lesson-structure_skill

Overview

This skill generates lesson markdown templates tailored for the AI-Native Robotics Textbook, ensuring each lesson follows the platform's required structure and pedagogical layering. It produces ready-to-use lesson metadata and sections so authors can focus on content, not formatting. Every output enforces the mandatory sections and concludes with a "Try With AI" extension for applied, AI-guided exploration.

How this skill works

Given a lesson topic and target layer, the skill emits a complete lesson scaffold in markdown with YAML metadata, required sections, and suggested content prompts. It validates that the template includes Learning Objectives, Prerequisites, Main Content, Hands-On Exercise, Reflection Questions, and the final Try With AI section. The skill can also assign an appropriate pedagogical layer (L1–L5) and recommend duration ranges.

When to use it

• Drafting new lessons for the AI-Native Robotics Textbook
• Converting lecture notes into a standardized lesson format
• Validating that a lesson includes all required sections
• Preparing curriculum packages with consistent metadata
• Creating practice and assessment prompts for hands-on labs

Best practices

• Start with clear, measurable learning objectives tied to robotic competencies
• Set prerequisites narrowly to avoid blocking motivated learners
• Design hands-on exercises that map directly to objectives and include success criteria
• Keep main content modular: concept, demonstration, and code/command snippets
• Use the Try With AI section to scaffold AI-guided experiments and prompt examples

Example use cases

• Produce a L2 lesson on sensor integration with YAML metadata and exercises
• Validate an existing lesson draft and add a missing Reflection Questions section
• Generate a 60-minute lesson scaffold for humanoid gait basics with hands-on tasks
• Create AI-assisted extension prompts for model-based control experiments
• Standardize a sequence of lessons into a cohesive module with consistent layers