blender_ai_probe_backends

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

No annotations are provided, so the description carries the full burden. It explicitly frames the tool as a read-only probe/report operation and names the reported categories. It does not mention potential latency or what happens when backends are unavailable, but it is transparent about the core non-mutating behavior.

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?

One dense, well-organized sentence. The action and scope are front-loaded, followed by a concise list of outputs and the optional parameter reminder. No filler or redundant wording.

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?

For a simple diagnostic tool with no required parameters and no output schema, the description is nearly complete: it lists the three output areas and the relevant 3D node names. The schema covers the optional parameter. Minor gaps around exact return structure and empty/failure behavior do not block correct 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 100%, and the schema already explains check_nodes as specific node class names with a default of all known nodes. The tool description adds no parameter-level meaning, but the schema fully handles it, so the baseline of 3 applies.

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?

Description uses a specific verb ('Probe') and resource ('AI backends'), and states concrete deliverables: which ComfyUI 3D nodes are available, GPU VRAM, and queue status. This clearly distinguishes it from nearby siblings like blender_ai_list_backends or blender_ai_generate_model.

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 gives clear context: this is for inspecting backend capabilities and node availability. It does not explicitly say 'use this before generating' or name alternatives, but the context is strong enough that an agent can infer when it is appropriate.

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