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xiaohai-uid

Blender-Mind-MCP

by xiaohai-uid

blender_execute_bpy

Execute custom Blender Python (bpy) scripts with error handling and return value capture.

Instructions

Directly runs custom Blender Python (bpy) scripts with full error containment and return value capture.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesPython script utilizing the bpy API
Behavior4/5

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

The description discloses two important behavioral traits: 'full error containment' and 'return value capture.' This goes beyond a generic 'runs scripts' statement. However, it does not describe side effects on the Blender scene, whether changes persist, or how errors are surfaced (e.g., exception messages vs. structured errors), which could be vital for a general execution tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence. It front-loads the primary action ('Directly runs'), then adds the key features ('full error containment and return value capture'). There is no unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description captures the core function and main behaviors, it leaves gaps: it doesn't describe the output format (e.g., what exactly is returned), how errors are reported (e.g., thrown exceptions vs. status codes), or potential side effects on scene state. Given that this tool executes arbitrary code, these omissions could lead to agent confusion. However, since there are no annotations or output schema, the description is the only source of information, so more completeness would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes the single parameter 'code' as 'Python script utilizing the bpy API.' The description adds the adjective 'custom' but no further semantics. With 100% schema coverage, the description adds minimal value beyond what the schema already conveys.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes Blender Python scripts, which is a specific verb and resource. It distinguishes itself from sibling tools (which are specialized actions like creating primitives or capturing viewport) by being the general 'run any bpy code' tool. It also mentions error containment and return capture, further clarifying its role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is the tool for arbitrary custom scripts, but it does not explicitly state when to use it versus the specialized sibling tools. It lacks guidance on exclusions or when to prefer other tools, requiring the agent to infer the intended usage from the contrast with siblings.

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

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