| name | motion-pipeline |
| promoted_to | game-pipeline |
| user-invocable | true |
| description | CPU-only motion data processing pipeline for game animation: BVH import, contact detection, root decomposition, motion blending, FABRIK IK. No GPU required. |
| allowed-tools | ["Read","Bash","Write","Edit","Glob","Grep"] |
| routing | {"triggers":["mocap","motion data","animation pipeline","BVH import","contact detection","IK solve","motion blend","bone trajectory","root extraction","FABRIK","skeletal animation data"],"category":"game-animation","pairs_with":["game-sprite-pipeline","phaser-gamedev"],"agents":["rive-skeletal-animator","pixijs-combat-renderer","game-asset-generator"]} |
Motion Pipeline Skill
CPU-only motion data processing pipeline for game animation, inspired by Meta's
ai4animationpy framework (CC BY-NC 4.0). All operations run on numpy and scipy
with no GPU or PyTorch required.
Why standalone implementations?
ai4animationpy's Math/Tensor.py imports torch unconditionally at the top
level, which propagates through every module (Animation, Import, IK, Math).
This means zero ai4animationpy modules are importable without PyTorch installed.
The standalone implementations in scripts/motion-pipeline.py replicate the
key algorithms from their source code using only numpy + scipy.
Environment setup
python3 -m venv /home/feedgen/vexjoy-agent/motion-pipeline-env/
motion-pipeline-env/bin/pip install numpy scipy pygltflib Pillow
motion-pipeline-env/bin/python -c "import numpy; import scipy; import pygltflib; print('OK')"
The venv is gitignored. The skill documents setup; it does not commit the venv.
Commands
All commands output JSON to stdout. Errors go to stderr with exit code 1.
import-bvh
Parse a BVH mocap file and print a motion summary.
motion-pipeline-env/bin/python scripts/motion-pipeline.py import-bvh FILE \
[--scale 0.01]
Output fields: name, num_frames, num_joints, framerate,
total_time_seconds, bones[], root_trajectory (x/y/z range).
extract-contacts
Detect ground contact frames per bone (foot, hand) using height + velocity
thresholds. Replicates ContactModule.GetContacts() from ai4animationpy.
motion-pipeline-env/bin/python scripts/motion-pipeline.py extract-contacts FILE \
--bones LeftFoot RightFoot \
--height 0.1 \
--vel 0.5
Output: { "bones": { "<name>": { "contact_frames": [...] } }, "total_frames": N }.
decompose
Split motion into root trajectory (WHERE + HOW) and per-joint local Euler
angles (POSE). Implements the RootModule / MotionModule decomposition pattern.
motion-pipeline-env/bin/python scripts/motion-pipeline.py decompose FILE \
--hip Hips
Output: root_trajectory.positions[], root_trajectory.velocities[],
root_trajectory.facing_directions[], per_joint_euler_zyx_degrees{}.
First 5 frames shown in stdout; full data requires piping to a file.
blend
Blend two BVH clips at a fixed alpha using SLERP rotations and LERP positions.
Clips must share the same bone hierarchy.
motion-pipeline-env/bin/python scripts/motion-pipeline.py blend FILE_A FILE_B \
--alpha 0.5
Output: summary of the blended motion.
solve-ik
Run FABRIK inverse kinematics on a bone chain at a single frame.
motion-pipeline-env/bin/python scripts/motion-pipeline.py solve-ik FILE \
--chain Hips:LeftFoot \
--target 0.2,0.05,0.3 \
--frame 10
Output: chain[], target[], initial_positions[], solved_positions[],
end_effector_error (metres).
generate-move-ts
Convert a BVH mocap file into a TypeScript MoveFrame function compatible with
road-to-aew's wrestlingMoves.ts interface. Outputs keyframe-interpolated
TypeScript to stdout (and optionally a file).
motion-pipeline-env/bin/python scripts/generate-move-ts.py BVH MOVE_NAME \
[--scale 0.01] \
[--contact-bones LeftToeBase RightToeBase LeftHand RightHand] \
[--num-keyframes 12] \
[--hip-bone Hips] \
[--output path/to/output.ts]
| Argument | Default | Purpose |
|---|
BVH | — | Path to .bvh mocap file |
MOVE_NAME | — | Kebab-case name (e.g. roundhouse-kick) used in TS identifiers |
--scale | 0.01 | Position scale; 0.01 converts cm→m for CMU/Mixamo files |
--contact-bones | LeftToeBase RightToeBase LeftHand RightHand | Bones used to detect the impact window |
--num-keyframes | 12 | Keyframe count in the output array (min 2) |
--hip-bone | Hips | Root bone name for trajectory extraction |
--output | stdout only | Write TS to this file path in addition to stdout |
Implementation note: The script imports motion-pipeline.py as a module
via importlib rather than calling it as a subprocess. This bypasses the 5-frame
truncation applied by the decompose CLI command, giving access to all frames.
Output structure:
const ROUNDHOUSE_KICK_KEYFRAMES = [...] as const;
export function getRoundhouseKick(progress: number): MoveFrame {
return { attacker, defender, isImpact };
}
The attacker's offsetX/Y/Z are root trajectory positions normalized to
start at origin. Rotations are in radians (converted from the BVH's Euler
ZYX degrees). The defender reaction is computed procedurally: pushed backward
at impact, eases to mat post-impact.
Impact detection: The script finds the first run of 3+ consecutive contact
frames across the specified bones. For strike moves, this captures the moment
of hit. For walking/idle clips (feet always down), the window will be frame-0
and isImpact will be nearly never true — this is correct behavior.
Validation: The script prints a summary to stderr including trajectory
range, impact window, and a structural syntax check. Exit code 1 if validation
fails.
Data architecture pattern
The decomposition from ai4animationpy becomes a design contract for all
game animation work:
Animation State
root_trajectory -- WHERE (position, velocity, facing direction)
per_joint_euler -- HOW (local pose in ZYX Euler degrees)
contact_frames -- WHAT (contact states for feet, hands)
[guidance] -- WHY (intent; handled at game engine layer)
This separation enables:
- Different movement speeds without distorting body pose
- Contact-driven game events (damage triggers, sound, VFX)
- AI/input guidance independent of motion playback
Source reference: ai4animationpy modules adopted
| ai4animationpy module | This script equivalent | Notes |
|---|
Import/BVHImporter.BVH | load_bvh() | Same parsing logic; scipy replaces torch |
Animation/Motion | Motion dataclass | numpy-only; no torch backend |
Animation/ContactModule | extract_contacts() | Height + velocity criterion identical |
Animation/RootModule | decompose() root section | FK decomposition via matrix inverse |
Animation/MotionModule | decompose() joint section | Local Euler extraction via scipy |
IK/FABRIK | solve_ik_fabrik() | Algorithm identical; no Actor dependency |
Integration points
| Downstream agent | Data consumed |
|---|
rive-skeletal-animator | per_joint_euler_zyx_degrees from decompose |
pixijs-combat-renderer | contact_frames from extract-contacts |
combat-effects-upgrade | contact_frames (impact timing) |
game-asset-generator | Produces source BVH files for this pipeline |
Sample BVH for testing
A walking cycle from ai4animationpy demos is available at:
/tmp/ai4animationpy/Demos/BVHLoading/WalkingStickLeft_BR.bvh
This is a full-body biped walking clip from the Geno character rig.
Reference: ai4animationpy
- Source:
/tmp/ai4animationpy (cloned locally)
- License: CC BY-NC 4.0 (non-commercial; aligned with hobby game projects)
- GitHub: https://github.com/facebookresearch/ai4animationpy
- Key finding: ALL modules require torch at import time via
Math/Tensor.py line 5.
No conditional import path exists. Standalone implementations are the correct approach.