Claude-skill-registry exercise-patterns
Structure for creating hands-on exercises in the Physical AI textbook.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/exercise-patterns" ~/.claude/skills/majiayu000-claude-skill-registry-exercise-patterns && rm -rf "$T"
manifest:
skills/data/exercise-patterns/SKILL.mdsource content
Exercise Template (Strict Format)
## Exercise X.Y: [Title] **Difficulty**: [Beginner | Intermediate | Advanced] **Time**: [15 min | 30 min | 1 hour | 2 hours] **Hardware**: [Workstation | Jetson + RealSense | Unitree Robot] ### Objectives By completing this exercise, you will: - [Action verb] [specific skill] (e.g., "Create a ROS 2 publisher node") - [Action verb] [specific skill] (e.g., "Visualize sensor data in RViz2") - [Action verb] [specific skill] (e.g., "Deploy code to Jetson Orin Nano") ### Prerequisites - Chapter X completed - ROS 2 Humble installed - [Specific hardware setup, e.g., "RealSense D435i connected"] ### Instructions #### Step 1: [Action] ```bash # Command to run ros2 pkg create my_package --build-type ament_python
Expected Output:
Successfully created package 'my_package'
Step 2: [Action]
[Detailed instructions with code snippets]
Step 3: [Verification]
Run this command to verify:
ros2 topic list
Expected: You should see
/my_topic in the list.
Validation Checklist
- Code compiles without errors (
)colcon build - Node runs and publishes data (
)ros2 topic echo /my_topic - RViz2 displays data correctly
Challenge (Optional)
[Extended task for advanced students, e.g., "Modify the node to publish at 100 Hz instead of 10 Hz"]
Troubleshooting
Problem: "Package not found" Solution: Source your workspace (
source install/setup.bash)
Problem: "Topic not visible" Solution: Check if node is running (
ros2 node list)
## Exercise Types ### 1. Thought Experiment (No Code) **Format**: Conceptual questions to build intuition **Example**: "List 5 tasks that require physical embodiment that an LLM alone cannot do" ### 2. Simulation Task (Gazebo/Isaac Sim) **Format**: Code + Launch files + Gazebo world **Example**: "Spawn a humanoid in Gazebo and make it walk forward 2 meters" ### 3. Hardware Integration (Jetson + Sensors) **Format**: Deploy ROS 2 node to Jetson, read sensor data **Example**: "Stream RealSense depth images to your workstation via Wi-Fi" ### 4. Capstone Project (Multi-Week) **Format**: Complete system with milestones **Example**: "Build an autonomous room-cleaning robot" ## Progressive Difficulty Curve **Beginner** (Chapters 1-5): - Copy-paste code examples - Run pre-built packages - Simple parameter changes **Intermediate** (Chapters 6-15): - Modify existing code - Create new nodes - Integrate multiple sensors **Advanced** (Chapters 16-28): - Design complete systems - Optimize for hardware (Jetson) - Implement novel algorithms - Deploy to real robots ## Validation Standards Every exercise must have: 1. **Clear Success Criteria** - "You should see X" or "The robot should do Y" 2. **Runnable Code** - Copy-paste should work without modification 3. **Hardware Note** - Explicitly state if Jetson/Robot required 4. **Time Estimate** - Realistic completion time for average student