prompt-creation

To create standardized context prompts, use template-driven markdown bodies with frontmatter metadata to enforce structure and schema validation, ensuring consistent AI guidance and governance across projects.

Frontmatter schema validation for AI prompts is a mechanism that enforces required metadata fields within markdown files, ensuring template-driven prompt bodies remain structured, predictable, and reusable across technology-stack configurations.

Yes, you can use markdown templates for both project configuration and assistant personas. The template approach supports technology-stack prompts with versions and policies alongside behavioral prompts defining assistant rules.

The best way to enforce structure and governance for AI assistant rules is applying frontmatter metadata combined with template-driven markdown bodies and schema validation, producing reusable and predictable behavioral prompts.

You validate prompt files by creating markdown using the prompt template and running schema validation against the embedded frontmatter metadata, ensuring the context gathering and template reuse meet standardized governance requirements.