blender_analyze_viewport

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

With no annotations, the description carries the full burden and does disclose the main behavior: rendering multiple angles, running an Ollama vision model, and returning feedback. However, it does not state whether the operation modifies the scene, what happens if the Ollama server is unreachable, or that multi-angle rendering may be resource-intensive—information an agent would benefit from before invoking it.

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 compact sentences front-load the primary behavior and output, then add the refinement context. Every clause earns its place and there is no redundant schema repetition.

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 covers the main action and the high-level return structure, which is important because no output schema exists. Still, with no annotations, six optional parameters, and many overlapping sibling tools, it leaves gaps around target selection, side effects, and external-service prerequisites, so it is only minimally complete.

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 each parameter (prompt, resolution, object_name, etc.) already has a clear schema description. The tool description repeats no parameter details but also does not need to; the baseline of 3 applies because the schema carries the semantic weight.

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 names a specific action ('Render multi-angle views and analyze with Ollama vision model') and a concrete output (structured feedback with quality score, issues, fix suggestions). This clearly conveys what the tool does, though it does not explicitly position itself against close siblings like blender_render_multi_angle or blender_ai_evaluate.

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 phrase 'for iterative mesh refinement' implies a use case, but the description gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives such as blender_ai_evaluate or blender_render_multi_angle. An agent must infer when this tool, rather than a sibling, is the right choice.

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