eval-harness

Implement evaluation-driven development workflows for Claude Code sessions.

Updated Feb 11, 2026
One-click install
npx skills add https://github.com/shygoly/sapbase --skill eval-harness-shygoly
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: eval-harness
Source: https://github.com/shygoly/sapbase/tree/main/docs/zh-CN/skills/eval-harness
Command: npx skills add https://github.com/shygoly/sapbase --skill eval-harness-shygoly

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a formal evaluation framework for Claude Code sessions, implementing evaluation-driven development (EDD) principles to treat evaluation as the unit test for AI development, ensuring early success criteria, continual checks, and traceable changes.

Core Features & Use Cases

  • Capability Evaluation: define and validate new capabilities before coding.
  • Regression Evaluation: guard existing functionality against changes.
  • Multi-Grader support: code-based, model-based, and human scoring with pass@k tracking.
  • Workflow Integration: define, implement, evaluate, and report within a structured repo.

Quick Start

Define your evaluation plan, implement the evaluators, run tests, and review results.

Frequently Asked Questions about eval-harness

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is evaluation-driven development for AI coding sessions?

Evaluation-driven development (EDD) treats evaluation as the unit test for AI development, ensuring early success criteria, continual checks, and traceable changes within Claude Code sessions.

How do I set up capability and regression evaluations for Claude Code?

Define an evaluation plan to validate new capabilities or guard existing functionality, implement code-based, model-based, or human graders, and store them in a structured repo under .claude/evals.

Does this evaluation framework support pass@k metrics?

Yes, the framework supports pass@k metrics alongside multiple grading methods including code-based, model-based, and human scoring to track evaluation success rates accurately.

What's the best way to structure an AI evaluation repository?

Use a structured repo layout under .claude/evals with clear guidelines for planning, running, and reviewing assessments to maintain evaluation baselines and track capability regressions.

Can I use multiple graders for AI regression testing?

Yes, you can apply code-based, model-based, and human scoring graders simultaneously within the evaluation workflow to comprehensively assess regression and capability test results.

When do I need formal capability evaluation in my development workflow?

You need formal capability evaluation when defining and validating new AI capabilities before coding, ensuring early success criteria are met and existing functionality is guarded against regressions.