human-eval-design

What problem does it solve?

Use this skill when you need to design robust human evaluation processes to benchmark AI outputs, establish ground-truth references, and define reliable quality metrics.

Core Features & Use Cases

• Annotation guidelines and criteria design to ensure consistent human judgments
• Rubric development with reliability-focused calibration and disagreement resolution
• End-to-end evaluation workflow covering data collection, annotation, analysis, and reporting
• Real-world use cases: calibrating model outputs, auditing AI safety, and validating improvements with human insights

Quick Start

Provide a complete human evaluation plan including annotation guidelines, rubric design, and calibration examples.