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blend-ai

by HoldMyBeer-gg
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Python
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set_brush_property

Set the active sculpt brush's size, strength, auto-smooth factor, or frontface property to control Blender sculpting behavior.

Instructions

Set a property on the active sculpt brush.

Args: property: Property to set - size, strength, auto_smooth_factor, or use_frontface. value: Value to set. size is int (1-500), strength is float (0.0-1.0), auto_smooth_factor is float (0.0-1.0), use_frontface is bool.

Returns: Confirmation dict with property name and new value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
propertyYes

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 / property / enum
      Added value: +[
+  "auto_smooth_factor",
+  "size",
+  "strength",
+  "stroke_method",
+  "use_frontface"
+]
  2. First observedv0.1.0

TDQS

B3.4/5.0
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 burden. It helpfully discloses accepted value types and ranges and that a confirmation dict is returned, but it omits the key precondition that a brush must be active and says nothing about persistence or undo behavior for a mutation.

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?

Two-sentence body plus a short Args/Returns block, front-loaded with the action and well organized. Slight redundancy in describing the return value when an output schema already exists, but no wasted prose.

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

Completeness3/5

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

For a two-parameter mutation with no annotations, the description covers value types and the response shape (the latter already encoded in the output schema). It is missing the operational precondition (active brush/sculpt mode) and the stroke_method value, so it is adequate but not complete.

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

Parameters3/5

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

Schema description coverage is 0%, and the description does document both parameters with types and ranges, which is real added value. However, the schema enum lists five properties including 'stroke_method', while the description enumerates only four and gives no type/range for stroke_method, leaving a gap and a misleading enumeration.

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+resource ('Set a property on the active sculpt brush'), which is clearly distinct from the sibling set_sculpt_brush (which picks the brush) and set_annotation_stroke_property. It does not explicitly name those siblings, so it stops short of a 5.

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?

The phrase 'active sculpt brush' implies a precondition (must be in sculpt mode with a brush selected), but the description never states that requirement, nor does it contrast with set_sculpt_brush or explain when to set a property versus switch brushes. Usage is only implied.

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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