How do I install the Motion Control skill?

Run npx skillmds@latest add baibai2013/motion-control in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Motion Control safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Motion Control?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Motion Control free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Motion Control?

baibai2013 (@baibai2013) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Motion Control by baibai2013 — Agent Skill

Name: Motion Control
Author: baibai2013

Motion Control

Executable robot-dog motion-control MVP for leg IK, gait phase generation, trajectory contracts, controller parameters, and simulation/firmware handoff. Use this skill when the user asks for FK/IK, inverse kinematics, gait generator, trot/walk/bound trajectories, controller parameters, motion-control code, or a trajectory to feed simulation, MuJoCo, or firmware.

baibai2013 20b6915 22 files · 34.6 KB Updated Sep 17, 2026

File contents

motion-control

This skill turns robot-dog kinematics and gait intent into machine-readable motion artifacts. The MVP implements deterministic 2-link sagittal IK and simple phase-based gait trajectories. It is a file-contract layer, not a full MPC/WBC controller.

When To Use

Use this skill for:

Checking whether foot targets are reachable by the leg geometry.
Generating initial trot/walk phase tables and joint trajectories.
Producing trajectory.json and controller_params.yaml for simulation or firmware.
Reporting IK blockers before gait/dynamics validation.

Workflow

Read <project>/motion_plan.yaml.
Solve IK targets against link lengths and joint limits.
Generate a phase-based gait trajectory for the requested gait.
Write reports and handoff files into <project>/reports/ and <project>/control/.

Commands

python skills/motion-control/scripts/solve_ik.py skills/motion-control/examples/quadruped_mvp
python skills/motion-control/scripts/generate_gait.py skills/motion-control/examples/quadruped_mvp

Rules

Keep MVP kinematics deterministic and conservative.
Treat unreachable required foot targets or joint-limit violations as blockers.
Keep output trajectory format compatible with simulation/viewer-style trajectory.json.
Do not claim this replaces full whole-body control, MPC, state estimation, or real-time firmware.
Do not import sibling subskill code. Read files only.

References

references/input-contract.md for motion_plan.yaml fields.
references/ik-model.md for MVP 2-link IK.
references/gait-contract.md for phase and trajectory output.
references/output-contract.md for report fields.
references/examples.md for sample project layout.

---name: motion-controldescription: Executable robot-dog motion-control MVP for leg IK, gait phase generation, trajectory contracts, controller parameters, and simulation/firmware handoff. Use this skill when the user asks for FK/IK, inverse kinematics, gait generator, trot/walk/bound trajectories, controller parameters, motion-control code, or a trajectory to feed simulation, MuJoCo, or firmware.---# motion-controlThis skill turns robot-dog kinematics and gait intent into machine-readablemotion artifacts. The MVP implements deterministic 2-link sagittal IK and simplephase-based gait trajectories. It is a file-contract layer, not a full MPC/WBCcontroller.## When To UseUse this skill for:- Checking whether foot targets are reachable by the leg geometry.- Generating initial trot/walk phase tables and joint trajectories.- Producing `trajectory.json` and `controller_params.yaml` for simulation or firmware.- Reporting IK blockers before gait/dynamics validation.## Workflow1. Read `<project>/motion_plan.yaml`.2. Solve IK targets against link lengths and joint limits.3. Generate a phase-based gait trajectory for the requested gait.4. Write reports and handoff files into `<project>/reports/` and `<project>/control/`.## Commands```bashpython skills/motion-control/scripts/solve_ik.py skills/motion-control/examples/quadruped_mvppython skills/motion-control/scripts/generate_gait.py skills/motion-control/examples/quadruped_mvp```## Rules- Keep MVP kinematics deterministic and conservative.- Treat unreachable required foot targets or joint-limit violations as blockers.- Keep output trajectory format compatible with simulation/viewer-style `trajectory.json`.- Do not claim this replaces full whole-body control, MPC, state estimation, or real-time firmware.- Do not import sibling subskill code. Read files only.## References- `references/input-contract.md` for `motion_plan.yaml` fields.- `references/ik-model.md` for MVP 2-link IK.- `references/gait-contract.md` for phase and trajectory output.- `references/output-contract.md` for report fields.- `references/examples.md` for sample project layout.

Frequently asked questions