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SekaiNoOwari77

mcp-3d-modeling-agent

blender_sculpt_mask_by_topology

Create sculpt masks from mesh topology to control which areas are affected by sculpting. Options include cavity, fill, clear, or random masks, with optional blur for smoother edges.

Instructions

Create sculpt masks based on topology features. Masks control which parts of the mesh are affected by sculpting operations. CAVITY masks concave areas, ALL fills the entire mask, NONE clears it, RANDOM creates a random mask pattern. Optional blur smooths mask edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
invertNoInvert the mask after creation (default: false)
mask_typeYesType of mask to create
object_nameYesName of the mesh object
blur_iterationsNoNumber of blur/smooth passes on the mask (default: 0)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the behavioral effect of each mask type and that 'Optional blur smooths mask edges.' However, it does not disclose that creating a mask typically replaces the existing mask on the object, nor any prerequisites such as whether the object must be a mesh or require sculpt mode.

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 compact at roughly three sentences, with the main verb and resource front-loaded in the first sentence and enum semantics following immediately. Every sentence contributes context, though the mask-purpose sentence is explanatory rather than strictly essential.

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?

The description covers purpose and parameter semantics well for a 4-parameter tool with no annotations and no output schema. Gaps remain: it does not indicate the return value, what happens to a pre-existing mask on the object, or any prerequisites beyond the schema's implicit object_name reference.

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 coverage is 100%, so the baseline is 3, but the description adds genuine value: it explains what each mask_type enum value does (CAVITY masks concave areas, ALL fills, NONE clears, RANDOM randomizes) and elaborates blur's effect as smoothing mask edges, going beyond the schema's terse 'Type of mask to create' and 'Number of blur/smooth passes.'

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 and resource: 'Create sculpt masks based on topology features,' with concrete detail on what each mask type does (CAVITY, ALL, NONE, RANDOM). Purpose is unambiguous, but it does not explicitly differentiate from related sculpt sibling tools like blender_sculpt_extract_mask or blender_sculpt_face_set_create.

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 description implies when the tool is useful by explaining that 'Masks control which parts of the mesh are affected by sculpting operations,' giving the agent contextual understanding of the mask concept. However, there is no explicit when-to-use/when-not-to-use guidance or mention of alternatives such as face sets.

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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