BlenderMCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool as a polling API, explains that it returns status lists or single statuses depending on the mode, defines completion criteria ('Done' or 'COMPLETED'), failure conditions, and advises to proceed only after final determination. It lacks details on rate limits or error handling, but covers core behavior well.

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 well-structured with clear sections for different modes, using bullet-like formatting for parameters and status interpretations. It is appropriately sized for the complexity, with no redundant sentences. However, it could be slightly more front-loaded by stating the dual-mode nature earlier, but overall it's efficient and informative.

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?

Given the tool's complexity (two operational modes with different parameters and statuses), no annotations, 0% schema coverage, and no output schema, the description does an excellent job of providing necessary context. It explains parameters, return values, completion criteria, and usage instructions. It slightly lacks details on error responses or polling intervals, but is largely complete for effective use.

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 fully. It does so by clearly explaining the two parameters: 'subscription_key' for MAIN_SITE mode and 'request_id' for FAL_AI mode, linking them to previous steps ('given in the generate model step'). This adds essential meaning beyond the bare schema, making the parameters understandable and actionable.

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's purpose: 'Check if the Hyper3D Rodin generation task is completed.' It specifies the verb ('check') and resource ('Hyper3D Rodin generation task'), and distinguishes it from siblings like 'get_hyper3d_status' by focusing on polling for completion rather than general status retrieval.

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 explicit usage guidelines: it specifies when to use the tool (to poll for task completion), when not to proceed (until status is 'finally determined'), and distinguishes between two modes (MAIN_SITE and FAL_AI) with different parameters and status interpretations, offering clear alternatives within the tool itself.

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