Build evaluation harnesses for AI-assisted implementations — capability evals, regression tests, graders (exact-match, LLM-judge, code-exec, rubric), and standardized metrics (pass@k, accuracy, latency, cost). Use when the user wants to set up or run evals, benchmark agents/skills, create regression test suites for prompts or AI features, compare model/prompt variants, or measure implementation quality. Triggers on "set up evals", "create eval harness", "benchmark this skill", "regression test the prompt", "run evals", "/eval-harness", or any request to systematically measure AI output quality.
$npx -y skills add mhylle/claude-skills-collection --skill eval-harnessInstalls into the current project.
Run `npx skills use "https://github.com/mhylle/claude-skills-collection" --skill "mhylle/claude-skills-collection/eval-harness"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mhylle/claude-skills-collection" that are relevant to the current task. Run `npx skills add "https://github.com/mhylle/claude-skills-collection"` and select the relevant skills, then follow their instructions.