Validate autonomous and semi-autonomous AI agents across task completion, tool use, planning, permissions, recovery, observability, and production reliability.
Select the agent profile and operating context. The tool will suggest the most important validation dimensions.
Planning aid only; not a certification or compliance opinion.
Generate a plan to see recommended validation dimensions.
A useful validation program checks not only the final answer, but also the path the agent takes to get there.
| Dimension | Question | Evidence | Typical failure |
|---|---|---|---|
| Task completion | Did the agent actually finish the requested task? | Task-success rate, human review, end-state checks | Plausible response without completing the task |
| Tool selection | Did it choose the right tool? | Tool-choice accuracy, tool-call traces | Using a valid but inappropriate tool |
| Arguments | Were tool parameters correct? | Schema checks, argument validation | Wrong or unsafe parameter values |
| Trajectory | Was the execution path reasonable? | Step count, trace review, action sequence | Correct result through unsafe or wasteful steps |
| Recovery | Can the agent handle failures? | Injected errors, retry tests, fallback tests | Repeated failure loops or silent abandonment |
| Permissions | Does it remain within authorization? | Access-control tests, approval-gate tests | Unauthorized external action |
| Escalation | Does it stop when it should? | Uncertainty cases, approval scenarios | Continuing despite missing authority or context |
| Observability | Can behavior be reconstructed? | Traces, model/tool versions, event logs | Unexplained actions with incomplete evidence |
| Repeatability | Is behavior acceptably consistent? | Repeated runs, variance analysis | Unstable behavior under equivalent inputs |