Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
How to install agentic-eval?
christophacham/agent-skills-library/agentic-eval
$npx -y skills add christophacham/agent-skills-library --skill agentic-evalInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/christophacham/agent-skills-library" --skill "christophacham/agent-skills-library/agentic-eval"` 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/christophacham/agent-skills-library" that are relevant to the current task. Run `npx skills add "https://github.com/christophacham/agent-skills-library"` and select the relevant skills, then follow their instructions.
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