scaffold-exercises

Scaffolding exercise directory structures that pass lint requires generating consistent folders for sections, problems, solutions, and explainers, then validating them with pnpm ai-hero-cli internal lint to ensure non-empty readmes and correct naming.

Creating stub readmes for course modules involves automatically generating non-empty readme.md files within each exercise subfolder, ensuring the directory structure remains consistent and lint-ready for bootcamps or practice sets.

Yes, you can use pnpm ai-hero-cli internal lint to validate scaffolded exercise folders, ensuring the generated directory structures, naming conventions, and non-empty readme files meet required linting standards before committing.

Planning and generating skeletons for course sections requires parsing a course plan to automatically create exercise directories with problem, solution, and explainer stubs, providing a lint-ready workflow for rapid module generation.

Exercise folder structures fail lint checks when subfolders lack non-empty readme.md files or use inconsistent naming conventions, requiring automated scaffolding to generate lint-ready directories that pass pnpm ai-hero-cli validation.

Yes, scaffold-exercises supports generating optional variant scaffolds for testing, automatically creating exercise directory structures with consistent naming and non-empty readmes that pass pnpm ai-hero-cli internal lint.