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blend-ai

by HoldMyBeer-gg
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Python
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spin_mesh

Create round 3D shapes like vases, columns, or wheels by spinning mesh geometry around an axis and center point in Blender.

Instructions

Spin (lathe) mesh geometry around an axis.

Creates rotational geometry by duplicating and rotating the selected geometry around a center point. Great for creating round shapes like vases, columns, or wheels.

Args: object_name: Name of the mesh object. angle: Total spin angle in radians. Range: -6.283 to 6.283 (full circle). steps: Number of steps in the spin. Range: 1-1000. axis: Spin axis as XYZ vector. Defaults to Z-up (0, 0, 1). center: Center point for the spin as XYZ. Defaults to origin.

selection: "ALL" to act on the whole mesh, or "CURRENT" to act only
    on what is already selected. Use the select_* tools to choose
    first. Defaults to "ALL".

Returns: Confirmation dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
axisNo
angleNo
stepsNo
centerNo
selectionNoALL
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.7.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / selection
      Added value: +{
+  "default": "ALL",
+  "enum": [
+    "ALL",
+    "CURRENT"
+  ],
+  "title": "Selection",
+  "type": "string"
+}
  2. Addedv1.2.2

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the core mechanics (the mesh is duplicated and rotated) and the meaning/default of every parameter, but says nothing about whether the original geometry is consumed or preserved, whether the operation is destructive/reversible, or whether permissions are needed.

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?

Front-loads the one-line purpose before the examples and the structured Args block. The content is well organized and mostly earns its place, though the example sentence and the per-arg prose run slightly long for a single mesh operation.

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?

An output schema exists, so the terse 'Returns: Confirmation dict' is acceptable and return values need not be detailed. For a mutation tool with zero annotations and zero schema coverage, the description covers mechanics and all parameters well; the notable gap is destructive-ness/reversibility of the source geometry.

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

Parameters5/5

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, and it does: it documents all six parameters with units (radians), ranges (-6.283 to 6.283, 1-1000), defaults (Z-up axis, origin center, ALL selection), and the ALL vs CURRENT semantics. This adds substantial meaning the bare schema does not carry.

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?

States a specific verb and resource ('spin (lathe) mesh geometry around an axis') and expands it with a concrete mechanic ('duplicating and rotating the selected geometry around a center point') plus example outputs (vases, columns, wheels). It does not, however, differentiate itself from nearby generative siblings like sweep_profile_along_path or create_polygon_prism.

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

Usage Guidelines4/5

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

Gives a clear usage context (round shapes such as vases, columns, wheels) and an actionable prerequisite for one mode: use the select_* tools first when selection is 'CURRENT'. It stops short of saying when to prefer this over alternatives such as sweep_profile_along_path, and lists no exclusions.

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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