mujoco-simulationlisted

# mujoco-simulation This skill defines and evaluates MuJoCo-style dynamics scenarios for robot-dog virtual prototypes. The MVP uses deterministic scenario metadata so tests and digital-twin gates can run without a local MuJoCo install. It establishes the file contract that later real `mujoco` runners will fill with solver output. ## When To Use Use this skill for: - MJCF/MuJoCo scenario planning and validation. - Stand, flat-walk, slope, step-obstacle, drop, and push-disturbance checks. - Contact/friction, foot slip, body roll/pitch, torque margin, and fall checks. - Generating `mujoco_result.json` for `robot-dog-digital-twin` gates. ## Workflow 1. Read `<project>/mujoco_scenarios.yaml`. 2. Evaluate each scenario against stability, posture, contact, torque, slip, and energy limits. 3. Write per-scenario `*.sim_result.json` plus a project-level `mujoco_result.json`. 4. Mark blockers when any required scenario falls, exceeds posture/contact limits, or violates torque/slip thresholds. ## Commands ```bash python skills/mujoco-simulation/scripts/run_scenarios.py skills/mujoco-simulation/examples/quadruped_mvp python skills/mujoco-simulation/scripts/summarize_results.py skills/mujoco-simulation/examples/quadruped_mvp ``` ## Rules - Keep the MVP deterministic and conservative. - Do not claim metadata-mode results are real MuJoCo solver output. - Use PyBullet `simulation` for lightweight CI smoke; use this skill for MuJoCo/MJCF contracts and higher-fidelity scenario gates.