gen_tripo_text_to_model

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Submit' and provides an example with confirm_spend=true, which hints at spending/cost but does not explain async behavior, job creation, credit checks, or what happens after submission. Significant behavioral gaps remain.

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 compact and front-loaded with the core action, then a KB anchor, then a concrete example. It is appropriately short and the example is useful, though a bit more context could be packed in without bloating it.

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?

This is a high-complexity tool with 17 parameters, no annotations, and no behavioral or parameter guidance. The description only covers submission and one example, leaving an agent without enough context to correctly invoke the tool or interpret its result. The output schema exists but is not explained; the description relies on an external KB reference.

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 0%, so the description must compensate, but it only names prompt, texture, pbr, and confirm_spend in the example. It does not explain quad, auto_size, face_limit, model_seed, orientation, session_name, texture_seed, model_version, generate_parts, smart_low_poly, negative_prompt, texture_quality, or geometry_quality.

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 states a clear verb ('Submit') and specific resource ('Tripo text_to_model task'). It also provides an example invocation. However, it does not explicitly differentiate from the sibling Tripo tools like image_to_model or refine_model, so it is clear but not fully distinguishing.

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?

There is no guidance on when to use this tool versus the many related sibling tools (e.g., gen_tripo_image_to_model, gen_tripo_refine_model, gen_tripo_get_task_status). The KB reference and example imply usage, but they do not state conditions, exclusions, or alternative selection criteria.

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