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blend-ai

by HoldMyBeer-gg
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Python
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subdivide_mesh

Add edge cuts to a Blender mesh by specifying the object name, cut count, and whether to affect all or only selected geometry.

Instructions

Subdivide a mesh.

Args: object_name: Name of the mesh object to subdivide. cuts: Number of cuts per edge. Range: 1-100.

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
cutsNo
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. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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 says only 'Returns: Confirmation dict' — it does not disclose that subdivision rewrites mesh topology, whether the change is applied directly or as a modifier, undoability, or any performance cost at high cut counts. Most of what it states (cuts default 1, selection default ALL) merely repeats schema defaults.

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?

Front-loaded one-line summary followed by arg docs and a returns note. No filler sentences; every line contributes parameter or return information.

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?

With an output schema present, return values need not be detailed, and all three parameters are covered in prose. The remaining gap is precondition/behavioral context (edit mode, effect on topology) for a mutating mesh tool with no annotations.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it names all three parameters, adds a range constraint for cuts (1-100) that the schema lacks, and explains the ALL/CURRENT enum semantics plus the default. Only object_name gets no added meaning beyond its name.

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 ('Subdivide a mesh') that an agent can distinguish from siblings such as subdivide_curve, remesh, or loop_cut on the resource noun alone. It stops short of explicitly naming an alternative, but the purpose is unambiguous.

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?

Gives real operational guidance for the 'selection' argument: use select_* tools first, ALL vs CURRENT, default ALL. It never says when to prefer subdivision over remesh/loop_cut or what preconditions (active object, edit mode) apply, so context is implied rather than stated.

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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