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delete_object

Remove a named object from a Blender scene to clean up 3D models, animations, or renders. Specify the object name and receive a confirmation.

Instructions

Delete an object from the scene by name.

Args: object_name: Name of the object to delete.

Returns: Confirmation dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.7.0
    • removedInput schema / properties / name
      Removed value: -{
      -  "title": "Name",
      -  "type": "string"
      -}
    • addedInput schema / properties / object_name
      Added value: +{
      +  "title": "Object Name",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "name"
      -]New value: +[
      +  "object_name"
      +]
  2. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It mentions deletion and returning a confirmation dict, but does not disclose critical traits such as whether the deletion is permanent, whether it can be undone, what permissions are required, or any side effects. This is a significant gap for a destructive operation.

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

Conciseness4/5

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

The description is short and front-loaded with the main action, followed by structured Args and Returns sections. It is efficient, though the Args section adds little beyond the obvious, and the Returns section is brief but appropriate given the output schema exists.

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

Completeness2/5

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

For a simple deletion tool with no annotations and a single undocumented parameter, the description is incomplete. It omits behavioral details (reversibility, permissions, side effects) that are essential for safe invocation, and the parameter lacks any format guidance. The presence of an output schema only means return values need not be explained.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only restates the parameter name ('Name of the object to delete') without adding format details, case sensitivity, or constraints. This minimal clarification does little beyond the schema's title.

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

Purpose4/5

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

The description states a specific verb (delete) and resource (object) with scope (from the scene by name). It clearly identifies what the tool does, but does not explicitly differentiate itself from sibling delete operations (e.g., delete_material, delete_light) in the text. The resource name alone carries the differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It merely states what the tool does, leaving the agent to infer context from the tool name and 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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