blender_refine_iteration

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

With no annotations provided, the description carries the transparency burden. It discloses the workflow steps (multi-angle render, vision analysis, convergence check) and the return values, but it remains silent on whether the object is modified, whether an active session is required, or whether the scene remains unchanged after the call. This is a meaningful gap for a refinement tool.

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 a single, front-loaded sentence that states the action, key sub-steps, and expected return values with no filler. The colon-separated list is compact and easy for an agent to parse quickly.

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 explains the operation and result well enough for a simple call, but with no output schema and no annotations it does not describe orchestration prerequisites such as creating a refinement session first. It also leaves the convergence criteria and the exact meaning of 'issues' unspecified. For a multi-step AI-loop tool, this is functional but incomplete.

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 input schema already documents all six parameters clearly. The description adds no additional meaning about how parameters interact, what defaults apply, or how previous_score and max_iterations influence convergence. Baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 identifies a specific action: running one iteration of the AI refinement loop, and differentiates it from session-level or full-refine siblings by emphasizing 'one iteration' and the convergence check. It enumerates concrete steps the agent can expect, making the tool's role unambiguous.

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 this tool is meant to be called within a refinement loop, but it does not explicitly say when to use it over alternatives such as blender_refine_create_session, blender_refine_get_session, or blender_ai_refine. No exclusions or transition conditions between loop control tools are provided.

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