exercise-designerlisted

## Purpose The exercise-designer skill helps educators create varied, evidence-based practice exercises that target specific learning objectives and apply proven strategies from cognitive science. This skill designs exercises with appropriate difficulty progression, spaced repetition opportunities, and clear assessment criteria. **Constitution v4.0.1 Alignment**: This skill implements evals-first exercise design—defining success criteria BEFORE creating exercises, integrating Section IIb (AI Three Roles Framework) co-learning exercise types, and aligning with Section IIa (4-Layer Method) for layer-appropriate exercises. ## When to Activate Use this skill when: - Educators need practice exercises for Python concepts - Designing homework assignments or problem sets - Creating varied exercise types beyond simple coding problems - Applying evidence-based learning strategies (retrieval practice, spaced repetition) - Establishing difficulty progression across exercise sequences - Generating test cases and rubrics for exercises - Evaluating existing exercises for pedagogical effectiveness ## Inputs Required: - **Learning objectives**: What learners should be able to do - **Concept/topic**: Python concept to practice (e.g., "loops", "dictionaries") Optional: - **Target audience**: beginner | intermediate | advanced - **Number of exercises**: How many to generate - **Exercise types**: Preferred types (fill-in, debug, build-from-scratch, etc.) - **Time