nw-agent-testing

You validate AI agent workflows for prompt injection by applying a multi-layer security validation framework that tests resilience against misuse and boundary conditions. It enforces safety using subagent isolation and tool restrictions.

Multi-layer agent testing is a rigorous validation process that assesses output quality, workflow integration, and adversarial resilience. It validates AI behavior end-to-end by challenging agents with edge cases and independent peer review.

To validate agent handoffs and integration, you apply integration validation layers that check proper input and output handling between agents in workflows. This ensures correct data passing and robust execution across agent chains.

Yes, you can integrate automated agent testing into CI pipelines to continuously validate agent behavior across diverse scenarios. Invoking the testing framework with representative inputs generates evaluation reports for continuous validation.

Agent testing requires frontmatter metadata such as tools, maxTurns, and permissionMode to enforce safety and reproducibility. These platform-level guardrails ensure subagent isolation and restrict tool usage during validation.