Detail how to construct automated pre-production evaluation pipelines for non-deterministic agents. Walk through building an evaluation harness (e.g., tests/eval_agent_trajectory.py using pytest and Cloud Build) executed against static "golden datasets." Contrast three evaluation types: Pointwise (single-turn metric checks), Pairwise (using gemini-2.5-pro as a Model-as-a-Judge), and Trajectory Evaluation (auditing tool invocation sequences using graph edit distance). Focus on the exact mathematical thresholds required to block releases in CI/CD: tool_call_accuracy >= 0.95, trajectory_match_score >= 0.90, and groundedness_score >= 0.90.
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