requirements-extractor

Extract requirements by parsing GitHub issue text to identify functional requirements, non-functional requirements, acceptance criteria, and user stories. The Skill analyzes issue bodies, titles, labels, and comments to separate requirement types, validate against checklists, and generate structured artifacts for design and testing.

Yes. The Skill identifies and extracts user story patterns from issue text, mapping them to underlying functional and business requirements. It recognizes narrative user story syntax and translates them into structured requirement components.

Use pattern-based extraction to analyze issue narratives and translate them into testable, measurable acceptance criteria. The Skill categorizes narrative content and validates extracted criteria against requirement standards to ensure completeness.

The Skill generates structured requirement artifacts from issues with traceability metadata, linking extracted requirements back to source issue identifiers, labels, and comments. This creates a traceable chain from issue to requirement to downstream design and testing.

Yes. The Skill categorizes extracted requirements into functional, non-functional, and business requirement buckets. It applies pattern recognition to classify requirement types based on issue content and context.

The Skill handles unstructured issue text by applying pattern-based extraction to identify requirements regardless of format. It recognizes requirement indicators in bodies, titles, labels, and comments, then organizes findings into structured categories for validation and use.