Image to 3D model (3DGen AI)

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

Annotations already cover safety (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description adds genuinely useful behavior beyond them: explicit credit cost per engine (3 aria / 8 symphony), the engine-dependent nature of options (reflections is symphony-only), and the max of 3 supplemental photos. It stops short of disclosing latency or how/where the GLB is returned.

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 short clauses, front-loaded with the core action, then enrichment hints, then the alternative workflow, then cost. Every sentence carries information; density is high but nothing is redundant.

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 states the output format (GLB) and the cost, which is what an agent most needs for this generation tool. The notable gap is result retrieval — sibling tools include luw_get_result, and the description doesn't say whether the model is returned inline or fetched asynchronously afterward.

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 already 86%, so the baseline is 3. The description nonetheless adds real meaning: extra_angles is framed as 'photos from other angles' capped at 3, and engine values are tied to concrete pricing and naming (symphony = Symphony-3), which helps the agent choose a value rather than just read an enum.

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 textured 3D model (GLB) from a photo of an object', and enumerates the target subjects (furniture, decor, products). It also distinguishes itself from image/video siblings by naming the text-to-3D path explicitly, so an agent can route correctly 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?

Clear usage context: supply a photo, optionally add up to 3 additional angles for accuracy, and for text-to-3D first call luw_generate_image. It names the alternative workflow, though it doesn't state when not to use this tool (e.g. vs. luw_sketch_to_render or luw_render for 2D outputs).

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