Evaluate a Python expression inside Blender and receive its repr. Use this for quick data lookups, such as checking object counts or scene properties, without writing a full script.
Evaluate one Python expression in Blender and return its repr.
A quick lookup that does not need a whole script.
| Name | Required | Description | Default |
|---|---|---|---|
| expression | Yes | A single Python expression, e.g. len(bpy.data.objects) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It clearly says the result is the repr of the evaluated expression, but it does not warn that evaluating a Python expression in Blender can have side effects or mutate the scene, nor does it mention undo 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?
Two tight, front-loaded sentences with no filler. The first sentence states the action and output; the second gives the usage context.
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 one-parameter tool with no output schema, the description covers the essential behavior and return format. It is slightly incomplete around side-effect risk and Blender context availability, but adequate for the intended quick-lookup use case.
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?
The schema already fully documents the only parameter, expression, with a concrete example. The description adds little param-specific meaning beyond confirming the repr return, 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?
States a specific verb and resource: evaluate one Python expression in Blender and return its repr. This clearly distinguishes it from script-execution tools like execute_blender_python.
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?
Describes itself as a quick lookup that does not need a whole script, implicitly guiding the agent to use it for lightweight one-off expressions rather than full Python scripts. It does not explicitly name the alternative or exclusion conditions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.