image_to_model

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

Adds behavior the annotations don't convey: the call spends credits and returns a task_id immediately rather than a finished mesh, establishing the async pattern. Annotations already flag it as a non-idempotent, destructive write, so the description isn't obligated to restate that; per-option credit costs live in 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?

Two sentences: the first defines the operation and valid inputs, the second covers side effects and the required next call. No filler, and the most decision-relevant facts (what it makes, what it costs, what to do next) are front-loaded.

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 21-parameter async generator with an output schema and full annotation coverage, the description supplies what the structured fields cannot: credit spend, immediate task_id return, and the wait_for_task handoff. It omits failure/precondition detail (e.g. minimum image size is only in the schema), which keeps it from a 5.

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 100% and every one of the 21 parameters is documented inline, including constraints, defaults and credit surcharges. The description adds no parameter-level meaning beyond restating the accepted input forms, so the baseline 3 is appropriate.

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 ('Generate a 3D mesh from one reference image') and scopes it to a single image, which cleanly separates it from multiview_to_model and text_to_model. The enumerated accepted input forms make the boundary even sharper.

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?

Names the upstream sources that produce valid input (text_to_image / image_to_image task IDs) and gives the explicit follow-up step: 'then call wait_for_task.' It doesn't contrast itself against sibling generators like multiview_to_model or image_to_splat, so it stops short of full when-not guidance.

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