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blend-ai

by HoldMyBeer-gg
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Python
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recalculate_normals

Fix flipped or inconsistent mesh face normals to remove shading artifacts. Recalculate them outward or inward for an entire object or current selection.

Instructions

Recalculate face normals to be consistent (all pointing outward or inward).

Fixes meshes with flipped or inconsistent normals that cause shading artifacts.

Args: object_name: Name of the mesh object. inside: If True, normals point inward instead of outward.

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
insideNo
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

A4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It discloses that the tool mutates mesh normal data and returns a confirmation dict, but says nothing about reversibility/undo, mode requirements, or failure behavior on non-mesh objects.

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 one-line purpose followed by a problem statement and a structured Args/Returns block. Slightly padded by the Returns stub ('Confirmation dict'), but every other line earns its place.

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?

An output schema exists, so the thin Returns note is acceptable. With 3 parameters, one enum, and no annotations, the description covers purpose, all parameters, and the selection workflow; only mutation-safety details are missing.

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

Parameters5/5

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: object_name is identified as the mesh object, inside is explained as direction of the normals, and selection enumerates ALL vs CURRENT with its default and the workflow needed to use CURRENT. This meaningfully exceeds the bare schema.

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 ('recalculate face normals') and the outcome it produces ('consistent, all outward or inward'), plus the problem it solves (flipped/inconsistent normals causing shading artifacts). It does not explicitly distinguish itself from the sibling flip_normals, which is the closest alternative, so it falls 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 Guidelines4/5

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

Gives concrete operational context: use select_* tools to establish a selection before calling with selection='CURRENT'. It does not state when NOT to use it (e.g., versus flip_normals) or prerequisites like object/edit mode, so it is clear but not exhaustive.

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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