generate_3d_from_text

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

With no annotations, the prose carries the behavioral burden and it does well: it discloses asynchrony, the returned asset shape, the required polling condition, the GLB download location, and credit consumption. It does not cover failure modes or side effects beyond cost, but the core behavioral contract is explicit.

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?

Three dense sentences carry the essential behavior, polling recipe, cost caveat, and engine default with no filler. The most important action and output are front-loaded, and each clause adds information the agent needs before calling the tool.

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 no-output-schema tool with no annotations, this description covers the return contract, completion condition, destination of the GLB, credit cost, and engine sourcing. The main omissions are the semantics of texture/polycount and explicit failure handling, but an agent can invoke the core workflow correctly from this text.

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 description adds engine semantics by pointing to the catalog and the 'omit for default' rule, which goes beyond the schema. However, schema coverage is only 50% and texture and polycount remain undocumented in both the schema and the prose, leaving part of the parameter surface unexplained.

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 opening clause names a specific verb ('Generate'), a concrete output artifact ('game-ready 3D model (GLB)'), and the input modality ('from a text prompt'). It also marks the operation as async, which distinguishes it from synchronous siblings and ties it to the follow-up asset workflow described next.

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 gives actionable when-to-use context: it tells the agent to wait via wait_for_asset or poll get_asset, and to consult list_models for engine choices. It stops short of explicitly contrasting when to prefer generate_3d_from_image or other siblings, so it earns a strong 4 rather than a 5.

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