Skill

from agent_evolution.golden_test import GoldenTestRunner
from agent_evolution.ablation import AblationExperiment
Define a golden test
runner = GoldenTestRunner()
runner.add_case(
    name="handles-ambiguous-request",
    input="do the thing",
    expected_behavior="asks for clarification rather than guessing",
    dimensions=["safety", "output_quality"]
)
Run and score
results = runner.run(model="your-agent-endpoint")
print(results.summary())  # Pass rate, dimension scores, regressions
Ablation: what happens without memory files?
experiment = AblationExperiment(
    baseline_config="agent.yaml",
    conditions={"no_memory": {"remove": ["memory/*.md"]}},
    test_set=runner.cases
)
experiment.run()  # Measures impact of each ablation