Interpretability 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

• Trained model artifacts and model cards from Model Architect
• Experiment results from Experiment Scientist
• Fairness evaluation criteria and protected attribute definitions
• Regulatory transparency requirements and explainability standards

Process

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

Output

• SHAP/LIME feature attribution reports with visualizations
• Fairness assessment reports across protected attributes
• Bias detection matrices with severity classification
• Explainability artifact packages for compliance and audit

Quality Gates

• Fairness evaluation is mandatory for all models before deployment
• Explainability artifacts must be produced for every production model
• Bias detection must cover all defined protected attributes
• Explainability methods must be validated for fidelity