blender_material_convert_to_pbr

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 does reveal the workflow (analyzes nodes, extracts color/roughness/metallic, rebuilds a PBR graph), which is useful. But it omits critical consequences: whether the original node tree is destroyed or preserved, what happens to nodes that don't map to PBR parameters, whether textures are retained or discarded, and failure behavior for unsupported materials. For a mutation tool this is a significant gap.

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, zero filler. The core action is front-loaded in the first sentence and the mechanism in the second, so an agent grasps the operation immediately.

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 moderate-complexity conversion tool with no annotations and no output schema, so the description must carry more weight. It explains the what but not the operational essentials: whether the operation is destructive/reversible, what happens to unmapped or texture nodes, what qualifies as a convertible material, and what the resulting 'clean Principled BSDF setup' structurally looks like (single node vs. node group). An agent cannot fully predict side effects before calling it.

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 100%, so the baseline is 3; both parameters already have descriptive text in the schema. The tool description reinforces that target_format drives optimization/compatibility of the rebuilt graph, adding marginal context, but it doesn't explain the meaning or effect of each enum value (e.g., what GENERIC implies versus GLTF).

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?

"Convert a material's existing node tree to a clean Principled BSDF setup" names a specific verb, resource, and outcome. The phrase "existing node tree" implicitly differentiates it from siblings like blender_material_set_principled (fresh setup) and blender_material_inspect_graph (read-only inspection), though it never names them explicitly.

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 use case is implied: use this when a material already has a node tree that needs cleaning up into a standard PBR graph. However, there is no explicit when-to-use/when-not-to-use guidance, no named alternatives, and no mention of prerequisites such as the material needing to exist with a compatible node tree first.

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