agent-evaluation

Use when testing prompt effectiveness, validating context engineering choices, or measuring agent improvement quality.

Evaluation Approaches:

• LLM-as-Judge - Direct scoring, pairwise comparison, rubric-based

• Outcome-Focused - Judge results, not exact paths (agents may take valid alternative routes)

• Multi-Level Testing - Simple to complex queries, isolated to extended interactions

• Bias Mitigation - Position bias, verbosity bias, self-enhancement bias

Multi-Dimensional Evaluation Rubric:

Dimension	Weight	What It Measures
Instruction Following	0.30	Task adherence
Output Completeness	0.25	Coverage of requirements
Tool Efficiency	0.20	Optimal tool selection
Reasoning Quality	0.15	Logical soundness
Response Coherence	0.10	Structure and clarity