eval-harness

Regression tests for Claude Code sessions are set up using a formal evaluation framework that enforces explicit eval types. This enforces explicit eval types to ensure model improvements do not break existing behavior across versions.

Eval-driven development is a workflow that standardizes AI coding evaluation through capability and regression checks. It defines graders, metrics, and an end-to-end workflow from defining evals to generating evaluation reports that inform releases.

Standardized grading across model versions and prompts is achieved by applying structured grader templates within an evaluation framework. These templates include code-based, model-based, and human graders to provide flexible evaluation strategies.

Yes, you can run a minimal eval suite to validate a Claude Code change end-to-end. The framework provides a complete workflow from defining evals and implementing changes to generating evaluation reports.

Yes, the eval framework supports human graders alongside model-based and code-based checks. These grader templates are integrated to provide flexible evaluation strategies for Claude Code sessions.

The best way to convert subjective coding assessments into metric-driven checks is by implementing a formal eval framework. It streamlines evaluation by defining explicit eval types, metrics, and graders for Claude Code sessions.