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blend-ai

by HoldMyBeer-gg
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Python
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quads_to_tris

Convert quad faces to triangles to prepare meshes for game engine export or any workflow requiring triangulated geometry. Applies to entire mesh or current selection.

Instructions

Convert all quad faces to triangles.

Useful for game engine export or when triangulated geometry is required.

Args: object_name: Name of the mesh object.

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
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

A4.4/5.0
Behavior4/5

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

No annotations exist, and the description carries the full burden competently: it discloses that it is a mesh mutation, states selection scope, and confirms the return is a confirmation dict. It does not state whether the operation is destructive/irreversible or whether existing triangles on the mesh are preserved, which is a notable gap for a topology-mutating tool.

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-loaded with the core action, then rationale, then arg docs. Every sentence earns its place. The Args/Returns block repeats the default already in the schema, a minor redundancy.

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

Completeness5/5

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

For a two-parameter mesh conversion tool with an existing output schema and no annotations, the description covers purpose, motivation, parameter semantics, and return type. Nothing an agent needs to invoke it correctly is missing.

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 0%, so the description must compensate. It documents both params: object_name's meaning and the semantics of the selection enum ('ALL' vs 'CURRENT'), plus its default. This is genuine added value, though it doesn't add syntax/format details beyond that.

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?

States a specific verb (Convert) and resource (quad faces to triangles), and directly names the inverse sibling tris_to_quads. An agent can tell this apart from the rest of the mesh-editing tools without opening the schema.

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?

Provides a clear reason to use it ('For game engine export or when triangulated geometry is required') and explains the selection.CURRENT workflow with a pointer to the select_* tools. It lacks an explicit 'when not to use' or a direct contrast with tris_to_quads, so it stops short of a 5.

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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