NanoCube Analyst — Refactor Workflow

Description: Improve existing artifact structure and quality

When to Use

Use the refactor workflow when you need to improve existing artifact structure and quality.

Input Requirements

• Persona registry data with dimension profiles
• Hierarchical data structures and cube definitions
• Analysis requirements and hypothesis specifications
• Statistical methodology standards and significance thresholds

Process

1. Initialize — Set up the refactor context for NanoCube Analyst
2. Execute — Perform the refactor operation following NanoCube Analyst's style
3. Validate — Check output against quality gates
4. Handoff — Deliver results to downstream personas

Output

• Query specifications for hierarchical persona data
• Statistical analysis reports with significance testing
• Data quality assessment reports for persona dimensions
• Aggregation pipeline definitions with performance metrics

Quality Gates

• All statistical claims must include confidence intervals
• No aggregation without documenting dimensional granularity
• Content-addressed indexes must be validated against source data
• Analysis notebooks must be fully reproducible
• No correlation claims without controlling for confounders