AI4Nieup Skill Creation Guide

To standardize AI skill creation, define competency units using a schema capturing name, tagline, description, category, keywords, dependencies, and components. This ensures each learning skill follows a unified structure.

Documenting AI competencies requires a standard metadata schema including name, tagline, description, category, keywords, dependencies, and components. This schema enables automated validation and toxicity rule checks.

To structure a new skill unit, create a root SKILL.md file with YAML frontmatter specifying the name and description. Populate the Markdown body with structured instructions and optional scripts, references, and assets.

Yes, you can use the Prisma client dependency to manage seed data and database interactions. The skill creation guide provides templates for concept metadata and seed data to accelerate authoring.

Standardized metadata schemas require strict adherence to predefined fields and toxicity validation rules. Skills must be self-contained within scripts, references, and assets directories to pass automated checks.

AI competency units fail validation when content violates established toxicity rules or lacks required schema fields. Ensure all metadata fields are populated and content passes safety checks before submission.