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ZachHandley

blender-mcp-enhanced

by ZachHandley

register_context_script

Register a Python script for later execution in Blender, organizing by category with an option to make it permanent.

Instructions

Register a Python script for later execution in Blender.

Args:
    script_name: Name for the script (without .py extension)
    script_content: The Python code to save
    category: Category/folder to organize scripts (default: "default")
    permanent: If True, script survives context clearing operations (default: False)

Returns:
    Success/error message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNodefault
permanentNo
script_nameYes
script_contentYes
Behavior3/5

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

The description adds behavioral traits beyond parameter names, such as the 'permanent' flag effect (survives context clearing) and the fact that it registers for later execution. However, it does not mention overwriting behavior, permissions, or limits, and no annotations are present to supplement.

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 front-loaded with the purpose, followed by a clear bullet-style list of parameters and return value. Every sentence adds value with no redundancy or unnecessary detail.

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

Completeness4/5

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

For a tool with 4 parameters (2 required) and no output schema, the description covers all parameters and mentions the return type (success/error message). It does not elaborate on potential errors or prerequisites (e.g., Blender must be running), but it is sufficiently complete for an agent to understand core usage.

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

Parameters4/5

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

With 0% schema coverage, the description explains all four parameters: script_name (without .py), script_content (Python code), category (default 'default'), and permanent (survives clearing). This adds meaning beyond the schema, but does not specify exact constraints or format requirements for script_content.

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 verb 'Register' and resource 'Python script for later execution in Blender', distinguishing it from sibling tools like 'execute_context_script' (run script) and 'list_context_scripts' (list scripts).

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. It does not mention that scripts can be executed later with execute_context_script or that clear_context_scripts removes them, leaving the agent to infer usage from context.

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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