Eval Harness

About

The Eval Harness skill provides a formal framework for implementing Eval-Driven Development (EDD) within Claude Code. By treating evaluations as the unit tests of AI development, it allows developers to define success criteria before implementation, track progress using pass@k metrics, and ensure long-term stability via automated regression checks. This skill is essential for transitioning from trial-and-error AI interactions to a measurable, deterministic development process that ensures Claude's outputs meet specific project requirements.

Key Features

• CLI-integrated workflow for defining, checking, and reporting evals
• Standardized evaluation reporting and history logging
• 34,604 GitHub stars
• Multi-modal grading including Code-based, Model-based, and Human review
• Capability and regression evaluation frameworks
• Pass@k and Pass^k reliability metric tracking

Use Cases

• Defining feature success criteria before initiating AI-led code generation
• Quantifying the reliability of AI-generated logic across multiple attempts
• Preventing regressions in legacy codebases during complex refactoring tasks