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

Beyond the annotations, the description discloses that credits are charged only on successful generation, that the call returns a job id rather than an immediate image, and that OAuth or an API key is required. These are meaningful behavioral details that an agent needs to manage cost expectations and polling flow.

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?

The description is organized logically: purpose, workflow prerequisite, return behavior, pricing, then auth. It is dense but every sentence adds needed information, and the primary purpose is front-loaded before the procedural details.

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 tool with four parameters and an output schema, the description covers the full invocation contract: what to prepare (quote_id), what happens next (job id poll via get_generation), cost timing, auth methods, and input constraints. Nothing essential for calling the tool 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?

The input schema already documents all parameters with 100% coverage, so the baseline is 3. The description adds practical semantics by explaining that quote_id must come from estimate_credit_cost, that model must match the quoted model, and that only certain models accept image_url, which goes beyond the schema's individual field descriptions.

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?

The description opens with a specific verb and resource, 'Make an AI image,' and lists concrete output types such as product still, thumbnail, poster, concept art, and reference frame. It further distinguishes the tool's output channel by noting the job returns a kind of 'image' to poll with get_generation, separating it from video generation.

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 description clearly states the prerequisite workflow: first obtain a quote_id from estimate_credit_cost, then call this tool, then poll with get_generation. It also explains when authentication is needed and how to provide it, but it does not explicitly name a sibling alternative such as generate_video for when video output is desired.

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