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Rigging

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arjun988
rigging

Production rigging in Blender with armatures, IK/FK, constraints, weight painting, mechanical rigs, facial rigs, and drivers. Use before animation on deforming assets via MCP.

Overview

Publisherarjun988
Repositoryblender-skills
Skill namerigging
Stars
384
Forks
22
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by arjun988 on GitHub. Read the source before you install it.

Installation

Install the Rigging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/arjun988/blender-skills/tree/main/.claude/skills/rigging
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/arjun988/blender-skills.git /tmp/blender-skills
mkdir -p .claude/skills
cp -r /tmp/blender-skills/.claude/skills/rigging .claude/skills/rigging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rigging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rigging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rigging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Rigging

Functional rigs supporting intended motion. Clean deformation. Engine-compatible bone hierarchies.

When to Use

  • Character/creature deformation rigs
  • Mechanical constraint rigs
  • Facial expression rigs
  • Prop rigs (doors, vehicles, weapons)
  • Before any animation work

Workflow

Skeleton Design → Bone Placement → Hierarchy → Constraints/IK
    → Weight Painting → Deformation Test → Export Prep

Armature Naming

Prefix: ARM_[AssetName] Bones: [side]_[region]_[name] — e.g., L_arm_upper, spine_01, jaw

Bone Hierarchy

ARM_Character
├── root
├── spine_01 → spine_02 → spine_03
│   ├── L_clavicle → L_arm_upper → L_arm_lower → L_hand
│   └── R_clavicle → R_arm_upper → R_arm_lower → R_hand
├── L_leg_upper → L_leg_lower → L_foot → L_toe
└── R_leg_upper → R_leg_lower → R_foot → R_toe

IK vs FK

Use IKUse FK
Legs (ground contact)Spine (flexible arc)
Arms (hand placement)Shoulder overlap
Feet plantingFinger detail
Mechanical reachWhip/tail motion

Standard: IK legs, FK spine; switchable arms for game characters.

Constraints

ConstraintUse
IKLimb positioning
Copy RotationMechanical sync
Limit RotationJoint ranges
Stretch ToTentacles, pistons
Child OfWeapon attach/detach
ShrinkwrapGround contact (use carefully)

Weight Painting

1. Automatic weights as starting point only
2. Clean weights: normalize per vertex (max 4 influences)
3. Smooth problematic areas (shoulders, hips)
4. Test extreme poses: T-pose, arms up, crouch, jaw open
5. Gradient weights at joints — no hard 1.0/0.0 at bend center

Mechanical Rigs

  • Empty objects as control handles
  • Constraints instead of weight painting
  • Hinge limits match real joint ranges
  • Parent hierarchy mirrors mechanical assembly

Facial Rigs

ApproachUse Case
Bone-basedGame characters
Shape keysCinematics, dialog
HybridHero game characters

Minimum game facial: jaw open, blink L/R, brow up/down.

Drivers

  • Gear rotation sync
  • Auto eyelid blink
  • Weapon reload mechanism
  • Procedural antenna/wire motion

MCP Integration

  1. Create armature via MCP
  2. Parent mesh with automatic weights via MCP
  3. Query bone count and hierarchy
  4. Validate weight groups via MCP if supported
  5. Export armature with mesh via export-pipeline

Deformation Test Poses

  • T-pose / A-pose (bind pose)
  • Arms fully raised
  • Deep crouch
  • Neck rotation extremes
  • Jaw wide open (characters)

Constraints

MUST DO

  • Rig after retopology complete
  • Name bones consistently
  • Limit bone influences to 4 per vertex (game engines)
  • Test deformation at extremes before animation
  • Document control scheme for animators

MUST NOT DO

  • Auto weights without cleanup (hero assets)
  • Scale bones in bind pose
  • Rig before topology validated
  • Skip IK pole targets on limbs
  • Mix multiple root bones without documentation

Reference Guide

TopicReferenceLoad When
Humanoid rigreferences/humanoid-rig.mdCharacters
Mechanical rigreferences/mechanical-rig.mdProps, vehicles

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Rigging AI skill do?

Production rigging in Blender with armatures, IK/FK, constraints, weight painting, mechanical rigs, facial rigs, and drivers. Use before animation on deforming assets via MCP.

Why use Rigging on TypingMind?

Because you install it once and use it with any model. Rigging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rigging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/arjun988/blender-skills/tree/main/.claude/skills/rigging. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Rigging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rigging?

As many as you like. As long as a model supports skills, you can use Rigging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rigging AI skill free?

Yes. It is published on GitHub by arjun988 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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