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subdivide_faces

Split picked faces into a grid with a chosen number of cuts per edge, keeping the shape for bending, sculpting, or displacing the new geometry.

Instructions

Split the picked faces into a grid; cuts is the number of cuts per edge. The shape stays: it gives geometry to bend, sculpt or displace. Use subdivide to round the whole mesh, remesh for an even skin over merged parts. where picks faces (or vertices, edges) by a condition, all given keys must hold: normal ('+Z', '-X' or [x,y,z]) with angle (degrees, default 25); x, y, z ranges [min, max] (null means open) on the world centre; box [[x0,y0,z0],[x1,y1,z1]]; area [min, max]; index [...]. {} or null picks everything. Look at mesh_info first to see where the faces are.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cutsNo
whereNo
objectYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose useful behavior: it says the operation preserves the overall shape and creates geometry useful for bending, sculpting, or displacing. However, it does not mention mutation side effects, reversibility, required permissions, or return behavior, leaving some behavioral gaps for a mesh-editing 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 core operation is front-loaded in the first sentence, followed by alternatives and then necessary `where` details. The description is long but dense and mostly free of repetition, though the multi-key `where` explanation could be more tightly formatted.

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?

Given no annotations, no output schema, and 0% schema description coverage, the description is fairly complete for usage and the `where` parameter. It still omits the required `object` parameter and any return or side-effect information, so it is not fully complete for safe invocation.

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 coverage is 0%, so the description must compensate. It thoroughly explains `cuts` and gives extensive semantics for `where`, including normal, angle, coordinate ranges, box, area, and index filters. But it never explains the required `object` parameter, so the description only partially compensates for the missing schema documentation.

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

Purpose5/5

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

The description states a specific verb and resource: 'Split the picked faces into a grid,' with `cuts` clarified as the number of cuts per edge. It explicitly distinguishes itself from sibling tools by naming `subdivide` and `remesh` and the conditions that select them.

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

Usage Guidelines5/5

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

It gives clear alternatives: use `subdivide` to round the whole mesh and `remesh` for an even skin over merged parts. It also provides a prerequisite workflow hint: 'Look at mesh_info first to see where the faces are,' and explains that `where` controls face selection, so an agent knows when and how to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.