blender_generate_lods

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

Annotations only provide risk flags, so the description adds useful behavior: it creates copies, places them in a collection, and reports original versus generated face counts. This makes the non-destructive, reporting-oriented behavior visible, though it does not address behavior around existing LOD collections or default selection.

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?

Two tight sentences: the first states the action and outcome, the second explains the value of the reports. There is no filler, and important information is front-loaded.

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?

The description gives a solid overview and mentions the face-count output, but with no output schema it leaves some ambiguity around what 'objects: null' means and how existing LOD collections are handled. It is adequate but not fully self-sufficient.

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 100%, so the baseline is 3. The description adds context around decimation and face-count reporting but does not add parameter-level guidance beyond what the schema already provides.

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 specific action ('Create decimated LOD copies of meshes') and a concrete result ('put them in a LOD collection'). It is clearly distinguishable from siblings like blender_duplicate_objects or blender_add_modifier because decimation and LOD collection organization are unique to this tool.

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 implies the tool is for generating LODs but gives no explicit guidance on when to use it over alternatives, no exclusions, and no conditions. An agent must infer the intended use case from the tool name and basic action.

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