Octocode Mannequin

Community

bgauryy

octocode-mannequin

Use when posing, animating, or explaining a 3D human skeleton/manikin: anatomical joints, ROM clamps, walk/run/dance/backflip sequences, Three.js viewer, or agent-driven WebMCP figure control (reach/look_at). Phrases like pose the manikin, skeleton scheme, animate a walk cycle. Not for general 3D scenes, physics/ragdoll, IK foot-locking, or mocap import.

Overview

Publisher	bgauryy
Repository	`octocode`
Skill name	`octocode-mannequin`
Stars	950
Forks	78
Bundled files	13
License	MIT
Links	Skill source Repository Homepage

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.
13 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by bgauryy on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/bgauryy/octocode/tree/main/skills/octocode-mannequin
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.

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/bgauryy/octocode.git /tmp/octocode
mkdir -p .claude/skills
cp -r /tmp/octocode/skills/octocode-mannequin .claude/skills/octocode-mannequin

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Octocode Mannequin 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 Octocode Mannequin 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 Octocode Mannequin 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.

Octocode Mannequin

Anatomically-named 22-bone humanoid rig (arms-down neutral, bilaterally mirrored) plus a movement protocol that clamps every joint to real range of motion, with a root 6-DOF channel (translate/pitch/yaw/roll) for travel, turns, jumps and backflips — a Node CLI, a self-contained Three.js viewer (grounded, smooth Catmull-Rom animation), and WebMCP tools an agent drives live. Flow: SCHEME → COMMAND → CLAMP+FK → RENDER → DRIVE.

Hard rules

scripts/skeleton.mjs is the single source of truth for bones/joints/ROM/movements; references and the viewer mirror it. The viewer re-implements the clamp/sideSign/FK math — any change must be made in BOTH files and re-verified (they must stay identical).
Movement commands use anatomical names valid for that joint, never raw signed degrees and never a movement outside the joint's allowlist — read references/movement-protocol.md before composing one; the CLI and the tools reject those.
Treat ROM values as rig defaults, not medical fact — read references/rom-table.md before quoting a limit.

Gate

Writing a viewer file (viewer --out <file>.html) overwrites that path, and agent-driving needs a fresh non-headless Chrome on a new port: confirm the output path and get the user's OK before the first write or browser launch.

Workflow

Run node scripts/skeleton.mjs scheme first to inspect bones + joint DOF/ROM/movements; for the hierarchy read references/anatomy-scheme.md, for the constraint model read references/joint-constraints.md, and for exact degrees read references/rom-table.md.
Compose a pose command using references/movement-protocol.md, run node scripts/skeleton.mjs pose --cmd '...', read warnings/clamped; then validate an animation by running skeleton.mjs sequence --file frames.json.
To render, run node scripts/skeleton.mjs viewer --out <file>.html [--pose pose.json], open it, drag sliders or call window.applyPose/window.playSequence from the console — ready animations live in assets/ (run-cycle.json, backflip.json, dance.json, idle.json for alive breathing/sway); for the viewer's mechanics read references/viewer-guide.md.
To agent-drive it live, load references/webmcp-agent.md and serve the viewer's WebMCP tools over CDP — 11 tools incl. task-space reach (put a hand/foot at a world point) and look_at; get_scheme.guide is the frame/units contract. Discover, invoke, verify with get_pose or a screenshot.

Stop when: the pose verifies via get_pose or a screenshot; clamped:true shows the joint is already at its ROM limit (that is the answer — do not push past it); a movement is rejected as invalid for the joint (retry with the reported allowlist, never with raw degrees); reach returns reached:false with a residual distance (the target is out of range — re-target, do not re-invoke unchanged); tool discovery returns WEBMCP_NO_TOOLS or fewer than 11 tools (fall back to window.applyPose via Runtime.evaluate); screenshots come back blank (Chrome is headless — relaunch non-headless); or the request needs physics, IK foot-locking, or mocap (out of scope, say so).

When NOT this skill

General 3D scene setup, or physics/ragdoll simulation, IK foot-locking, balance, collision, or mocap (BVH/glTF) import. Motion is keyframed kinematics — a backflip is authored, not simulated; for why that scope was chosen read references/references.md.

Progressive refs

Ref	When
`references/anatomy-scheme.md`	Building/explaining the bone hierarchy
`references/joint-constraints.md`	DOF/constraint model + verified rotation directions per joint
`references/rom-table.md`	Exact degree limits per movement
`references/movement-protocol.md`	Writing/validating a pose command
`references/viewer-guide.md`	Generating/driving the Three.js viewer
`references/webmcp-agent.md`	Agent-driving the manikin via WebMCP + CDP
`references/references.md`	Provenance / why a design choice was made

Scripts

Run node scripts/skeleton.mjs for the scheme / pose / sequence / viewer subcommands (--help); zero npm installs. WebMCP CDP mechanics are delegated to the octocode-chrome-devtools skill.

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 Octocode Mannequin AI skill do?

Why use Octocode Mannequin on TypingMind?

Because you install it once and use it with any model. Octocode Mannequin 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 Octocode Mannequin in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bgauryy/octocode/tree/main/skills/octocode-mannequin. 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 Octocode Mannequin?

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 Octocode Mannequin?

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

Is the Octocode Mannequin AI skill free?

Yes. It is published on GitHub by bgauryy 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Octocode Mannequin

Hard rules

Gate

Workflow

When NOT this skill

Progressive refs

Scripts

Bundled files

Frequently asked questions

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