that reference images are plan-capped, and that a signed-in account is required. This is exactly the extra context an agent needs for a paid, network-reaching mutation.

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?

Front-loaded with the core action, then each subsequent clause carries a distinct, load-bearing fact (cost, latency, fallback, reference constraint, auth). No filler sentences.

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 an output schema present, return values needn't be described, and the description still covers cost, latency, the job_id fallback, and the auth requirement. Nothing material for correct invocation 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 high (75%), so the baseline is 3, but the description adds genuinely new meaning: reference images are optional and plan-capped, and model/tier selection is sourced from list_models. It does not elaborate on prompt/context/conversation_id beyond the schema.

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+resource ('Generate a new image from a prompt') and scopes it to StockCake's AI models, which cleanly separates it from create_video and the search/edit siblings. An agent can identify the operation without opening the schema.

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?

Routes the agent to list_models for model selection and to get_job when a result is pending, and states the account prerequisite. It stops short of explicitly contrasting with alternatives like search_images or create_video, so it is clear context rather than full when/when-not guidance.

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