manage_object_construction

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

With no annotations provided, the description carries full burden. It describes the general workflow (natural language to Python script execution, validation for modify) but lacks details on side effects (e.g., scene changes, script storage, failure modes) and does not mention that this is a destructive operation by nature.

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 bullet points for each operation and a client requirement note. It is somewhat verbose (e.g., listing supported clients) but front-loaded with the core purpose. A minor improvement would be to remove the client list or move it to a separate context.

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 has 12 parameters, no schema descriptions, and output schema exists but is not described, the description is incomplete. It fails to explain return values, error scenarios, or how the AI sampling integrates with the parameters. The tool's complexity demands more thorough documentation.

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. However, it only hints at 'description' and 'object_name' through the operation explanations, leaving 10 out of 12 parameters undocumented. Parameters like 'complexity', 'style_preset', 'allow_modifications' are not explained.

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 is for 'AI-powered object construction and modification via sampling' and lists three distinct operations (construct, construct_and_save, modify). This verb+resource specification differentiates it from sibling tools like 'construct_object' which is likely simpler.

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?

No explicit guidance on when to use this tool versus alternatives like 'construct_object' or other blender tools. It mentions a client requirement (MCP sampling) but does not explain contexts for each operation or provide exclusion criteria.

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