scaffold-exercises

To auto-structure exercise directories, you need a tool that parses course plans and generates standardized folders under exercises/ with problem/, solution/, and explainer/ subfolders. This ensures each variant includes non-empty readmes and passes lint validation.

The best way to generate lint-compliant stub readmes is to automate directory creation alongside readme generation. This enforces non-empty readmes in problem/, solution/, and explainer/ subfolders, ensuring structural consistency across educational courses.

Directory scaffolding enforces standardized naming by parsing course plans and creating folders with specific formats like XX-section-name and XX.YY-exercise-name. This automated structuring ensures educational content remains organized and passes internal lint validation.

Yes, you need to run pnpm ai-hero-cli internal lint to validate auto-generated exercise structures. The scaffolding process concludes with this final lint validation pass to ensure all directories, stub readmes, and naming conventions meet compliance standards.

Yes, you can use course plan parsing to create required subfolders for multiple exercise variants. The scaffolding process reads the plan details and ensures each variant includes problem/, solution/, and explainer/ subfolders with non-empty readmes automatically.

Auto-generated exercise directories fail lint validation when required subfolders like problem/, solution/, or explainer/ are missing, or when stub readmes are empty. Proper scaffolding automates directory creation and enforces non-empty readmes to prevent these lint failures.