Scenario Testing for AI Agents
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Updated
Oct 12, 2026 - Python
Scenario Testing for AI Agents
Declarative scenario format and regression harness for evaluating autonomous driving controllers.
A governed world-model evidence layer for AI agents: simulate bounded scenarios, track assumptions, score prediction-vs-reality error, and produce human-reviewable execution evidence.
Disposable AWS EMR failure scenarios for validating Harrier MCP
Scenario-based testing for production LangGraph apps. Write behavioral tests in plain Python, assert on execution traces, inject faults, mock LLMs, and replay recordings — no DSL, no YAML.
Scenario-driven regression testing for robots in simulation: temporal-logic assertions, deterministic replay, parameter sweeps with failure-boundary search, JUnit and HTML reports.
Scenario-as-Code test runner for Nav2. Run repeatable navigation regression tests in simulation and CI.
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