generate_model

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

With no annotations provided, the description must disclose behavioral traits. It does so by stating the job is async, describes idempotency behavior with clientRequestId (reuse to avoid double charge), and mentions the server generates one if omitted. This is valuable context beyond the schema.

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 concise, about three sentences, and front-loaded with the primary action and requirement. Every sentence adds value: stating async, prerequisite, and idempotency. No fluff.

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 an async job with no output schema, the description covers the start flow, prerequisite, and polling behavior. It doesn't explain all parameters, but given the schema and enum constraints, the missing details are not critical for an agent to make a correct call.

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 50%, so the description partially compensates. It explains the role of imageAssetIds and clientRequestId, but doesn't detail other parameters like mode, quality, texture. However, those have enums which provide some clarity, so the description adds enough value to meet the baseline.

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 clearly states the tool starts an async image-to-3D job on pictostl.com, specifying the input requirement (imageAssetIds) and the output action (poll with get_task). It distinguishes itself from siblings like upload_image and get_task, which are for uploading and status checking respectively.

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 provides clear context: it requires imageAssetIds from upload_image and directs to poll with get_task. It does not explicitly mention when not to use this tool or alternatives, but the workflow is clear enough for an agent to infer.

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