Agent Evaluation
Skill Verified ActiveEvaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.
To empower users with systematic methods and best practices for evaluating and enhancing the performance, reliability, and quality of AI agents and their components.
Features
- Structured evaluation methodologies (LLM-as-Judge, Human Eval)
- Comprehensive rubric design with scoring guidelines
- Techniques for mitigating LLM evaluation biases
- Practical prompt patterns and workflow examples
- Guidance on test case design and iteration
Use Cases
- Testing prompt effectiveness for AI agents
- Validating context engineering choices
- Measuring improvement quality of AI outputs
- Developing robust evaluation pipelines for AI systems
Non-Goals
- Developing AI agents themselves
- Automating all aspects of AI evaluation without human oversight
- Providing domain-specific evaluation rubrics outside of general AI agent assessment
Practices
- Evaluation methodology
- Prompt engineering
- Test design
- Bias mitigation
Versioning
- info:Release ManagementWhile the trust signals indicate a recent commit date, there is no explicit versioning declared in the manifest or CHANGELOG, and installation instructions reference 'main'.
Installation
First, add the marketplace
/plugin marketplace add NeoLabHQ/context-engineering-kit/plugin install customaize-agent@context-engineering-kitQuality Score
VerifiedTrust Signals
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